RALEIGH, N.C.–(BUSINESS WIRE)–Red Hat, Inc., the world’s leading provider of open source solutions, today announced several upgrades to its enterprise automation platform, including the latest version of Red Hat Ansible Automation Platform with new Red Hat Certified Ansible Content Collections, automation services catalog and private Automation Hub.

With dynamic global challenges requiring rapid adjustments in operational domains and environments, automation projects have helped mitigate the complexity that these conditions produced and provides faster responses to changing business requirements. Bringing together teams for improved collaboration, these new services and offerings ultimately connect business managers with automation leaders to better align automation strategies with the needs of the business and expand how automation can be invoked.

In a related announcement, Red Hat previewed an integration between Red Hat Advanced Cluster Management and Ansible Automation Platform, bridging the divide between traditional IT environments and cloud native, container-based solutions. This integration unites two of Red Hat’s industry-leading platforms, Red Hat OpenShift and Ansible Automation Platform, to drive automation across the open hybrid cloud.

Additional Certified Content Collections: in-demand automation code made more readily available

Introduced in 2019, Ansible Content Collections provide a standardized method for automation developers to build and package automation content, and for implementers to consume them in a portable and scalable way. Ansible Content Collections bring guardrails and structure to automation content, packaging Collections into categories based on automation domain or platform. Collections delivered in Ansible Automation Hub are certified by the Ansible partner network and are tested, validated and fully supported for enterprise-class production environments.

The newest version of Ansible Automation Platform is slated to include newly certified Ansible Content Collections for Red Hat OpenShift, Kubernetes Core and VMware vSphere REST API. These Collections showcase Red Hat’s continued commitment to automating cloud and Kubernetes platforms for modern IT. Hybrid cloud use cases have pressed forward, whether it’s utilizing native Kubernetes or Red Hat OpenShift, these Certified Content Collections enable automation for various container management systems.

With the addition of these new Collections, there are now more than 60 Ansible Content Collections available from Red Hat and its partners in Automation Hub; you can view a full list of supported and certified Ansible Content Collections.

Building internal automation content communities with private Automation Hub

Ansible Automation Hub is a managed cloud service to provide easy access to certified Ansible content for customers, maintained by Red Hat and our partners. As automation efforts expand across organizations, individual teams often look to integrate automation as part of their overall IT strategy, while IT leaders want the ability to ensure security and manageability of unsupported content. Private Automation Hub delivers a central location for internal automation communities to manage and curate their Ansible content privately, using trusted content from Red Hat, its partners and internal developers.

Private Automation Hub enables content creators as part of enterprises to collaborate and publish trusted, verified resources from a single source, helping to streamline Ansible code within an organization and create a knowledge guide for automation newcomers. More advanced teams can still use this content as a basis for automation, while the organization as a whole gains the ability to manage and control the lifecycle of Ansible automation content as needs scale across the hybrid cloud.

Driving customized automation for the open hybrid cloud

Announced at Red Hat Summit 2020, the automation services catalog makes enterprise-specific, pre-approved, curated automation available to infrastructure and application teams, as well as to business users. This capability helps provide IT administrators and security operations teams with greater visibility over what is being automated while not slowing down organization-wide automation practices. With the addition of the connector technology in the automation services catalog, customers can now bring the automation services catalog directly and more securely to their own private infrastructure, enhancing control over what automation practices are being used.

The connector technology also enables organizations to maintain business-specific controls and compliance mechanisms, while developers can still access the information they need, faster. New integrations for Information Technology Service Management (ITSM) also extends the automation services catalog to platforms like BMC Remedy and ServiceNow, reducing friction in proactively completing ITSM rulesets and standards tasks. This can help drive greater efficiency for teams that are seeking to make Ansible automation a key part of their overall business strategy and not simply a siloed IT component.

Automation as an enterprise imperative

Red Hat acquired Ansible in 2015, and since then, the world of IT has changed.

Organizations now understand that automation can provide faster responses to changing business requirements, and provides the capability to automate more aspects of a business as a driver for future plans. According to a 2020 Forrester report commissioned by Red Hat, automation is a necessity; three out of five respondents reported automation as one of their firms’ top initiatives, even amid competing priorities like adoption of cloud, containers and security management. This imperative for automation has fueled momentum around Ansible, making it a leader in infrastructure automation platforms today:

More than 87% of U.S. executive departments and 83% of airlines in the Fortune 500 use Ansible Automation Platform
Organizations across industries are running Ansible Automation Platform to manage global operations, freeing up IT teams to focus on digital transformation and business-level innovations.
IT automation knowledge is now frequently cited amongst the most in-demand job skills.
Ansible Automation Platform enables customers to move away from do-it-yourself, siloed approaches and to improve ROI. These customers are automating millions of nodes with Ansible as part of a modernization of management approach.

Availability

The latest version of Red Hat Ansible Automation Platform is slated for November release, including private Automation Hub on-premise or in the cloud of your choice. The connector technology in the automation services catalog will also be available next month for technology preview. The new Ansible Content Collections are available now on cloud.redhat.com, with additional Collections released on a rolling basis.

Supporting Quotes

Joe Fitzgerald, vice president, Management, Red Hat
“Ansible has evolved into a defacto standard for automation and became one of the top 10 open source projects in the world, according to a most recent study. Red Hat has built an automation platform for enterprises to more easily access, consume and share Ansible content to significantly reduce the time-to-automation. As customers continue down the path of digital transformation, these pre-integrated resources can address common use cases while advancing the management and innovation of traditional and cloud-native infrastructure.”

Five Years in the Making: Ansible for DevOps, 2nd Edition

After five years of continuous development, 834 commits, and 24 major revisions, Jeff Geerling published the 2nd edition of Ansible for DevOps. The book has sold over 60,000 copies and served as the foundation for a free Ansible 101 video series on YouTube. The 2nd edition marks the start of the 2.x revision series.

The book covers a broad range of infrastructure automation topics:

• Managing Linux servers with Ansible basics
• Continuous integration pipelines
• Application deployments
• Container image management
• Kubernetes cluster management with Ansible

The Problem with Traditional Edition-Based Publishing

Geerling’s original commitment was simple: ebook updates would be free, forever. He has published at least one new revision per quarter since the first release (version 0.42 on LeanPub in 2014). However, selling through Amazon introduced friction: Amazon follows the traditional publishing convention of “editions,” where any substantive update beyond minor corrections requires a new edition — complete with a new ISBN and a new product listing.

This model made sense in the era of print, but it creates a poor experience for readers of digital technical books. Anyone who has owned outdated print books on Python 2, PHP 5, or legacy Linux distributions understands the problem. Technology moves faster than print publishing cycles, and readers who buy digital copies deserve to benefit from an author’s ongoing improvements.

What an Evergreen Technical Book Looks Like in Practice

Keeping a technical book genuinely current requires more than occasional edits. Geerling’s approach to maintaining Ansible for DevOps as an evergreen resource included:

• Quarterly revisions to reflect new Ansible releases, deprecation cycles, and evolving best practices.
• Chapter rewrites when underlying architecture shifted significantly enough to make older guidance misleading.
• A companion GitHub repository containing all code examples from the book, with CI tests that run on a weekly schedule to catch bit rot — examples that silently break as dependencies, APIs, or Ansible modules change.
• An open issue tracker where readers can report broken or confusing examples, and submit patches directly.

The CI testing approach is particularly notable for a book project. Rather than relying solely on manual review, automated weekly test runs surface problems proactively, before readers encounter them.

The Financial Case for Self-Publishing Technical Books

Geerling is candid about the economics. Over five years, Ansible for DevOps earned him nearly $200,000 in royalties — after platform fees of 30–70% from Amazon, Apple Books, and LeanPub (LeanPub being the most author-generous of the three).

For context, a comparable deal with a traditional publisher might have yielded:

• A few thousand dollars as an advance
• Roughly a 5% royalty rate on net sales
• No royalties until the advance was earned out
• An estimated total return of under $50,000 for the same sales volume

Self-publishing platforms like LeanPub typically return 70–80% of the sale price to the author. Amazon’s cut varies by price tier and format. The gap in author earnings between self-publishing and traditional publishing is substantial, and for a successful title it can represent a difference of four times or more in total income.

“Self-publish, don’t write for a publisher.” — Jeff Geerling

Honest Advice: Don’t Quit Your Day Job

Despite Ansible for DevOps being a genuinely successful technical book — one of the more successful self-published DevOps titles available — Geerling is direct: $200,000 over five years averages $40,000 per year. That is meaningful supplemental income, but it does not replace the salary a skilled DevOps engineer or software architect can command.

His conclusion for anyone considering writing a technical book:

• If you have deep, practical expertise in a cloud or infrastructure topic, your salary as a practitioner will likely exceed your maximum book revenue by a factor of five or more.
• Write the book as a practitioner, not as a full-time author. The best technical books come from people solving real problems in production environments, not from authors who write to fill a publisher’s catalog.
• “Fluff” tech books — written by light users of a tool or by serial authors without hands-on depth — are immediately apparent to experienced readers and rarely offer the small, high-value tips that justify the purchase price.

LeanPub and the Lean Publishing Model

One of the practical enablers of Geerling’s approach is LeanPub, a publishing platform designed for iterative, in-progress book writing. Key properties that make it well-suited for technical authors:

• You can publish and sell a partial, in-progress manuscript immediately.
• Readers who buy early can engage with the content and provide feedback while the book is still being written.
• Updates to buyers are automatic and free — no new purchase required.
• Author royalty rates are significantly higher than traditional publishers or even most major retail platforms.

This model validates demand early, reduces the risk of spending months writing a book nobody wants, and aligns author incentives with reader experience over the long term.

What This Means for DevOps Engineers Considering Writing

If you are a DevOps or platform engineering practitioner with genuine depth on a specific tool or workflow, self-publishing a technical book is a viable way to build credibility, contribute to the community, and earn supplemental income. The key takeaways from Geerling’s experience:

• Start lean. Publish early on a platform like LeanPub and iterate publicly.
• Automate quality assurance. Treat code examples like production code — use CI to test them on a regular schedule.
• Commit to maintenance. A technical book that goes stale within a year damages your reputation more than not writing one at all.
• Self-publish first. Traditional publishing deals rarely make financial sense for technical authors with the motivation to self-publish.
• Keep your day job. Even a successful technical book is unlikely to match your engineering salary.

About the Books

Ansible for DevOps, 2nd Edition is available on Amazon, LeanPub, and Apple Books. Jeff Geerling is also writing Ansible for Kubernetes, a deeper dive into Kubernetes and container automation with Ansible, available in progress on LeanPub with the same free-updates-forever commitment.

For more from Jeff Geerling, see jeffgeerling.com.

Overview

Red Hat announced a series of updates to the Ansible Automation Platform, its enterprise-grade automation solution that helps DevOps teams create, manage, and share resources for automating application and infrastructure deployments. The updates span three key areas: a new Automation Services Catalog, expanded certified content, and improved analytics capabilities.

The Ansible Automation Platform was introduced in late 2019 with the goal of enabling scalable, enterprise-wide automation across projects and teams. Red Hat framed the April 2020 updates as particularly relevant given the economic pressures organizations were facing at the time, emphasizing the platform’s value proposition of helping enterprises “do more with less.”

Automation Services Catalog

Scheduled for a late May 2020 rollout, the Automation Services Catalog provides organizations with a structured way to govern and extend automation across the enterprise while maintaining compliance requirements and internal controls.

Key capabilities of the Automation Services Catalog include:

• Lifecycle management for automation resources, enabling teams to track and govern automation assets from creation through retirement.
• Compliance and controls enforcement, ensuring that automation resources meet organizational policy requirements before being deployed broadly across teams.
• A centralized service interface that makes it easier to offer automation capabilities as self-service resources to different teams and business units.

Expanded Certified Content in Ansible Content Collections

Red Hat significantly expanded the certified content available through Ansible Content Collections, the packaging format that allows users to share and consume reusable automation content including modules, plugins, roles, and playbooks.

At the time of the announcement, Automation Hub—the centralized content repository for Red Hat and its certified partners—hosted more than 1,200 certified Ansible Modules. This represented a dramatic increase from approximately 100 modules available in November 2019, reflecting rapid growth in Red Hat’s partner ecosystem and content certification program.

Automation Hub serves as the trusted source for certified, supported content, offering DevOps teams confidence in the quality and compatibility of the automation resources they consume.

Enhanced Analytics Capabilities

Red Hat also introduced new analytics features within the platform to give operators and engineers deeper visibility into automation performance. The enhancements focus on helping teams understand how their automation is running and where improvements can be made.

New and improved analytics features include:

• Improved filtering: Users can now filter analytics down to individual Red Hat Ansible Tower clusters and filter results by date range.
• New job statistics: Metrics now include total runs, total execution time, average execution time, overall success rate, and identification of the most frequently failed task.
• Organizational comparison filters: Within organizational statistics, new filters allow teams to compare automation adoption rates and activity across different internal organizations or business units.

These analytics improvements are aimed at helping platform administrators and DevOps leads demonstrate the value of automation investments and identify bottlenecks or reliability issues in their automation workflows.

