SCM practices include vision control in establishing a baseline. If something goes wrong, the SCM can determine what was changed and who changed it.

The goals of software configuration management are generally to implement configuration, identification, configuration idioms, and baselines, configuration control, control change processes.

This is usually achieved by establishing a change control board whose primary function is to accept all change requests sent against any baseline or rejected. Configuration position to record all the necessary information on accounting, reporting, and development process conditions.

Configuration Management Tools Features:

• Infrastructure automation
• Automated provisioning
• Application deployment
• Task management
• Visualization and reporting
• Orchestration
• Node management
• Role-based access control

Configuration Management Benefits:

Configuration Management aims to keep detailed records of information about the computer system and the need to update them.

The main benefits are:

• Lower risk of outages and security breaches
• Reduce costs by avoiding duplication of technology assets.
• Process control rapid problem resolution through implementing formal policies and procedures
• Efficient change management by understanding infrastructure
• Quick resumption of service

Here is the list of Top 5 Configuration Management Tools:

1. Ansible

Ansible is also the best configuration management, deployment, orchestration open-source tool, and automation engine. In fact, it is included in popular Linux distros like Fedora. This software provisioning and help IT infrastructure automation ranging from configuration management application to deployment, so get big productivity gains.

Ansible is a helpful tool that DevOps engineers can use to achieve infrastructure, application, network, and container environment automation. Engineers use this tool extensively for the automation and configuration of servers.

Features:

• Ansible Tower, a platform within Ansible, is a visualization dashboard for the entire IT environment.
• Through role-based access control (RBAC), Ansible can create scope users, and operate permissions for the environment.
• Ansible supports both on-premises and multi-cloud infrastructure configurations.

2. Puppet

Puppet is an open-source software configuration management tool. It is used to deploy, configure and manage servers. It uses a master-slave architecture.

Through the puppet, it is possible to overcome through continuous compliance with operational and safety risks in the IT environment. This includes Windows infrastructure automation, patch management, and managed application operations.

Thousands of companies, including Google, Cisco, and Splunk, use Puppet for configuration management.

Features:

• Highly extensible, supporting several developer tools and APIs.
• Puppet has Bolt, a powerful task orchestrator for automating manual tasks.
• Puppet integrates well with Kubernetes and Docker.
• Automated Provisioning

3. Chef

Chef is basically an automation platform that provides a way to configure and manage the infrastructure. Infrastructure as code implies execution by coding rather than performing manual execution. Chef works on Ruby and DSL to write the configuration.

Chef as a tool in DevOps lets you perform configuration management tasks on servers and other computing resources. Using Chef to automate processes is simple. With a few clicks, multiple nodes can be up and running.

Top companies like Facebook, Slack, and Spotify have employed Chef in their ecosystems.

Features:

• Chef is an agent-based automation platform.
• Chef handles infrastructure as code.
• Supports all operating systems and integrates with any cloud technology.
• Chef provides analytics for monitoring changes to the server.

4. Saltstack

SaltStack or simply Salt is a scalable configuration management and orchestration tool. DevOps teams use salt to manage IT environments such as data centers through event-driven orchestration and remote execution of configurations.

SaltStack is based on the Python programming language, SaltStack provides push and SSH methods to communicate with clients. Saltstak allows customers and group configuration templates together to be simple and easy to control the environment.

Salt configuration depends on the management framework states and configuration files so that it can be shown that is how the provision of IT infrastructure and deployment.

Features:

• Salt Cloud Platform for Provisioning Systems on the Cloud.
• Supports both agent-based and agentless control of nodes.
• Supports both *NIX and Windows operating systems.

5. CFEngine

CFEngine is a highly scalable platform for automated management of your IT infrastructure. Teams with CFEngine physical and virtual infrastructure provisioning, patch management, access control, user management, and system security, all can do the same location.