Why These Updates Matter for DevOps Teams

Taken together, these updates address three common challenges DevOps teams face when scaling automation across an enterprise:

1. Governance at scale: The Automation Services Catalog helps platform operators enforce policies and compliance requirements without blocking teams from consuming automation resources.
2. Content quality and discovery: The growth in certified modules reduces the risk of relying on untested community content and makes it easier to find supported integrations for common platforms and services.
3. Operational visibility: The new analytics features close the feedback loop, allowing teams to measure automation effectiveness and troubleshoot failures more efficiently.

For DevOps engineers evaluating or already running the Ansible Automation Platform, the April 2020 updates represented a meaningful step toward making enterprise-scale automation more manageable, observable, and compliant.

What Is Build Automation Software?

Build automation software orchestrates the steps required to transform source code into a deployable artifact. At a minimum, that means compiling code, resolving dependencies, running unit tests, and packaging the result. More mature pipelines extend automation to integration testing, static analysis, security scanning, artifact publishing, and deployment. The goals are consistency (every build follows the same steps), speed (automation is faster than manual processes), and auditability (every build is logged and reproducible).

Build automation tools are typically categorized along two axes:

• Delivery model: Self-hosted (installed on your own infrastructure) vs. cloud-hosted SaaS
• Scope: Build-focused tools vs. full CI/CD platforms that also handle deployment orchestration

Key Tools in the Build Automation Ecosystem

The following tools represent the most widely adopted options across enterprise and open-source environments. Each has a distinct philosophy, integration footprint, and target user base.

Jenkins

Jenkins is the most widely deployed open-source CI/CD server. It is self-hosted, written in Java, and extensible through a plugin ecosystem of over 1,800 community-maintained plugins. Jenkins pipelines are defined in a Jenkinsfile using a Groovy-based DSL, and the tool supports both declarative and scripted syntax.

Best for: Teams that need maximum flexibility and are comfortable managing their own infrastructure. Jenkins suits complex, custom pipeline requirements where off-the-shelf SaaS tools fall short.

Watch out for: Operational overhead. Jenkins requires maintenance of the server, plugins, and agents. Plugin compatibility issues are a common pain point as the ecosystem ages.

TeamCity

TeamCity is a CI/CD server developed by JetBrains. It is available as a self-hosted installation and as a cloud-hosted offering (TeamCity Cloud). TeamCity provides a rich web UI, excellent out-of-the-box support for .NET, Java, and Kotlin projects, and deep integration with JetBrains IDEs.

Best for: Teams already using JetBrains tools, .NET shops, and organizations that want a polished UI without writing pipeline-as-code from scratch. TeamCity has a free tier for small teams.

CircleCI

CircleCI is a cloud-native CI/CD platform that defines pipelines in a YAML configuration file (.circleci/config.yml). It offers fast build times through parallelism and caching, first-class Docker support, and an orbs system for reusable pipeline components. A self-hosted server option is also available for enterprises.

Best for: Teams that want a managed, scalable CI/CD platform with minimal infrastructure management. CircleCI integrates tightly with GitHub and Bitbucket.

Bamboo

Bamboo is Atlassian’s self-hosted CI/CD server. It integrates natively with Jira, Bitbucket, and Confluence, making it a natural fit for teams already in the Atlassian ecosystem. Bamboo uses a plan-and-stage model to organize builds and deployments.

Best for: Atlassian-heavy shops that want CI/CD tooling consistent with their existing project management and source control stack. Note that Atlassian has been encouraging migration to Bitbucket Pipelines for cloud-based workflows.

Ansible

Ansible is an open-source IT automation tool from Red Hat. It is agentless, uses SSH for communication, and describes automation tasks in human-readable YAML playbooks. While Ansible is not a CI/CD server in the traditional sense, it is widely used as the deployment layer in build pipelines — handling configuration management, application deployment, and infrastructure provisioning.

Best for: Infrastructure automation, configuration management, and deployment orchestration. Ansible is commonly paired with Jenkins or another CI server rather than used as a standalone build tool.

Microsoft Azure DevOps (formerly Team Foundation Server)

Azure DevOps is Microsoft’s end-to-end DevOps platform, encompassing Azure Repos (source control), Azure Pipelines (CI/CD), Azure Boards (work tracking), and Azure Artifacts (package management). Pipelines are defined in YAML and support build, test, and release stages with strong integration across the Azure ecosystem.

Best for: Microsoft-centric organizations (.NET, Azure infrastructure) and enterprises wanting a single platform spanning the entire software delivery lifecycle.

Apache Maven and Gradle

Maven and Gradle are build tools rather than CI servers — they handle dependency resolution, compilation, testing, and packaging at the project level. They are typically invoked by a CI server (Jenkins, CircleCI, etc.) rather than replacing one.

• Maven uses XML (pom.xml) and a convention-over-configuration model. It is the dominant build tool in the Java enterprise world.
• Gradle uses a Groovy or Kotlin DSL (build.gradle) and offers incremental builds and a flexible task model. It is the default build tool for Android development and is gaining ground in general JVM projects.

Travis CI

Travis CI was one of the first cloud-hosted CI services to gain widespread adoption in the open-source community, largely due to its free tier for public GitHub repositories. Configuration is defined in a .travis.yml file. Travis CI’s open-source offering has changed ownership and pricing models in recent years, leading many projects to migrate to GitHub Actions or CircleCI.

Codeship

Codeship (now part of CloudBees) is a hosted CI/CD platform offering two modes: Codeship Basic (simple, UI-configured pipelines) and Codeship Pro (Docker-based pipelines defined in YAML). It targets teams that want a straightforward setup without deep infrastructure knowledge.

Chef

Like Ansible, Chef is a configuration management tool rather than a CI/CD server. Chef uses Ruby-based recipes and cookbooks to define the desired state of infrastructure. It is agent-based (requiring the Chef client on managed nodes) and is commonly used alongside CI/CD pipelines to manage server configuration and compliance.

Cloud-Based vs. Self-Hosted Build Automation

One of the most consequential decisions when choosing a build automation platform is whether to run it yourself or consume it as a managed service.

Enterprise vs. SME Considerations

Build automation requirements differ significantly between large enterprises and small-to-medium teams.

Large Enterprises

• Typically require on-premises or private-cloud deployment for compliance and data sovereignty reasons
• Need role-based access control, audit logging, and SSO integration
• Often run heterogeneous build environments (multiple languages, platforms, and deployment targets)
• Benefit from tools like Jenkins (flexibility), TeamCity (enterprise features), or Azure DevOps (Microsoft stack integration)

Small and Medium Teams

• Prefer managed services to reduce operational burden
• Value fast setup, good documentation, and transparent pricing
• GitHub Actions, CircleCI, and Bitbucket Pipelines are popular choices due to tight SCM integration and generous free tiers

How to Evaluate Build Automation Tools

When assessing tools for your environment, consider the following criteria:

1. Pipeline-as-code support: Does the tool allow you to define pipelines in version-controlled files? YAML and Groovy DSL are common formats. Pipeline-as-code is a best practice for auditability and reproducibility.
2. Language and framework support: Does the tool have native support or well-maintained integrations for your primary languages and build tools (Maven, Gradle, npm, Make, etc.)?
3. Integration with your SCM: Native GitHub, GitLab, or Bitbucket integration simplifies webhook configuration, pull request status checks, and branch policies.
4. Artifact management: Can the tool publish and retrieve build artifacts from repositories like Nexus, Artifactory, or cloud-native artifact stores?
5. Scalability: How does the platform handle concurrent builds? Can you add build agents horizontally?
6. Security features: Secret management, least-privilege runner permissions, and dependency scanning are table stakes for production pipelines.
7. Total cost of ownership: Include licensing, infrastructure, and engineering time for setup and maintenance.

The Broader DevOps Context

Build automation does not exist in isolation. It is one layer in a broader DevOps toolchain that typically includes source control management, artifact repositories, container registries, deployment orchestration (Kubernetes, Helm, Ansible), monitoring, and incident response. The best build automation tool is the one that integrates cleanly with the rest of your stack and that your team will actually maintain and improve over time.

As DevOps practices mature, build pipelines are also incorporating security scanning (the “shift left” security movement), infrastructure-as-code validation, and policy enforcement as automated gates — turning the build pipeline into a quality and compliance checkpoint, not just a compilation step.

Summary: Tool Selection at a Glance

Build automation is a high-return investment for any engineering team. Starting with a clear understanding of your pipeline requirements, your team’s operational capacity, and your existing toolchain will put you in a much stronger position to choose and implement the right platform.

What Are Automotive Driving Simulators?

Automotive driving simulators are hardware and software systems that replicate real-world vehicle dynamics and driving environments in a controlled setting. They are used across a wide range of applications — from training drivers and testing autonomous vehicle software to entertainment and regulatory compliance testing. High-fidelity simulators can reproduce steering feedback, road surface characteristics, vehicle roll and pitch, and environmental conditions without requiring a physical road test.

The global market for these systems has grown steadily as automotive OEMs, motorsport organisations, transport authorities, and training institutions invest in simulation technology to reduce development costs, improve safety outcomes, and accelerate the validation of advanced driver assistance systems (ADAS) and autonomous driving stacks.

Key Market Players

The Eon Market Research report identifies several established vendors competing in the global automotive driving simulators space:

• Ansible Motion – Known for high-fidelity dynamic driving simulators aimed at vehicle development and motorsport applications.
• Cruden – Supplies professional driving simulators for motorsport teams, OEM research, and training environments.
• Dallara – An Italian chassis manufacturer with simulator capabilities, primarily serving motorsport and automotive engineering.
• Mechanical Simulation – Provides vehicle dynamics simulation software widely used in engineering and research contexts.
• Moog – A motion control technology company whose simulation platforms are used in automotive, aerospace, and defence sectors.
• Oktal (Sogeclair Group) – Specialises in driving simulation software and hardware solutions for transport and defence applications.

Each vendor competes on dimensions including motion platform fidelity, software integration capabilities, latency, customisability, and total cost of ownership. The report is said to include financial overviews, R&D investment data, and product portfolio details for these players, though those specifics are not reproduced here.

Market Segmentation by Product Type

The report segments the automotive driving simulator market into four primary product categories:

• Modular Design Simulator – Configurable platforms that can be adapted for different vehicle types and research requirements.
• Multi-Station Driving Simulator – Systems supporting multiple simultaneous users, commonly deployed in large training facilities.
• Bus Simulator – Specialised simulators designed specifically for public transport driver training, replicating the ergonomics and dynamics of buses and coaches.
• Physical Simulator – Full-scale or near-full-scale physical mockups with motion systems, providing the highest level of immersion.

Market Segmentation by Application

On the demand side, the report categorises end-use applications as follows:

• Entertainment – Arcade-style and immersive consumer driving experiences.
• Training Institutions – Driving schools, fleet operator training centres, and vocational programmes.
• Transport Authorities – Government and public-sector bodies using simulation for licensing assessment, road safety research, and emergency response training.
• Other – Automotive OEM R&D, motorsport engineering, ADAS validation, and academic research.

Regional Breakdown

The report covers the following geographic regions and sub-markets:

• North America – United States, Canada, Mexico
• Asia-Pacific – China, India, Japan, South Korea, Australia, Indonesia, Malaysia, Philippines, Thailand, Vietnam
• Europe – Germany, France, United Kingdom, Italy, Russia
• Central & South America – Brazil, Rest of Central & South America
• Middle East & Africa – GCC Countries, Egypt, South Africa

Regional segmentation of this kind is typically used to identify where demand is growing fastest, which regulatory environments are most favourable to simulator adoption, and where infrastructure investment in training or autonomous vehicle testing is concentrated.

Analytical Framework Used in the Report

According to the source summary, the report structures its analysis across 13 chapters, covering:

• Industry overview, definitions, and specifications
• Manufacturing cost structure, including raw materials, equipment, and labour
• Competitive landscape and regulatory framework
• Technical data, manufacturing plant analysis, capacity, and production figures
• Revenue, price, cost, gross margin, and consumption analysis by type, region, and manufacturer
• SWOT analysis and Porter’s Five Forces analysis for strategic context
• Investment outlook and business strategy profiles of key players

SWOT and Porter’s Five Forces are standard strategic analysis tools. Their inclusion suggests the report is aimed at business strategists and investors evaluating entry into or expansion within the automotive simulation market, rather than purely technical engineering audiences.

Why This Market Matters for DevOps and Automotive Engineering Teams

For DevOps engineers working in automotive or mobility contexts, driving simulators are increasingly relevant infrastructure. ADAS and autonomous vehicle software requires massive volumes of simulated test scenarios — something physical road testing cannot practically deliver at scale. Simulation platforms are now tightly integrated with CI/CD pipelines, enabling automated regression testing of vehicle perception, decision-making, and control software in virtual environments.

Vendors like Mechanical Simulation and Oktal offer software APIs and integration hooks that allow engineering teams to run simulator scenarios as part of automated build validation. Understanding which vendors dominate the market, and what product categories are growing, is useful context for teams evaluating toolchain partnerships or infrastructure investment.

About the Source

This article is based on a market intelligence report summary published by Eon Market Research (EMR), a market research firm providing quantitative forecasting and trend analysis across multiple industries. The original summary was referenced via fashiontrendsnow.com. Full report details and purchase information would be available directly from EMR.

The Ansible Certified Content available on IBM Z provides easy to use automation building blocks and will promote the automation of IBM Z applications.

IBM has announced the general availability of Red Hat Ansible Certified Content for IBM Z enhancing the collective experience of IT Infrastructure, cloud, and its applications. This would make it possible for the Ansible users to automate the IBM Z applications and will allow data management across hybrid environments through a single control panel.

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Developers can use the Certified Content from the Automation Hub, which, along with this, will be housing an upstream open source version offered on Ansible Galaxy. Additionally, it enables users to simplify the configuration, access resources, streamline automation of operations, and leverage existing automation.

Red Hat Ansible Certified Content provides easy to use automation building blocks. These blocks can accelerate the pace of automation of z/OS and z/OS-based software. It includes action plugins, connection plugins, modules, and a sample playbook that help in automating tasks for z/OS, such as retrieving job output, creating data sets, and submitting jobs.

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Skyla Loomis, Director, IMS and z/TPF, IBM Z Software, said while talking exclusively to toolbox, “In today’s hybrid IT world, an enterprise-wide strategy to provide consistent automation is critical for clients on their journey to cloud. Bringing Ansible to IBM Z is a big step forward toward making this a reality – enabling our clients to take advantage of automation spanning their IT infrastructure, clouds and applications.”

Ansible enables users to break down the conventional internal technology silos to centralize automation and maintain the performance, scale, control, and security provided by IBM Z.

What Was Announced

IBM announced the general availability of Red Hat Ansible Certified Content for IBM Z, enabling Ansible users to automate IBM Z (mainframe) applications and IT infrastructure using the same automation toolchain they deploy across the rest of their hybrid environment. The Certified Content is available through Red Hat Automation Hub for Ansible Automation Platform subscribers, with an upstream open-source version published on Ansible Galaxy under the collection name ibm.ibm_zos_core.

Why This Matters for Hybrid IT

Enterprise IT environments are rarely homogeneous. Organizations running IBM Z mainframes alongside x86 servers, private clouds, and public cloud services have historically needed separate automation stacks for each platform. This fragmentation increases operational overhead, slows down delivery pipelines, and creates inconsistencies between environments.

By bringing IBM Z into the Ansible ecosystem, organizations can manage their entire infrastructure — including z/OS workloads — through a single control plane. This removes one of the most persistent silos in enterprise IT: the gap between mainframe operations and the DevOps tooling used everywhere else.

What the ibm.ibm_zos_core Collection Includes

The initial release of the core collection ships with the following automation building blocks for z/OS:

• Connection plugins – Enable Ansible to communicate securely with z/OS hosts.
• Action plugins – Extend standard Ansible action handling for z/OS-specific workflows.
• Modules – Purpose-built modules covering common z/OS tasks, including:
  • Creating and managing data sets
  • Retrieving job output (JES spool)
  • Submitting batch jobs (JCL)
• Sample playbooks – Reference playbooks to accelerate onboarding and demonstrate best practices.

The collection is delivered as a fully supported, enterprise-grade Red Hat Ansible Certified Content Collection, meaning it carries Red Hat’s quality and support guarantees for Ansible Automation Platform subscribers.

Key Benefits for z/OS Operators and Developers

• Consistent automation language: Teams already writing Ansible playbooks for Linux, Windows, or cloud infrastructure can apply the same YAML-based syntax to z/OS tasks — no separate scripting language or mainframe-specific tooling required.
• Simplified configuration management: Automate configuration and resource access on z/OS using standard Ansible inventory and variable management.
• Leverage existing automation investments: Existing Ansible roles and workflows can be extended to include z/OS steps, rather than building parallel automation pipelines.
• Accelerated z/OS DevOps: Integrates with CI/CD pipelines using tools like Jenkins and Git, which IBM had already been introducing to the Z platform through projects like IBM Z Open Editor, IBM Developer for z/OS, and the Zowe open-source framework.
• Performance, scale, and security: Automation runs against a platform already known for its reliability and security characteristics, without sacrificing those properties.

Context: IBM Z’s Broader DevOps Push

The Ansible Certified Content announcement built on several earlier IBM Z modernization efforts:

• Zowe – An open-source framework (of which IBM is a founding member) that brings modern interfaces and APIs to z/OS.
• IBM Z Open Editor – A VS Code extension for editing COBOL, PL/I, and JCL on z/OS.
• IBM Developer for z/OS V14.2.1 – An IDE update aimed at improving developer productivity on the platform.
• Red Hat OpenShift on IBM Z – Announced in early 2020, enabling cloud-native containerized workloads to run on IBM Z hardware alongside traditional workloads.

Together, these initiatives represent IBM’s strategy of bringing industry-standard, open-source DevOps tooling to the mainframe rather than asking enterprises to choose between the mainframe and modern development practices.

Where to Get Started

There are three primary entry points depending on your subscription and preference:

1. Ansible Galaxy (ibm.ibm_zos_core) – Free, open-source version for evaluation and community use. Search for the collection on galaxy.ansible.com.
2. Red Hat Ansible Automation Hub – The fully supported, certified version for Ansible Automation Platform subscribers.
3. GitHub – Source code and documentation for the open-source upstream project, where community contributions and issue tracking are hosted.

Summary

Red Hat Ansible Certified Content for IBM Z closes a long-standing automation gap in hybrid enterprise environments. By allowing operations teams and developers to manage z/OS through the same Ansible playbooks, inventories, and control planes they use for the rest of their infrastructure, IBM and Red Hat have made it meaningfully easier to include mainframe workloads in modern DevOps and infrastructure-as-code practices — without requiring separate toolchains or deep mainframe scripting expertise for routine automation tasks.

Note: IBM’s statements regarding product direction are subject to change at IBM’s sole discretion and should not be taken as binding commitments.

What Cumulus Networks Released

Cumulus Networks released an open source toolkit designed to automate network testing and configuration for data center deployments. The toolkit targets network and DevOps engineers who understand the theory behind CI/CD and infrastructure as code (IaC) but struggle to translate those concepts into production network environments.

“Everyone understands the concepts of CI/CD, everyone understands the value of infrastructure as code, but they struggle to put it into production,” said Partho Mishra, president and chief product officer at Cumulus Networks.

According to Mishra, Cumulus had been using the toolkit internally for approximately two years to design and deploy customer networks before deciding to open source it.

What the Toolkit Includes

The toolkit is described as an out-of-the-box, production-tested package. Its components include:

• A fully populated variables file object model — structured variable definitions that represent network topology and configuration state
• Jinja2 templates — for rendering device configurations dynamically from those variables
• Ansible playbooks — for orchestrating configuration pushes across network devices
• Network validation tests — enabling continuous integration (CI) workflows against live or virtual network environments
• An infrastructure-as-code deployment framework — tying the above components into a repeatable, version-controlled workflow

Importantly, the toolkit relies only on Ansible core modules and does not require any additional plugins or vendor-specific add-ons, lowering the barrier to adoption.

“We are essentially open sourcing a complete, out-of-the-box package of tested scripts and playbooks that can be used to set up typical data center and other network deployments.”

— Partho Mishra, President and CPO, Cumulus Networks

Licensing and Availability

The toolkit was published to GitLab under a Creative Commons license, making it freely distributable and modifiable. Cumulus expressed the intent to grow a community around the codebase, with the expectation that community contributions would accelerate broader adoption of network automation practices.

Why Ansible—and What Comes Next

Cumulus selected Ansible as the automation engine because it was the most widely used tool in their customer base at the time of release. However, Mishra indicated that support for Chef, Puppet, and SaltStack was planned for the following months, allowing teams using those tools to adopt the same framework.

Automated Testing with NetQ and Cumulus VX

A key differentiator of the toolkit is its integrated testing pipeline. When code is committed to the repository, it automatically triggers the creation of a virtual lab environment using Cumulus VX—a virtual instance of Cumulus Linux. The pipeline then runs a suite of validation tests using Cumulus NetQ, the vendor’s telemetry and network validation platform.

Tests performed include:

• Validating Maximum Transmission Units (MTUs) across links
• Verifying that routing sessions (such as BGP peers) come up as expected
• Broader functional validation to catch configuration errors before they reach production

Mishra underscored why automated validation matters in this context: “With automation you can set up 500 switches with the push of a button, but you can also destroy 500 switches with the push of a button. The validation suite looks for functional errors.”

This closed-loop approach—commit code, spin up a virtual lab, run tests, validate before deploying to production—mirrors standard software CI/CD pipelines and brings that discipline to network operations.

Cumulus in the Cloud Updates

Alongside the toolkit release, Cumulus also updated Cumulus in the Cloud, its self-service demo environment. According to the company, the updated environment provides:

• A fully configured spine-and-leaf network topology running Cumulus Linux
• Servers running Ubuntu integrated into the topology
• All nodes connected to and monitored by Cumulus NetQ
• A ready-to-use environment provisioned in under five minutes
• Deployable, production-ready demo scenarios
• Access to the Cumulus NetQ 2.0 CLI and GUI within the demo environment

The demo environment gives network engineers a low-risk way to evaluate the toolkit and NetQ before committing to a production rollout.

Why This Matters for Network DevOps

Network automation has lagged behind application-layer DevOps for years, largely because purpose-built tooling for network IaC was scarce and vendor-specific. By releasing a complete, tested, Ansible-native framework under a permissive license, Cumulus lowered the practical barrier for network teams to adopt GitOps-style workflows for switch configuration and validation.

The use of standard tools—Ansible, Jinja2, GitLab CI—means engineers do not need to learn a proprietary DSL or lock themselves into a single vendor’s management plane. The framework is portable in principle, and community contributions could extend it to support additional platforms and automation engines over time.

Note: Cumulus Networks was acquired by NVIDIA in 2020. Current availability and licensing of this toolkit should be verified against NVIDIA’s current documentation and repositories.

Why Network Engineers Start with Ansible

Ansible has earned its place as a common entry point for network automation. Its low barrier to entry, human-readable playbook syntax, and broad module ecosystem make it accessible to network engineers who may not have a software development background. Before examining where Ansible falls short, it helps to understand why so many teams reach for it first.

Ansible Strengths for Network Automation

• Easy-to-learn YAML syntax: Ansible playbooks are sequential task definitions written in YAML. Engineers already comfortable with device CLIs — configuring QoS policies, ACLs, or route maps — tend to pick up YAML quickly.
• Extensive module library: Ansible modules abstract away low-level operations. Dedicated network modules allow you to execute commands on devices, collect output, and push configuration changes without writing custom scripts.
• Jinja2 templating: The built-in Jinja2 engine lets you use variables inside playbooks and configuration templates, making it straightforward to generate device-specific configs from a shared template.

This combination — simple syntax, a rich module library, and templating — means teams can automate routine tasks quickly. For collecting troubleshooting data, pushing standard configurations across many devices, or generating compliance reports, Ansible is genuinely effective.

Ansible Limitations for Network Automation

Despite its strengths, Ansible has well-documented limitations that become significant as automation use cases grow more complex. Understanding these limitations before you invest heavily in Ansible-based workflows will save you considerable frustration.

1. Debugging Is Difficult

Ansible includes a playbook debugger, but it is limited in scope. It supports five trigger modes:

• always — trigger the debugger on every task
• never — disable the debugger entirely
• on_failed — trigger only when a task fails
• on_unreachable — trigger when a host cannot be reached
• on_skipped — trigger when a task is skipped

Within a debugging session, you can print or set variables and re-run a failed task. However, you cannot inspect the internal operation of a module. Because many network modules have significant logic inside them, diagnosing failures often means guessing at what the module is doing rather than observing it directly. Failures can be caused by environmental issues entirely outside the playbook — a misconfigured DNS server, for example — and tracking those down through Ansible’s debugger alone is tedious and time-consuming.

2. Performance Degrades with Large Data Volumes

Ansible serializes and deserializes JSON data internally as it passes information between tasks. For small data sets and simple playbooks, this overhead is negligible. When playbooks process large volumes of data — such as full routing tables or extensive device inventories — the serialization cycle becomes a CPU bottleneck and overall execution slows significantly. This is an architectural constraint, not something that can be tuned away easily in most cases.

3. Complex Data Structures Are Awkward to Manage

Many practical network automation tasks require building and manipulating nested or relational data structures. Network discovery is a clear example of where this becomes painful:

• To perform network discovery, you need to maintain a table of already-discovered devices and a queue of devices yet to be checked. Each entry must store neighbor relationships so you can recursively discover the next hop.
• Generating a network topology diagram (for example, using a Graphviz DOT language file to represent physical connectivity) requires correlating neighbor data across multiple devices in a structured way.

While Ansible supports lists and dictionaries in YAML, working with nested, relational structures across tasks quickly becomes unwieldy. The data model that YAML and Ansible variables support is not designed for the kind of graph traversal or relational operations that network discovery and topology tasks require.

4. Control Flow Is Limited

Ansible provides looping constructs and conditional statements, but its control flow capabilities are constrained compared to a general-purpose programming language. Tasks requiring recursive logic, dynamic branching based on accumulated state, or complex iteration over nested data structures push Ansible to its limits. The playbook syntax becomes increasingly difficult to read and maintain as these constructs are layered together. A playbook that includes Jinja2 variable manipulation, nested loops, and conditionals can become nearly impenetrable after a few months — even for the engineer who wrote it.

When Ansible Is the Right Tool

None of these limitations mean you should avoid Ansible. They mean you should be deliberate about where you apply it. Ansible is well suited to tasks that share these characteristics:

• A well-defined, sequential set of steps to execute across many devices
• Configuration pushes or standard remediation tasks
• Collecting troubleshooting output or operational statistics from devices
• Generating configuration files from templates using known variables
• Tasks where the data structures involved are relatively flat and predictable

For these use cases, Ansible’s simplicity and speed of development are genuine advantages over writing custom scripts or adopting a heavier automation framework from the start.

When to Replace Ansible with a More Suitable Tool

The key skill for any automation engineer is recognizing when the tool you have chosen is no longer the right fit. Signals that you may need to move beyond Ansible for a given use case include:

• Your playbooks are growing in length and becoming difficult to follow, even for the person who wrote them
• You need to maintain complex relational state across multiple devices or task iterations
• You require recursive or deeply nested control flow logic
• Performance is suffering because of large data volumes being passed between tasks
• Debugging failures is taking disproportionate amounts of time relative to writing the automation itself

At that point, a general-purpose language such as Python — with libraries like Netmiko, NAPALM, or Nornir — gives you full control over data structures, control flow, and debugging tooling. The good news is that experience with Ansible provides a strong conceptual foundation. Understanding playbooks, inventory, and modules makes the transition to Python-based network automation considerably easier.

Summary

Ansible remains one of the best tools for introducing network engineers to automation concepts. Use it where it fits, recognize its boundaries, and treat those boundaries as a signal to grow your toolset rather than a reason to abandon Ansible entirely.

Red Hat, Inc., the world’s leading provider of open source solutions, today announced that Omnitracs, LLC, the global pioneer of fleet management solutions to transportation and logistics companies, has delivered its Omnitracs One platform, the next-generation of fleet management innovation, on the foundation of Red Hat OpenShift. Using the industry’s leading enterprise Kubernetes platform along with Red Hat Ansible Automation Platform, Omnitracs One is a completely cloud-native offering and provides an enhanced user experience with a clear path towards future innovations.

The transportation industry is undergoing a digital revolution and Omnitracs engaged Red Hat as the partner to help accelerate its own transformation efforts. Omnitracs wanted to build upon proven, cloud-native technologies, but with the backing of enterprise-grade support and expertise. The company selected Red Hat based on its reputation for supporting flexible, open technologies in production environments, as well as its knowledge and leadership in enabling cloud-native innovation.

With Red Hat’s expertise and guidance, Omnitracs was able to effectively embrace a shift from on-premises development technologies to cloud-native services, improving overall operations and creating a more collaborative development process culture. Omnitracs One benefits commercial fleets of all sizes through a superior driver experience, a comprehensive library of third-party integrations, device independence and exchangeable data across operations.

The team also enhanced several capabilities, including:

Driving wholesale transformation across the Omnitracs One platform and the entire development process.
Improving the reliability, scalability and overall platform security of the Omnitracs One solution
Reducing development time to bring new features to market and more quickly address changing customer needs
Red Hat’s collaboration with Omnitracs extended beyond technology development, with Red Hat providing training and strategic guidance on product deployment through Red Hat Open Innovation Labs. The Red Hat team also trained the Omnitracs staff on the entire development process, teaching them how to use powerful cloud-based toolchains to create new applications for a cloud-native future.

Although the initial project is complete, Omnitracs and Red Hat are continuing their work together through various community initiatives, including a recent codefest to improve the Truckers Against Trafficking mobile application. Red Hat and Omnitracs plan to continue these initiatives in the future to further enhance the transportation industry through cloud-native solutions.

Supporting Quotes:

Ashesh Badani, senior vice president, Cloud Platforms, Red Hat

“Transformation is more than just changing how code is built or how a new product is delivered; rather true transformation stems from evolving an organization’s development process, from top to bottom, by building on the principles of open technologies, culture and principles. We’re pleased to have helped Omnitracs embrace this change through the expertise of Red Hat Open Innovation Labs and the adoption of cloud-native, fully open technologies like Red Hat OpenShift and Red Hat Ansible Automation Platform.”

Kent Norton, chief technology officer, Omnitracs

“The key result from our successful collaboration with Red Hat is how we now approach technology as well as people and processes. We have re-engineered how we develop, test, secure and deploy software. This has enabled us to not only build and launch an innovative platform for fleet management, but it has also created substantial opportunities for future success with the tools and knowledge needed to address cloud-native demands.”

Additional Resources

Read more Red Hat customer success stories
Learn more about Red Hat OpenShift
Learn more about Red Hat Ansible Automation Platform
Learn more about Red Hat Open Innovation Labs
Learn more about cloud-native application development
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About Red Hat, Inc.

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver reliable and high-performing Linux, hybrid cloud, container, and Kubernetes technologies. Red Hat helps customers integrate new and existing IT applications, develop cloud-native applications, standardize on our industry-leading operating system, and automate, secure, and manage complex environments. Award-winning support, training, and consulting services make Red Hat a trusted adviser to the Fortune 500. As a strategic partner to cloud providers, system integrators, application vendors, customers, and open source communities, Red Hat can help organizations prepare for the digital future.

Forward-Looking Statements

Certain statements contained in this press release may constitute “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements provide current expectations of future events based on certain assumptions and include any statement that does not directly relate to any historical or current fact. Actual results may differ materially from those indicated by such forward-looking statements as a result of various important factors, including: risks related to the ability of the Company to compete effectively; the ability to deliver and stimulate demand for new products and technological innovations on a timely basis; delays or reductions in information technology spending; the integration of acquisitions and the ability to market successfully acquired technologies and products; risks related to errors or defects in our offerings and third-party products upon which our offerings depend; risks related to the security of our offerings and other data security vulnerabilities; fluctuations in exchange rates; changes in and a dependence on key personnel; the effects of industry consolidation; uncertainty and adverse results in litigation and related settlements; the inability to adequately protect Company intellectual property and the potential for infringement or breach of license claims of or relating to third party intellectual property; the ability to meet financial and operational challenges encountered in our international operations; and ineffective management of, and control over, the Company’s growth and international operations, as well as other factors. In addition to these factors, actual future performance, outcomes, and results may differ materially because of more general factors including (without limitation) general industry and market conditions and growth rates, economic and political conditions, governmental and public policy changes and the impact of natural disasters such as earthquakes and floods. The forward-looking statements included in this press release represent the Company’s views as of the date of this press release and these views could change. However, while the Company may elect to update these forward-looking statements at some point in the future, the Company specifically disclaims any obligation to do so. These forward-looking statements should not be relied upon as representing the Company’s views as of any date subsequent to the date of this press release.

Why Ansible Works Well for Network Automation

Two properties make Ansible particularly attractive in a network context:

• Agentless operation. Ansible communicates with network devices over SSH (or a vendor API where available). There is nothing to install on the managed device — a major advantage when you are working with switches and routers that do not expose a general-purpose OS.
• Low barrier to entry. YAML playbooks read almost like plain English. Network engineers who are comfortable with incremental learning — picking up IOS features as needed, for example — adapt quickly to Ansible’s model.

Ansible runs on a control node (a Linux host or WSL instance) and issues commands to one or many network devices simultaneously. Its behaviour is governed by plain-text configuration files, making it easy to version-control your automation alongside your other infrastructure code.

Key Concepts Before You Start

• Inventory — a list of the devices Ansible manages, organised into groups.
• Playbook — a YAML file describing one or more plays, each containing one or more tasks.
• Module — a reusable unit of work. Network modules such as ios_command, eos_command, and the vendor-agnostic cli_command handle interaction with specific platforms.
• Variables — stored in group_vars and host_vars directories and merged at run time, giving you fine-grained control over per-device or per-group settings.

Recommended Directory Structure

You can run Ansible with a single flat file, but that quickly becomes unmanageable. A structured layout separates concerns and scales cleanly as your device count grows. The following layout is used in the examples below:

.
├── ansible.cfg
├── group_vars
│   └── IOS_switches.yml
├── host_vars
│   └── test_sw.yml
├── inventory.yml
└── sh_arp.yml

ansible.cfg

This INI-format file overrides Ansible defaults. The most important settings for network automation are disabling fact gathering (which is designed for Linux hosts, not network devices) and pointing Ansible at your inventory file.

[defaults]
gathering = explicit
inventory = inventory.yml
retry_files_enabled = False

group_vars/IOS_switches.yml

Variables in group_vars apply to every host in the named group. Here we set the connection type to network_cli, declare the OS as ios, and supply credentials. In production, use Ansible Vault or SSH keys rather than plain-text passwords.

---
# IOS_switches variables
ansible_connection: network_cli
ansible_network_os: ios
ansible_become: yes
ansible_become_method: enable
ansible_become_password: "foobar"

ansible_user: tester
ansible_ssh_pass: foobar

host_vars/test_sw.yml

Host-level variables override group variables for a specific device. A management IP address and hostname are the minimum useful entries.

---
# test_sw variables
ipaddr: 192.168.1.108
hostname: test_sw

inventory.yml

The inventory file lists your devices and organises them into groups. A single device can belong to multiple groups, which is useful when you want to target switches by both vendor OS and network role.

---
all:
  children:
    IOS_switches:
      hosts:
        test_sw:
    IOS_routers:
      hosts:
        router1:
    access:
      hosts:
        test_sw:
    core:
      hosts:
        router1:

Writing Your First Playbook: Collecting the ARP Table

A good first automation task is read-only data collection — it is safe, immediately useful, and gives you a baseline to compare against. The playbook below, sh_arp.yml, issues show arp to every host in the IOS_switches group and prints the output.

---
- name: Gather ARP data
  hosts: IOS_switches
  tasks:
    - name: "Task 1: Get output of show arp on IOS"
      ios_command:
        commands: "show arp"
      register: cli_result

    - name: "Task 2: Display stdout_lines[0]"
      debug:
        msg: "{{ cli_result.stdout_lines[0] }}"

Key points about the playbook structure:

• ios_command sends a CLI command to an IOS device and returns the output as a string.
• register: cli_result saves the module’s return value into a variable for use in later tasks.
• The debug module prints the value of cli_result.stdout_lines[0] — a list of output lines from the first (and only) command issued.

Running the Playbook

$ ansible-playbook sh_arp.yml

Expected output:

PLAY [Gather ARP data] ***************************************************

TASK [Task 1: Get output of show arp on IOS] *****************************
ok: [test_sw]

TASK [Task 2: Display stdout_lines[0]] ***********************************
ok: [test_sw] => {
    "msg": [
        "Protocol  Address     Age (min)  Hardware Addr   Type  Interface",
        "Internet  192.168.1.108       -  bcc4.933e.49c0  ARPA  Vlan1",
        "Internet  192.168.1.126       5  f894.c220.2177  ARPA  Vlan1",
        "Internet  192.168.1.133       1  88c2.55fb.9ce7  ARPA  Vlan1",
        "Internet  192.168.1.138       0  a860.b60a.7a3a  ARPA  Vlan1"
    ]
}

PLAY RECAP ***************************************************************
test_sw                    : ok=2    changed=0    unreachable=0    failed=0

The PLAY RECAP line confirms two tasks completed successfully with no changes and no failures — exactly what you want from a read-only operation.

Scaling Up: Running Across Many Devices

The real value of Ansible is not running a single command on one switch — it is running a set of tasks across dozens or hundreds of devices with a single command. Once your inventory is populated, the same playbook targets every matching host automatically.

Practical use cases that are well suited to this pattern include:

• Compliance auditing. Verify that device configurations match a known-good template — for example, that QoS policies or MPLS route targets are consistent across the fleet.
• Inventory and documentation. Collect show version output from every device and store it to disk. You immediately have a searchable record of firmware versions, model numbers, and serial numbers.
• MAC and IP address tracking. Save show arp and show mac address-table dynamic output, then use grep to locate any device on the network by its IP or MAC address across hundreds of output files.
• Configuration generation and deployment. Combine Ansible with the Jinja2 templating language to dynamically render device configurations and push them across the network.

Beyond the Basics

The example above covers a small fraction of what Ansible can do for network teams:

• Ad hoc mode. Run a single module against an inventory group without writing a playbook — useful for quick checks during troubleshooting.
• Ansible Vault. Encrypt sensitive files such as credential variables so that secrets are never stored in plain text.
• Filters and plugins. Parse structured output, transform data, and extend Ansible’s capabilities beyond its built-in modules.
• Jinja2 templating. Generate device-specific configuration files from a single template, replacing manual copy-paste workflows.
• Roles. Package related tasks, variables, and templates into a reusable unit that can be shared across projects or published to Ansible Galaxy.

Nick Russo’s tutorial, Automating Networks with Ansible the Right Way, is frequently cited as a useful resource for engineers who want to move beyond basic playbooks into areas such as maintaining MPLS configurations with Ansible.

Getting Started: Recommended Approach

1. Install Ansible on a Linux control node (or WSL on Windows).
2. Build the directory structure shown above with a single test device in your inventory.
3. Start with the read-only ARP collection playbook and confirm it works.
4. Expand to additional show commands and save results to files using the copy or template modules.
5. Once comfortable, explore write operations — start with non-production devices and always test with --check mode where supported.

Ansible’s official Ansible for Network Automation documentation section is the authoritative starting point. It links to a getting-started guide, an advanced topics guide, and a full list of network modules organised by vendor and platform.

Summary

Ansible is a practical choice for network automation: it is agentless, uses SSH, and its YAML-based playbooks are no harder to learn than many networking concepts you already know. Starting with simple read-only tasks — collecting ARP tables, documenting firmware versions, auditing configurations — gives you immediate value with minimal risk. As your confidence grows, the same tool scales to configuration deployment, compliance enforcement, and full network lifecycle management.

What Is Build Automation Software?

Build automation software manages the process of compiling source code, running tests, packaging artifacts, and deploying applications—automatically and repeatably. By removing manual steps from the software delivery pipeline, these tools reduce human error, accelerate feedback loops, and make continuous integration and continuous delivery (CI/CD) practical at scale.

Organizations of all sizes—from small development teams to global enterprises—depend on build automation to ship software reliably. The market reflects this breadth, with tools ranging from self-hosted open-source platforms to fully managed cloud services.

Major Tools and Market Players

The competitive landscape includes a mix of open-source projects, commercial products, and cloud-native SaaS offerings. The key platforms cited in market analyses of this space include:

• Jenkins – The dominant open-source automation server. Jenkins has a massive plugin ecosystem (thousands of plugins) and a large community. It is self-hosted, highly flexible, but requires significant operational overhead to maintain at scale.
• TeamCity – JetBrains’ commercial CI server. Known for its polished UI, deep IDE integration, and strong support for .NET and JVM ecosystems. Offers a free tier for small teams.
• CircleCI – A cloud-native CI/CD platform that emphasizes speed through parallelism and caching. Popular with teams that prefer a managed service over running their own build infrastructure.
• Bamboo – Atlassian’s CI/CD server. Integrates tightly with Jira and Bitbucket, making it a natural fit for teams already in the Atlassian ecosystem.
• Ansible – Primarily a configuration management and application deployment tool rather than a build system in the traditional sense. It automates provisioning, orchestration, and deployment tasks using agentless, YAML-based playbooks.
• Microsoft Azure DevOps / Team Foundation Server (TFS) – Microsoft’s integrated DevOps suite, including Azure Pipelines for CI/CD. Supports both cloud-hosted and self-hosted agents across Windows, Linux, and macOS.
• Apache Maven – A build lifecycle and dependency management tool for Java projects. Often used in combination with a CI server like Jenkins rather than as a standalone automation platform.
• Azure Automation – Microsoft’s cloud service for process automation, configuration management, and update management within Azure environments.
• Codeship – A cloud-based CI/CD service focused on simplicity and fast setup, available in both a Basic (no configuration files) and Pro (Docker-based) tier.
• Travis CI – One of the first cloud-based CI services to gain wide adoption, particularly in open-source projects hosted on GitHub.
• Gradle – A flexible, high-performance build tool used extensively in Android and JVM projects. Supports incremental builds and build caching to reduce build times.
• Chef – A configuration management platform that uses Ruby-based recipes and cookbooks to automate infrastructure provisioning and application deployment.

Deployment Models: Cloud-Based vs. Web-Based (Self-Hosted)

Build automation tools generally fall into two deployment categories:

Cloud-Based (SaaS)

Platforms like CircleCI, Travis CI, and Codeship manage the underlying build infrastructure for you. Benefits include zero server maintenance, elastic scaling, and fast onboarding. The trade-off is reduced control over the build environment and potential data residency concerns for regulated industries.

Self-Hosted / On-Premises

Tools like Jenkins, TeamCity, and Bamboo can be deployed on your own infrastructure. This gives teams full control over hardware, networking, and data. The cost is operational: your team is responsible for installation, upgrades, plugin management, and capacity planning.

Many enterprises adopt a hybrid approach—using a cloud-based CI service for open-source or low-sensitivity projects while keeping a self-hosted platform for proprietary or compliance-sensitive workloads.

Market Segments by Organization Size

Adoption patterns differ significantly between large enterprises and small-to-medium enterprises (SMEs):

• Large Enterprises often standardize on a single platform (commonly Jenkins or Azure DevOps) managed by a dedicated platform engineering team. They value enterprise support contracts, audit logging, role-based access control, and integration with existing identity providers (LDAP, Active Directory).
• SMEs tend to favor managed SaaS offerings that minimize operational burden. CircleCI, Travis CI, and GitHub Actions (not listed in the original market report but now a major player) are common choices because teams can get a working pipeline in minutes without managing servers.

Key Drivers of Build Automation Adoption

Several trends accelerate demand for build automation tooling:

• DevOps and Agile adoption – Short sprint cycles require fast, reliable feedback on every commit. Manual builds are a bottleneck that automation eliminates.
• Microservices architectures – Decomposing applications into services multiplies the number of independent build pipelines, increasing the value of robust automation tooling.
• Container and Kubernetes adoption – Building and pushing container images is now a standard pipeline step, and all major tools have added Docker and Kubernetes integration.
• Security and compliance requirements – Automated pipelines provide an auditable, reproducible build process, which is increasingly required by compliance frameworks such as SOC 2 and ISO 27001.
• Remote and distributed teams – Cloud-based CI removes the dependency on a shared office network or VPN for running builds.

Regional Landscape

Build automation software is a genuinely global market. Adoption is strong across all major regions:

• Americas (US, Canada, Mexico, Brazil) – North America leads in enterprise adoption, driven by mature DevOps practices and a high concentration of software companies and cloud providers.
• Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia) – Rapid growth driven by expanding software industries in India and Southeast Asia, and strong enterprise IT investment in Japan and South Korea.
• Europe (Germany, France, UK, Italy, Russia, Spain) – Strong adoption, with additional emphasis on data sovereignty and on-premises deployments in regulated industries such as banking and healthcare.
• Middle East and Africa – An emerging market with growing cloud infrastructure investment, particularly in GCC countries.

Choosing a Build Automation Tool: What to Evaluate

No single tool is the right answer for every team. Consider these criteria when evaluating platforms:

1. Language and framework support – Does the tool have first-class support for your stack (JVM, .NET, Python, Go, Node.js, etc.)?
2. Ecosystem integrations – Does it integrate with your source control (GitHub, GitLab, Bitbucket), artifact repositories (Nexus, Artifactory), and deployment targets (Kubernetes, AWS, Azure)?
3. Operational overhead – Can your team afford to manage build infrastructure, or do you need a managed service?
4. Scalability – Can the tool handle your peak build load without queuing delays? Does it support distributed agents or parallel job execution?
5. Security and access control – Does it support SSO, RBAC, secret management, and audit logging?
6. Cost model – Open-source tools have zero licensing cost but real operational costs. SaaS tools have predictable per-seat or per-minute pricing. Model both total cost of ownership scenarios for your team size.
7. Community and support – A large, active community (as Jenkins has) means more plugins, answered Stack Overflow questions, and available expertise. Commercial tools offer paid support with SLAs.

Summary

The build automation software market is large, competitive, and continuing to grow as DevOps practices mature globally. Jenkins remains the most widely deployed self-hosted platform, while cloud-native tools like CircleCI and GitHub Actions are gaining share among teams that prioritize speed of setup and reduced operational burden. Purpose-built tools like Gradle and Maven fill critical niches in the JVM and Android ecosystems, while configuration management platforms like Ansible and Chef extend automation beyond the build step into provisioning and deployment.

The right choice depends on your team’s size, technology stack, compliance requirements, and willingness to invest in platform operations. Evaluating tools against the criteria above—rather than following market share alone—will lead to a better long-term fit.

Why Cloud Infrastructure Automation Matters

Manual infrastructure management does not scale. As cloud environments grow to span hundreds of services, multiple regions, and hybrid on-premises deployments, teams face mounting risks: configuration drift, inconsistent security posture, slow release cycles, and human error. Automation software addresses these problems by codifying infrastructure state, enforcing consistency, and enabling repeatable, auditable deployments.

Key business drivers pushing adoption include:

• Cost control: Automated scheduling, right-sizing, and teardown of non-production environments reduce idle spend.
• Compliance and auditability: Infrastructure-as-code (IaC) creates a version-controlled history of every change.
• Speed to market: Self-service provisioning cuts the time from code commit to running environment from days to minutes.
• Reliability: Idempotent tooling ensures environments are always in the desired state, regardless of how many times a playbook or plan is applied.

Major Vendors and Tools in the Ecosystem

The cloud infrastructure automation space is served by a mix of hyperscaler-native services, open-source projects, and commercial platforms. Below is a breakdown of the most widely referenced tools and vendors.

Hyperscaler-Native Services

• AWS: AWS CloudFormation provides declarative IaC for AWS resources. AWS Systems Manager, OpsWorks, and the AWS CDK extend automation to configuration management and higher-level abstractions.
• Google Cloud: Google Cloud Deployment Manager and the newer Config Connector allow teams to manage GCP resources as Kubernetes-style manifests. Google also has deep integrations with Terraform through its provider ecosystem.
• Microsoft Azure: Azure Resource Manager (ARM) templates and the newer Bicep language handle IaC on Azure. Azure Automation provides runbook-based orchestration for operational tasks.
• IBM: IBM Cloud Schematics is a managed Terraform service layered on top of IBM Cloud, targeting enterprise hybrid-cloud deployments.

Cross-Cloud and Open-Source Tools

• HashiCorp Terraform: The de facto standard for multi-cloud IaC. Terraform uses a declarative HCL syntax to describe desired resource state and a provider model that covers virtually every major cloud and SaaS platform. HashiCorp also offers Terraform Cloud and Terraform Enterprise for team collaboration, remote state, and policy enforcement via Sentinel.
• Ansible: An agentless configuration management and orchestration tool from Red Hat. Ansible playbooks are written in YAML and can target cloud APIs as well as operating system configuration, making it a popular choice for hybrid environments. Ansible Automation Platform adds enterprise workflow, RBAC, and a content hub.
• Puppet Enterprise: A model-driven configuration management platform that enforces desired state on servers. Puppet is widely used in large, regulated enterprises that require continuous compliance enforcement.
• Chef: A Ruby-based configuration management tool that treats infrastructure as code using “recipes” and “cookbooks.” Chef InSpec provides compliance-as-code testing.
• SaltStack (Salt): An event-driven automation platform with both agent-based and agentless modes. Salt is known for high performance at scale and its reactive automation capabilities via the Salt reactor system. VMware acquired SaltStack in 2020.
• CFEngine: One of the oldest configuration management tools, CFEngine is designed for very large-scale, high-frequency convergence. It is commonly found in telco and financial services environments.
• Juju (Canonical): Juju uses an operator model (“charms”) to model application relationships and lifecycle management, targeting both cloud and bare-metal deployments.

Managed and Specialized Platforms

• Nerdio: Focuses on automating Azure Virtual Desktop (AVD) deployments for managed service providers, adding cost optimization and multi-tenant management on top of Azure-native tooling.
• CloudShell Pro: Provides sandbox environments and network automation, commonly used in telco and networking labs.
• CenturyLink (now Lumen Technologies): Offers managed cloud and network automation services, targeting enterprise hybrid connectivity scenarios.

How to Compare Tools: Key Technical Dimensions

No single tool wins in every scenario. Evaluate automation software against these dimensions before committing to a stack:

Market Growth Drivers and Restraints

Drivers

• Accelerating cloud migration across enterprises and SMBs
• Growing adoption of multi-cloud and hybrid-cloud architectures that require cloud-agnostic tooling
• DevSecOps mandates that require security and compliance to be embedded in the provisioning pipeline
• The rise of platform engineering teams building internal developer platforms (IDPs) on top of automation primitives
• Kubernetes and container adoption driving demand for complementary infrastructure automation (Helm, Crossplane, ArgoCD)

Restraints and Challenges

• Skill gaps: IaC and configuration management require specialized knowledge that many operations teams are still developing.
• Tool sprawl: Organizations often end up with overlapping tools serving similar purposes, increasing operational complexity.
• State drift in large environments: Even with automation, manual changes made outside the toolchain (“snowflake” resources) create drift that is difficult to reconcile.
• Vendor lock-in concerns: Teams that invest heavily in hyperscaler-native IaC formats face migration costs if they shift cloud providers.
• Security of secrets and state: Terraform state files and Ansible vaults containing credentials must be protected carefully, adding operational overhead.

Competitive Dynamics: Five Forces at a Glance

• Threat of new entrants: Moderate. Open-source tooling lowers barriers, but enterprise sales cycles and ecosystem maturity favor established players.
• Supplier power: High for hyperscalers. AWS, Azure, and GCP can bundle native automation services, putting pressure on independent vendors.
• Buyer power: Increasing. The availability of mature open-source alternatives gives buyers strong negotiating leverage against commercial vendors.
• Threat of substitutes: Growing. Kubernetes operators, service meshes, and GitOps tools (Flux, ArgoCD) are absorbing some use cases previously handled by traditional CM tools.
• Competitive rivalry: Intense, particularly between Terraform and cloud-native IaC formats, and between Ansible and newer declarative alternatives.

Regional Considerations

Adoption patterns vary by geography. North America (the Americas region) leads in enterprise cloud automation maturity, driven by early cloud adoption and a large base of DevOps-skilled engineers. The Asia-Pacific (APAC) region shows rapid growth, particularly in financial services and e-commerce sectors in India, Australia, and Southeast Asia. Europe is significantly shaped by data sovereignty requirements (GDPR) and a preference for hybrid deployments that keep sensitive workloads on-premises. The Middle East and Africa (MEA) is an emerging market, with government-led digital transformation programs accelerating cloud and automation adoption.

Practical Recommendations for DevOps Teams

1. Start with Terraform for multi-cloud IaC. Its provider ecosystem and community are unmatched for provisioning across AWS, Azure, and GCP simultaneously.
2. Use Ansible for configuration management and day-2 operations. It complements Terraform well: Terraform provisions the infrastructure, Ansible configures what runs on it.
3. Adopt a GitOps workflow. Store all IaC in version control, use pull requests for changes, and run automation through CI/CD pipelines to create a full audit trail.
4. Enforce policy as code. Tools like HashiCorp Sentinel, Open Policy Agent (OPA), or Checkov can validate Terraform plans and Ansible playbooks before they execute.
5. Protect your state and secrets. Use remote state backends (S3 with DynamoDB locking, Terraform Cloud) and a secrets manager (HashiCorp Vault, AWS Secrets Manager) rather than storing credentials in plain text.
6. Evaluate hyperscaler-native tools for single-cloud workloads. If you are fully committed to one cloud, AWS CDK, Azure Bicep, or Google Config Connector may offer tighter integration than a third-party tool.

Summary

Cloud infrastructure automation is not a single product decision — it is an ecosystem of tools, practices, and organizational capabilities. The vendors profiled here — from AWS and Google to HashiCorp Terraform, Ansible, Puppet, Chef, SaltStack, and CFEngine — each occupy distinct niches shaped by their architecture, target scale, and integration model. Teams that invest in understanding these tradeoffs, codify their infrastructure, and enforce policy through automation pipelines will be best positioned to operate cloud environments reliably and at scale.

Overview of the Global DevOps Platform Market (2019)

By the end of 2019, the DevOps toolchain and platform market had matured into a competitive, multi-billion-dollar segment of the broader enterprise software industry. Organizations across verticals were accelerating adoption of DevOps practices to shorten release cycles, improve system reliability, and reduce operational friction between development and operations teams. Market research conducted during this period typically examined historic growth trends, near-term forecasts through 2024, competitive positioning, and vertical-market penetration.

Standard analytical frameworks applied to this market included Porter’s Five Forces (to assess competitive intensity and barriers to entry), SWOT analysis (strengths, weaknesses, opportunities, threats per vendor segment), and PESTEL analysis (political, economic, social, technological, environmental, and legal factors shaping adoption).

Leading DevOps Platform Vendors

The 2019 market landscape included a broad mix of open-source projects, independent software vendors, and large enterprise technology companies. Key players identified by market researchers at the time included:

• Ansible – Red Hat’s agentless automation and configuration management platform
• Chef – Infrastructure-as-code and compliance automation (now Progress Chef)
• Jenkins – The dominant open-source CI/CD automation server
• TeamCity – JetBrains’ commercial CI/CD server popular in .NET and JVM shops
• Atlassian – Provider of Jira, Confluence, Bitbucket, and Bamboo for planning through deployment
• SaltStack – Event-driven automation and remote execution framework
• Vagrant – HashiCorp tool for reproducible development environments
• Splunk – Observability, log management, and security intelligence
• ServiceNow – IT service management and DevOps workflow integration
• Puppet Labs – Declarative infrastructure automation and compliance
• CA Technologies – Enterprise DevOps tooling (acquired by Broadcom in 2018)
• IBM – DevOps capabilities spanning UrbanCode, Cloud Pak, and Watson AIOps
• Rackspace – Managed cloud and DevOps professional services
• Red Hat – OpenShift, Ansible, and open-source middleware
• CFEngine – Lightweight, high-performance configuration management
• Cisco – Network-layer DevOps and infrastructure automation
• Clarive – Release orchestration and DevOps value stream management
• CollabNet – Application lifecycle management and CI/CD platform
• DBmaestro – Database DevOps and deployment automation
• Dell Technologies – Infrastructure and cloud enablement for DevOps pipelines
• Docker – Container runtime and image registry central to modern CI/CD
• HP (HPE) – Enterprise DevOps testing and delivery tooling
• Inedo – ProGet, BuildMaster, and Otter for artifact management and orchestration
• Infosys – DevOps consulting, managed services, and toolchain integration
• Microsoft – Azure DevOps (formerly VSTS), GitHub, and related services
• VersionOne – Agile and DevOps planning (now Digital.ai)
• VMware – vSphere automation, Tanzu application platform, and CI/CD integration

This vendor mix illustrates how the market spanned pure-play DevOps specialists (Jenkins, Chef, Puppet), cloud-native platforms (Docker, Atlassian, Microsoft Azure DevOps), and large enterprise incumbents extending into DevOps territory (IBM, CA Technologies, HPE).

Product Segment Analysis

Market researchers in 2019 typically categorized DevOps platform offerings into three broad product types:

• Developer-driven DevOps – Toolchains initiated and owned primarily by engineering teams, emphasizing source control, CI pipelines, testing automation, and artifact management. Examples include GitHub Actions, Jenkins, and GitLab CI.
• Operations-driven DevOps – Platforms emphasizing infrastructure automation, configuration management, monitoring, and incident response. Examples include Ansible, Puppet, SaltStack, and Splunk.
• Platform 2.5 environments – Hybrid or integrated platforms bridging development and operations concerns under a single pane of glass, often including value stream management capabilities. Atlassian, ServiceNow, and CA Technologies occupied this space.

Application (Vertical) Segment Analysis

DevOps platform adoption was not uniform across industries in 2019. The major end-user verticals identified by researchers were:

• IT Industry – The largest adopter, encompassing software vendors, SaaS companies, and managed service providers where DevOps practices originated.
• Banking, Financial Services, and Insurance (BFSI) – Rapid adoption driven by digital transformation, regulatory compliance automation, and competitive pressure from fintech. Security and auditability requirements shaped toolchain choices.
• Telecom – Network function virtualization (NFV) and software-defined networking (SDN) initiatives drove DevOps adoption in large carriers.
• Retail – E-commerce scalability demands, seasonal traffic patterns, and omnichannel delivery pushed retailers toward continuous delivery practices.
• Other end-users – Healthcare, government, manufacturing, and energy sectors showing early-to-mid-stage adoption.

Regional Market Dynamics

Geographically, the DevOps platform market in 2019 was analyzed across the following regions:

• North America – The most mature and largest revenue-generating region, driven by high cloud adoption, a large concentration of technology companies, and strong DevOps cultural penetration.
• Europe – Significant adoption in the UK, Germany, and the Netherlands, with GDPR compliance automation adding an additional driver for pipeline tooling investment.
• Asia-Pacific – The fastest-growing region, with China, India, Japan, and South Korea leading adoption. India’s large software services sector made it a particularly notable market for DevOps tooling and training.
• Middle East and Africa – Emerging adoption, particularly in the Gulf Cooperation Council (GCC) countries undergoing digital transformation.
• Rest of the World – Latin America and other markets in earlier stages of DevOps maturity.

Key Market Drivers and Restraints

Understanding why the DevOps platform market was growing — and what was slowing it — is more durable than any specific market-size figure. Common drivers identified in 2019 research included:

• Accelerating cloud migration creating demand for infrastructure automation tools
• Competitive pressure to reduce software release cycles from months to days or hours
• Growing availability of open-source tooling lowering the entry cost for DevOps adoption
• Enterprise DevOps culture maturity and executive sponsorship improving top-down investment
• Container and Kubernetes adoption expanding the scope of DevOps platforms

Common restraints and challenges included:

• Organizational silos and cultural resistance to cross-functional collaboration
• Skills shortages in areas such as Kubernetes, infrastructure-as-code, and site reliability engineering
• Complexity of integrating diverse toolchains across heterogeneous environments
• Security and compliance concerns, particularly in regulated industries
• Fragmented vendor landscape creating evaluation and standardization challenges

Competitive Landscape and Strategic Takeaways

By late 2019, several strategic patterns were visible in the DevOps platform market:

• Consolidation: Large vendors were acquiring point-solution specialists. Red Hat’s acquisition of Ansible (2015), Microsoft’s acquisition of GitHub (2018), and Broadcom’s acquisition of CA Technologies (2018) exemplified this trend.
• Open-source as a moat: Vendors like HashiCorp, Elastic, and GitLab built large communities around open-source cores before monetizing through enterprise features or hosted SaaS.
• Platform vs. best-of-breed: Organizations debated whether to standardize on integrated platforms (Azure DevOps, GitLab) or compose toolchains from specialized tools. Neither approach dominated.
• Cloud-native pressure: Managed CI/CD services from AWS (CodePipeline), Google (Cloud Build), and Azure were beginning to compete with on-premises or self-hosted alternatives.

Summary

The DevOps platform market entering 2020 was characterized by strong growth, rapid consolidation, and expanding scope — from CI/CD pipelines into value stream management, security (DevSecOps), and AI-assisted operations (AIOps). The vendors listed above represent a snapshot of the competitive field at the close of 2019. Many of these companies have since merged, pivoted, or significantly evolved their product offerings.

For practitioners evaluating DevOps tooling, the more durable takeaway from this period is the importance of assessing tools against your specific workflow needs, team skills, and integration requirements — rather than relying solely on market share rankings.

Overview of the Global DevOps Platform Market

The DevOps Platform market encompasses tools, frameworks, and integrated suites that help organizations automate, monitor, and improve the software delivery lifecycle. By 2019, adoption had grown substantially across industries ranging from financial services to retail, driven by demand for faster release cycles, improved collaboration between development and operations teams, and cloud-native infrastructure.

Market research in this space typically segments the landscape by platform maturity level, industry vertical, and geography, providing organizations with benchmarks for evaluating their own DevOps readiness and investment priorities.

Leading DevOps Platform Vendors

The competitive landscape in 2019 included a broad mix of open-source-driven vendors, enterprise software incumbents, and cloud-native specialists. Key players identified in market research of the period include:

• Puppet Labs – Configuration management and infrastructure automation, widely used in enterprise environments.
• Chef (now Progress Chef) – Infrastructure-as-code automation platform with strong compliance and security features.
• Docker Inc. – Container runtime and registry platform that became foundational to modern CI/CD pipelines.
• Red Hat (Ansible) – Agentless automation and orchestration, tightly integrated with Red Hat’s OpenShift container platform.
• Atlassian – Collaboration and project tracking tools (Jira, Confluence, Bitbucket) widely embedded in DevOps workflows.
• SaltStack – Event-driven automation and remote execution engine, popular for large-scale infrastructure management.
• CA Technologies – Enterprise release automation and value stream management tooling.
• Rackspace – Managed cloud services with DevOps consulting and toolchain integration offerings.
• XebiaLabs (now Digital.ai) – Release orchestration and deployment automation at enterprise scale.
• VersionOne (now Digital.ai) – Agile and DevOps planning and metrics platform.
• Cisco – Network automation and infrastructure tooling contributing to DevOps pipeline security and observability.
• CollabNet – Application lifecycle management and DevOps toolchain integration.
• HP (Micro Focus) – Testing, ALM, and release management capabilities.
• IBM – End-to-end DevOps toolchains integrated with IBM Cloud and hybrid cloud environments.
• Microsoft – Azure DevOps (formerly VSTS) offering source control, pipelines, boards, and artifact management as a unified platform.
• Spirent Communications – Network and application performance testing tools used in DevOps validation workflows.
• VMware – Virtualization and cloud infrastructure platform with DevOps integrations via Tanzu and vRealize.
• DBmaestro – Database DevOps automation focused on controlled, auditable database deployments.

Market Segmentation

Research on the DevOps Platform market typically divides the landscape across three dimensions:

By Platform Maturity

• DevOps Ready – Organizations or platforms with foundational tooling in place but limited integration across the delivery pipeline.
• DevOps Enabled – Intermediate adoption with automated testing, CI pipelines, and collaborative practices established.
• DevOps Capable – Fully integrated, metrics-driven delivery pipelines with continuous deployment, observability, and feedback loops in production.

By Industry Vertical

• IT and Technology – Historically the earliest adopters, with high platform maturity.
• Banking, Financial Services, and Insurance (BFSI) – Driven by regulatory pressure and the need for reliable, frequent releases.
• Retail – E-commerce and omnichannel operations driving rapid release cycles.
• Telecom – Network function virtualization and OSS/BSS modernization fueling DevOps adoption.
• Education – Growing adoption of cloud-hosted learning platforms requiring agile delivery.
• Others – Healthcare, manufacturing, government, and media sectors at varying stages of adoption.

By Geography

North America led the global DevOps Platform market in 2019 by revenue, followed by Europe and the Asia-Pacific region. Growth rates in Asia-Pacific were among the highest, reflecting rapid cloud infrastructure investment and digital transformation programs in markets such as China, India, and Australia.

Key Market Drivers

Several forces accelerated DevOps Platform market growth during this period:

• Cloud adoption – Migration to public, private, and hybrid cloud environments created demand for automated provisioning and configuration management tools.
• Container and microservices proliferation – Docker and Kubernetes adoption fundamentally changed how teams build, ship, and run applications, requiring new platform capabilities around orchestration and observability.
• Agile at scale – Organizations scaling Agile frameworks (SAFe, LeSS) beyond individual teams invested in DevOps toolchains to support enterprise-wide delivery pipelines.
• Security and compliance requirements – Pressure to embed security earlier in the delivery cycle (DevSecOps) expanded the scope and value of DevOps platform investments.
• Talent and toolchain consolidation – Organizations sought to reduce tool sprawl by standardizing on integrated platforms rather than managing dozens of point solutions.

Challenges and Risks

Despite strong growth, the DevOps Platform market faced notable challenges:

• Cultural resistance – Organizational silos between development, operations, and security remained a significant barrier to platform adoption beyond pilot teams.
• Skills gaps – Demand for engineers with combined development, operations, and cloud expertise outpaced supply in most markets.
• Vendor fragmentation – The large number of competing tools and vendors made standardization difficult, particularly in regulated industries.
• Integration complexity – Connecting DevOps platforms with existing legacy systems, ERP platforms, and mainframe environments required significant custom engineering effort.

Evaluating DevOps Platform Vendors: What to Look For

When assessing vendors in this market, engineering and platform teams should consider the following criteria:

• Pipeline integration breadth – Does the platform support your existing SCM, CI, artifact, testing, and deployment tooling out of the box?
• Scalability – Can the platform support hundreds or thousands of pipelines without degrading performance or increasing operational overhead?
• Security controls – Does the platform provide role-based access, secrets management, audit logging, and policy enforcement?
• Observability – Are DORA metrics (deployment frequency, lead time, change failure rate, MTTR) surfaced natively, or do they require custom instrumentation?
• Open standards support – Does the vendor support open formats (OpenTelemetry, OCI images, Helm charts) to avoid proprietary lock-in?
• Enterprise support model – What SLAs, professional services, and training programs are available for large-scale rollouts?

Conclusion

The global DevOps Platform market in 2019 reflected a maturing but still rapidly evolving ecosystem, with established vendors competing alongside a new generation of cloud-native tooling providers. The market’s segmentation by platform maturity, industry vertical, and geography provides a useful framework for organizations benchmarking their own DevOps investment strategy. Engineering leaders evaluating platforms should prioritize integration breadth, security posture, and observability capabilities alongside headline feature comparisons to make durable toolchain decisions.

Source context: This article draws on market descriptions originally referenced from industrynewschronicle.com (2019). Specific market size and revenue figures from the original third-party report have not been reproduced, as they could not be independently verified.

What is Ansible? Ansible is an open-source IT automation engine, which can remove drudgery from your work life, and will also dramatically improve the scalability, consistency, and reliability of your IT environment. We’ll start to explore how to automate repetitive system administration tasks using Ansible, and if you want to learn more, you can go much deeper into how to use Ansible with Cloud Academy’s new Introduction to Ansible learning path.

What is Ansible and what can it automate?
You can use Ansible to automate three types of tasks:

Provisioning: Set up the various servers you need in your infrastructure.
Configuration management: Change the configuration of an application, OS, or device; start and stop services; install or update applications; implement a security policy; or perform a wide variety of other configuration tasks.
Application deployment: Make DevOps easier by automating the deployment of internally developed applications to your production systems.
Ansible can automate IT environments whether they are hosted on traditional bare metal servers, virtualization platforms, or in the cloud. It can also automate the configuration of a wide range of systems and devices such as databases, storage devices, networks, firewalls, and many others.

The best part is that you don’t even need to know the commands used to accomplish a particular task. You just need to specify what state you want the system to be in and Ansible will take care of it. For example, to ensure that your web servers are running the latest version of Apache, you could use a playbook similar to the following and Ansible would handle the details.

—
– hosts: webservers
vars:
http_port: 80
max_clients: 200
remote_user: root
tasks:
– name: ensure apache is at the latest version
yum: name=httpd state=latest
– name: write the apache config file
template: src=/srv/httpd.j2 dest=/etc/httpd.conf
notify:
– restart apache
– name: ensure apache is running (and enable it at boot)
service: name=httpd state=started enabled=yes
handlers:
– name: restart apache
service: name=httpd state=restarted
The line in the above playbook that actually installs or updates Apache is “yum: name=httpd state=latest”. You just specify the name of the software package (httpd) and the desired state (latest) and Ansible does the rest. The other tasks in the playbook update the Apache config file, restart Apache, and enablea Apache to run at boot time. Take a read at one of our previous blog posts on how to build Ansible playbooks.

Why Ansible?
There are many other IT automation tools available, including more mature ones like Puppet and Chef, so why would you choose Ansible? The main reason is simplicity. Michael DeHaan, the creator of Ansible, already had a lot of experience with other configuration management tools when he decided to develop a new one. He said that he wanted “a tool that you could not use for six months, come back to, and still remember.”

DeHaan accomplished this by using YAML, a simple configuration language. Puppet and Chef, on the other hand, use Ruby, which is more difficult to learn. This makes Ansible especially appealing to system administrators.

DeHaan also simplified Ansible deployment by making it agentless. That is, instead of having to install an agent on every system you want to manage (as you have to do with Puppet and Chef), Ansible just requires that systems have Python (on Linux servers) or PowerShell (on Windows servers) and SSH.

What is Ansible? A New Learning Path
Although Ansible is easier to learn than many of the other IT automation engines, you still need to learn a lot before you can start using it. To help you with this, Cloud Academy has released its Introduction to Ansible learning path.

This learning path includes three video courses:

What is Configuration Management?: A high-level overview of configuration management concepts and software options.
Getting Started With Ansible: Covers everything from Ansible components to writing and debugging playbooks in YAML.
Introduction to Managing Ansible Infrastructure: An overview of Ansible Tower (Red Hat’s proprietary management add-on to Ansible) and Ansible Galaxy (a place to find and share Ansible content).
Hands-on practice is critical when learning a new technology, so we have included two labs in the learning path:

Getting Started With Ansible: Create your first playbook to build a LAMP (Linux, Apache, MySQL, Python) stack on an EC2 instance.
Ansible: Deploying Web Applications: Learn about roles, templates, and handlers by deploying a Python application.
Finally, you can test your knowledge of Ansible by taking the quizzes.

Watch this short video, taken from the Getting Started with Ansible Course, where we take a look at the most common Ansible use cases.

Conclusion
Whether you need to make your life easier by automating your administration tasks or you’re interested in becoming a DevOps professional, Ansible is a good place to start. Learn how to streamline your IT operations with Introduction to Ansible.

What Is Cloud Infrastructure Automation Software?

Cloud infrastructure automation software enables teams to define, provision, configure, and manage cloud resources programmatically rather than through manual processes. Common use cases include infrastructure-as-code (IaC), configuration management, continuous delivery pipelines, and compliance enforcement. By reducing manual intervention, these tools increase deployment speed, reduce human error, and improve repeatability across environments.

Key Vendors in the Market

The market includes a broad mix of cloud hyperscalers, open-source projects, and independent software vendors. Below is an overview of the most prominent players:

• AWS (Amazon Web Services): Offers native automation tools including AWS CloudFormation for IaC, AWS Systems Manager for configuration and patching, and AWS CodePipeline for CI/CD orchestration.
• Google Cloud: Provides Deployment Manager for declarative resource provisioning and integrates with open-source tools such as Terraform and Ansible through its Cloud Build platform.
• Microsoft Azure: Delivers Azure Resource Manager (ARM) templates and Bicep for IaC, alongside Azure Automation for runbook-based operational tasks.
• HashiCorp Terraform: One of the most widely adopted open-source IaC tools. Uses a declarative HCL syntax and supports hundreds of cloud providers through a plugin-based provider model.
• Ansible (Red Hat): An agentless configuration management and automation tool that uses YAML-based playbooks. Commonly used for server provisioning, application deployment, and network automation.
• Puppet Enterprise: A model-driven configuration management platform with a strong presence in large enterprise environments. Enforces desired state continuously across nodes.
• Chef: Uses Ruby-based recipes and cookbooks to define infrastructure configuration. Popular in environments that require fine-grained control over configuration logic.
• SaltStack (VMware): An event-driven automation platform capable of managing thousands of nodes at scale. Supports both agent-based and agentless operation.
• IBM: Provides automation capabilities through IBM Cloud Schematics (built on Terraform) and IBM Turbonomic for resource optimization.
• CFEngine: One of the oldest configuration management tools. Known for high performance and low resource usage, making it relevant for large-scale and edge deployments.
• Juju (Canonical): An application modeling tool that focuses on deploying and managing complex multi-service applications across clouds.

Primary User Segments

Cloud infrastructure automation tools are consumed across several distinct technical roles, each with different priorities:

• Developers: Use automation tools to spin up consistent development and testing environments, reducing the “works on my machine” problem and enabling self-service infrastructure.
• Infrastructure Architects: Design reusable, modular IaC templates and governance guardrails that standardize how cloud resources are provisioned across the organization.
• DevOps and Platform Engineering Teams: Operate automation pipelines end-to-end, integrating IaC with CI/CD systems, secret management, policy enforcement, and observability tooling.

Key Growth Drivers

Several structural forces are pushing demand for infrastructure automation software:

• Multi-cloud adoption: Organizations running workloads across AWS, Azure, and Google Cloud need tools that abstract provider-specific APIs into a consistent workflow. Terraform and Ansible are particularly popular in multi-cloud contexts.
• Shift-left security: Security teams now expect infrastructure configuration to be validated before deployment. Tools that integrate policy-as-code (for example, HashiCorp Sentinel or Open Policy Agent) are in high demand.
• Container and Kubernetes growth: Container orchestration has expanded the scope of infrastructure automation to include cluster provisioning, Helm chart management, and GitOps workflows.
• Regulatory compliance: Industries subject to frameworks such as SOC 2, PCI-DSS, and HIPAA increasingly rely on automation to enforce and audit configuration standards consistently.
• Talent constraints: Automation reduces the operational burden on smaller teams, making it possible to manage larger, more complex infrastructure without proportional headcount growth.

Regional Landscape

Adoption patterns vary significantly by geography:

• North America (United States and Canada) leads in both vendor presence and enterprise adoption, driven by mature cloud markets and a high concentration of technology-first organizations.
• Europe (Germany, UK, France, Italy) is a significant adopter, with additional complexity arising from data sovereignty requirements under GDPR influencing tool selection and deployment architecture.
• Asia-Pacific (China, Japan, India, South Korea) represents one of the fastest-growing regions, driven by digital transformation initiatives across financial services, manufacturing, and government sectors.
• Middle East, Africa, and GCC are emerging markets where public cloud investment is accelerating, particularly around national digital infrastructure programs.

Competitive Dynamics and Tool Selection Considerations

Choosing the right automation tool depends on several factors specific to your organization:

• Cloud provider concentration: Teams deeply invested in a single cloud provider may find native tools (CloudFormation for AWS, ARM for Azure) sufficient. Multi-cloud teams typically prefer provider-agnostic tools like Terraform.
• Existing skill sets: Ansible’s YAML syntax has a lower barrier to entry than Chef’s Ruby DSL. Puppet and SaltStack require more investment to operate at scale but offer stronger drift detection capabilities.
• Agent vs. agentless architecture: Agentless tools (Ansible, Terraform) are easier to adopt without changing target system configurations. Agent-based tools (Puppet, Chef, SaltStack in agent mode) offer continuous enforcement and richer reporting.
• Open-source vs. commercial licensing: Many of these tools offer open-source community editions alongside paid enterprise tiers that add RBAC, audit logging, support SLAs, and governance features relevant to regulated environments.

Summary

The cloud infrastructure automation software market encompasses a wide range of tools serving developers, architects, and DevOps teams across every major industry and geography. Established players like AWS, Microsoft, and Google continue to extend native automation capabilities, while independent tools like Terraform, Ansible, and Puppet maintain strong adoption due to their flexibility and multi-cloud support. For engineering teams evaluating or expanding their automation toolchain, the key decision factors remain cloud strategy, team skill sets, compliance requirements, and the balance between open-source flexibility and enterprise support.

What Is Ansible Tower?

Ansible Tower is Red Hat’s web-based control plane for Ansible automation. It adds a graphical interface, role-based access control, a REST API, job scheduling, and centralised logging on top of core Ansible. Tower is also the primary component of the Ansible Automation Platform, which Red Hat announced and made generally available shortly before this 3.6 release.

Approval Nodes: Manual Gates Inside Automated Workflows

The headline feature of Tower 3.6 is the introduction of approval nodes in workflow job templates. Before this release, workflows executed their node sequences automatically from start to finish. Approval nodes let you insert a deliberate pause at any point in the workflow graph, requiring a human to explicitly approve or deny before execution continues.

Typical use cases include:

• Change advisory board (CAB) gates – halt a deployment until a change ticket has been reviewed.
• Environment promotion – require sign-off before pushing artefacts from staging to production.
• Destructive-operation confirmation – pause before a database migration or infrastructure teardown.

When the workflow reaches an approval node, Tower halts and sends a notification. An authorised user can then log in to the Tower UI or call the REST API to approve or deny the request. Denying terminates the workflow branch; approving allows the next node to execute.

GitHub and GitLab Webhook Integration

Tower 3.6 adds native webhook support for GitHub and GitLab events. This means you can configure a repository to POST an event payload directly to Tower, which then triggers a workflow or individual job template without any intermediary CI system.

Common scenarios enabled by this integration:

• Kick off a deployment pipeline on a push to the main branch.
• Trigger infrastructure provisioning from a pull-request merge event.
• Run compliance checks whenever a repository tag is created.

Tower exposes a unique webhook URL per job template or workflow, and validates incoming requests using a shared secret, reducing the risk of unauthorised triggers.

Customisable Notifications

Notifications in Tower 3.6 can now be customised with additional detail. Teams can include dynamic fields drawn from the job run itself — such as job status, inventory name, or extra variables — directly inside notification messages. This makes alerts sent to Slack, email, PagerDuty, or other configured endpoints more actionable without requiring recipients to log in to Tower for context.

Experimental: OpenShift-Based Job Execution

Tower 3.6 ships an experimental capability to delegate automation job execution to an OpenShift cluster. When configured, Tower can spin up a pod to run the automation task and tear it down once the job completes. The intent is to provide on-demand, elastic execution capacity rather than relying solely on Tower’s own execution nodes.

Because this feature is labelled experimental, it should not be relied upon for production workloads without thorough testing in your environment.

Breaking Changes and Migration Notes

Tower 3.6 removes several previously deprecated items. If you are upgrading from an earlier version, review the following before proceeding:

Tower API v1 Removed

The /api/v1/ endpoint has been removed entirely. All API clients and scripts must be updated to use /api/v2/. This affects any tooling, integration scripts, or third-party applications that still reference the v1 base path.

Credential Field Endpoints Removed

The credential field on job template API endpoints and the corresponding credential field on workflow job template nodes have been removed. These were deprecated in favour of the multi-credential model introduced in earlier releases. Update any automation that sets credentials through these fields to use the credentials list endpoint instead.

tower-cli Replaced by awx CLI

The tower-cli command-line tool has been superseded by the new awx CLI. The two tools differ in command structure and authentication handling, so existing shell scripts or CI pipeline steps that call tower-cli will need to be rewritten for awx. Check the official AWX project documentation for the updated command reference.

Summary of Changes

Teams running Ansible Tower in regulated environments or with manual change-control processes will find approval nodes the most impactful addition in this release. The webhook integration reduces the need for a separate CI server to bridge SCM events to Ansible automation, simplifying pipeline architecture for teams already invested in Tower.

The Problem: IT Silos and Manual Processes

Most IT departments share a common set of structural problems. Diverse application portfolios, fragmented toolchains, and independently acting business units create persistent IT silos. When departments operate without central coordination, shadow IT flourishes — teams adopt their own tools outside of IT governance, making the overall environment harder to manage, audit, and secure.

The resulting processes tend to be slow, error-prone, and inflexible. Security risks increase as untracked systems and configurations proliferate. Digital transformation initiatives stall because there is no consistent foundation on which to build automated, repeatable workflows.

Why Automation Alone Is Not Enough

Automation is widely recognized as a key enabler of operational efficiency, standardization, and DevOps adoption. However, a critical distinction must be made: automating individual silos in isolation does not solve the underlying problem. Automated silos are still silos.

Effective automation requires a cross-functional approach. Previously separate, standalone tools must be integrated into coherent workflows. That integration demands specialist knowledge spread across multiple teams and departments, which introduces coordination overhead, delays, and compatibility challenges.

A unified automation platform addresses these challenges by providing a common language and toolchain that all teams can use — without requiring every team to understand the implementation details of every other team’s systems.

Red Hat Ansible Automation

Red Hat Ansible addresses the cross-team automation challenge through its modular architecture. Ansible allows teams to encapsulate their domain-specific knowledge in playbooks and roles — reusable, human-readable units of automation written in YAML. These individual playbooks can then be composed into larger, multi-stage workflows without requiring each team to expose or share proprietary implementation details.

This model makes it possible for a networking team, a security team, and an application team to each maintain their own automation assets while still contributing to a shared, end-to-end process. Ansible acts as the integrating layer across previously disconnected domains.

Example: Automating SAP HANA Deployments

A concrete use case for Ansible automation is the deployment and configuration of SAP HANA, an in-memory database with strict, well-documented setup requirements. SAP defines these requirements through SAP Notes — detailed technical documents that cover platform-specific installation and configuration steps. Manually following SAP Notes is time-consuming and introduces the risk of missed or misinterpreted steps, which can affect both system stability and SAP’s support eligibility for production environments.

The standard HANA installation process involves the following stages:

1. Hardware provisioning or virtual machine setup
2. Installation and configuration of Red Hat Enterprise Linux (RHEL)
3. Installation and configuration of SAP HANA
4. System validation and customization
5. Integration into the regular maintenance and patching cycle

By translating the relevant SAP Notes into Ansible Playbooks and Roles, teams can automate all of these stages — from OS configuration through HANA installation, validation, and customization. The reported outcome of this approach is a reduction in setup time from days to minutes. Ansible roles also support more complex topologies, including scale-up and scale-out environments, HANA System Replication, and high-availability configurations using Pacemaker.

Red Hat Ansible Tower

Red Hat Ansible Tower (now available as Ansible Automation Platform in more recent releases) serves as the enterprise control plane for Ansible automation. It provides the management and governance capabilities needed to operationalize Ansible at scale across an organization.

Key features of Ansible Tower include:

• RESTful API and self-service portal: Enables integration with existing ITSM tools, CI/CD pipelines, and custom dashboards, making automation accessible to non-CLI users across the business.
• Centralized inventory management: Maintains a single source of truth for all managed hosts, supporting dynamic inventory sources for cloud and on-premises environments.
• Role-based access control (RBAC): Restricts what each team or user can view, run, or modify, enforcing least-privilege principles across automation workflows.
• Credential management: Stores and injects secrets securely without exposing them in playbooks or logs.
• End-to-end audit trail: Logs every job run with full output, enabling traceability and compliance reporting.
• Workflow orchestration: Chains multiple playbooks into complex, multi-stage workflows with conditional branching and parallel execution.

Configuration Management and Patch Lifecycle

Beyond initial deployment, Ansible — used in combination with Red Hat Satellite — supports ongoing configuration management, patch management, and release management throughout the operational lifecycle. This means that the same automation assets used for initial provisioning can be reused to enforce configuration drift remediation and apply updates consistently across environments.

Staging workflows are also supported. Identical environments can be instantiated in a cloud provider for quality assurance, pre-production testing of patches, or upgrade and migration validation, before changes are applied to production systems.

Development Workflow and Continuous Testing

Ansible playbook development has a relatively low barrier to entry due to YAML’s readability. Changes to playbooks should be continuously tested using a dedicated developer platform or pipeline. A recommended practice is to trigger test runs across multiple deployment scenarios — such as scale-up, scale-out, system replication, and Pacemaker configurations — whenever a playbook change is committed. This ensures that modifications do not introduce regressions across any of the supported topologies.

Key Takeaways

• IT silos and manual processes are a primary obstacle to digital transformation — automation must span organizational boundaries, not just individual tools.
• Red Hat Ansible uses playbooks and roles to encapsulate team-specific automation while enabling cross-functional workflow composition.
• SAP HANA deployment is a practical example where Ansible can reduce setup time significantly by codifying SAP Notes into reusable automation assets.
• Ansible Tower provides the enterprise governance layer — RBAC, auditing, APIs, and workflow orchestration — needed to scale Ansible across an organization.
• Combined with Red Hat Satellite, Ansible covers the full lifecycle: provisioning, configuration management, patching, and release management.

What Is the Global DevOps Platform Market?

The Global DevOps Platform Market encompasses the tools, services, and integrated platforms that organisations use to implement DevOps practices — spanning continuous integration, continuous delivery, infrastructure automation, monitoring, and collaboration. Market research reports on this space typically analyse growth drivers, competitive dynamics, and regional demand to help vendors, investors, and practitioners understand where the industry is heading.

This article summarises the key findings and structure of a market intelligence report covering the Global DevOps Platform Market from 2019 through a projected horizon of 2026, as originally published by industrynewsinfo.com.

Key Market Players

The report identifies a broad set of vendors competing across the DevOps toolchain. Major players cited include:

• Puppet Labs — configuration management and infrastructure automation
• Chef — policy-based infrastructure automation
• Docker Inc. — containerisation platform
• Red Hat (Ansible) — agentless automation and OpenShift container platform
• Atlassian — developer collaboration tools including Jira and Bitbucket
• SaltStack — event-driven automation
• CA Technologies — enterprise DevOps and release automation
• Rackspace — managed cloud services with DevOps support
• XebiaLabs — release orchestration and deployment automation
• VersionOne — Agile and DevOps planning
• Cisco, CollabNet, HP, IBM, Microsoft, Spirent Communications, VMware, DBmaestro

Each vendor profile in the full report typically covers product portfolio, financial statistics, competitive positioning, and market share estimates.

Market Segmentation

By Product Maturity / Capability Level

The report categorises DevOps platforms by organisational readiness and tooling maturity:

• DevOps Ready — platforms or toolsets that provide foundational capabilities for teams beginning a DevOps transformation
• DevOps Enabled — integrated solutions that actively support established DevOps workflows including CI/CD pipelines and monitoring
• DevOps Capable — fully mature platforms designed for large-scale, enterprise-grade DevOps operations with advanced automation and analytics

By Application / Industry Vertical

DevOps platform adoption is analysed across the following verticals:

• IT — the largest adopter segment, spanning software development, managed services, and cloud operations
• BFSI (Banking, Financial Services, and Insurance) — driven by regulatory compliance, release velocity, and security requirements
• Retail — e-commerce platforms and supply chain systems benefiting from rapid deployment cycles
• Telecom — network function virtualisation and service delivery automation
• Education — digital learning platforms and institutional IT modernisation
• Others — healthcare, manufacturing, government, and more

Regional Market Breakdown

The report analyses DevOps platform demand and revenue across five major geographic regions:

• North America (USA, Canada, Mexico)
• Asia-Pacific (China, Japan, India, South Korea, Australia, Indonesia, Taiwan, Thailand)
• Europe (Germany, UK, France, Italy, Russia, Spain)
• Middle East & Africa (Turkey, Saudi Arabia, Iran, Egypt, Nigeria, UAE, Israel, South Africa)
• South America (Brazil, Argentina, Colombia, Chile, Venezuela, Peru)

North America and Europe have historically led DevOps platform adoption due to mature cloud infrastructure and established software engineering cultures. Asia-Pacific is identified as a high-growth region, driven by rapid digital transformation across India, China, and Southeast Asia.

Analytical Frameworks Used

Market reports of this type typically apply several standard analytical frameworks to evaluate competitive dynamics and strategic positioning:

SWOT Analysis

Strengths, Weaknesses, Opportunities, and Threats are assessed for both the overall market and individual key players. For DevOps platforms, common strengths include strong developer ecosystems and cloud-native integrations; threats include vendor consolidation and open-source commoditisation of tooling.

Porter’s Five Forces

This framework evaluates: competitive rivalry among existing players, threat of new entrants (high given low barriers for open-source tools), threat of substitutes, bargaining power of buyers, and bargaining power of suppliers.

Value Chain Analysis

The value chain spans from infrastructure and tooling providers through to system integrators, managed service providers, and end-user organisations. Understanding where margin and influence concentrate helps stakeholders identify partnership and investment opportunities.

Key Data Points Covered in the Report

The full market intelligence report addresses the following analytical areas:

• Production Statistics — volume and unit-level data by product type, region, and application segment, including pricing portfolios of major vendors
• Sales and Revenue — regional revenue figures with price sensitivity analysis to identify which markets are most price-competitive
• Supply and Demand Dynamics — analysis of the gap between platform supply and enterprise demand, including import/export considerations for licensed software and cloud services
• Competitive Profiles — vendor-level breakdowns covering product range, technical capabilities, cost structure, and revenue contribution
• Trade and Supply Statistics — contact information for key producers, suppliers, and major enterprise consumers
• CAGR Projections — compound annual growth rate estimates derived from historical data (pre-2019) combined with identified current trends, projecting market conditions through 2026

Why This Market Matters to DevOps Practitioners

Understanding the competitive landscape of the DevOps platform market is practically useful for engineering leaders and architects in several ways:

• Vendor selection — knowing which vendors are growing, consolidating, or being acquired helps teams make durable toolchain decisions
• Budget justification — market growth data supports business cases for DevOps investment to non-technical stakeholders
• Career and skills planning — dominant platforms in the market signal where practitioner demand will be highest
• Partnership strategy — organisations building DevOps practices on top of vendor ecosystems benefit from understanding each vendor’s financial health and strategic direction

The DevOps tooling market has continued to evolve significantly since this report’s 2019 publication date, with notable developments including Red Hat’s deeper integration of Ansible into OpenShift, Microsoft’s expansion of Azure DevOps and GitHub Actions, and the broader shift toward platform engineering as a discipline.