With CFEngine, autonomous agents are working continuously to continuously monitor, repair, update and restore IT infrastructure. Continuous system checks and automated treatment in CFEngine guarantee dependability and consistency across an infrastructure.

Features:

• Highly flexible due to the ‘write once use repeatedly’ configuration scheme.
• CFEngine is the Enterprise Mission Portal, a central dashboard platform for visibility and real-time monitoring of IT systems.
• Use lightweight automation agents within the WebScale platform to configure and manage multiple nodes.

The best way to find the best tools for your needs is to try them out. Who works for others it may not work for you, try to see how it works, how it can help keep your organization consistent and secure configuration.

It is quite important to do research and choose the best equipment which will be good for your organization.

I hope this article will help you with that.

Dell Technologies today announced the general availability of Omnia, its open source platform for managing high-performance computing (HPC) and artificial intelligence (AI) workloads.

Omnia is an open source set of Ansible Playbooks developed by Dell’s HPC and AI innovation team in partnership with Intel and the broader HPC community. If this sounds familiar, Dell quietly released Omnia on Github earlier this year.

The platform automates the process of downloading and installing open source software for things like cluster management, application execution, accelerator drivers, frameworks, applications and platforms, and it manages systems running Slurm or Kubernetes, explained Caitlin Gordon, VP of product management at Dell Technologies.

“It’s all about simplifying and easing the development and the management of high-performance clusters for not just HPC but AI,” she said.

And because these automations are built on Ansible Playbooks, “you can compose and recompose the stack, based on what you need,” Gordon said. “We’re really taking an infrastructure as code approach here.”

This, she added, allows users to compose HPC deployments around a wide variety of workloads and hardware from multiple vendors. “Of course, because its open source, it can be shaped to whatever your needs are,” Gordon said. “We’ll continue to integrate the latest open source tools, but we also, even more importantly, have the collective power of the HPC community already working behind this.”

Arizona State University, one of Dell Technology’s HPC and AI centers for excellence, is among the first to deploy Omnia and begin contributing to its development, according to Gordon.

Dell HPC Nabs VMware Support, PowerEdge Gets Nvidia Upgrade
Dell Technologies also extended support for VMware to its HPC on-Demand program, which launched last year.

“Being able to consume things as a service be able to access resources as you need them, be able to move faster and simply pay for what you’re using. That’s really what HPC on demand is all about,” Gordon said. “It’s really about being able to support our customers who may not have the resources, or may not want to invest in their own infrastructure and people, because their HPC workloads maybe are inconsistent, and/or maybe they need to complement what they already have in their environment with a secondary environment to burst to.”

With support for VMware Cloud Foundation, VMware Cloud Director, and VMware vRealize Operations, customers can now extend these capabilities beyond single-tenant environments to include multi-tenant use cases.

Meanwhile, Dell Tech is adding Nvidia A10 and A30 GPUs to its PowerEdge server portfolio. “These are really ideal for things like VDI inferencing and interactive rendering,” Gordon said.

As I explained in my prior blog, Containers Practices Gap Assessment, containerizing software is valuable for DevOps.

Yet, as I work with clients on their DevOps journeys, I continue to encounter organizations that haven’t grasped the importance of using containers relative to bare metal, virtual machines (VMs) and serverless computing solutions. This article is intended to help organizations understand the difference and the advantages that containers offer for DevOps.

The workhorse of IT is the computer server on which software application stacks run. The server consists of an operating system, computing, memory, storage and network access capabilities; often referred to as a computer machine or just “machine.”

A bare metal machine is a dedicated server using dedicated hardware. Data centers have many bare metal servers that are racked and stacked in clusters, all interconnected through switches and routers. Human and automated users of a data center access the machines through access servers, high security firewalls and load balancers.

The virtual machine introduced an operating system simulation layer between the bare metal server’s operating system and the application, so one bare metal server can support more than one application stack with a variety of operating systems.

This provides a layer of abstraction that allows the servers in a data center to be software-configured and repurposed on demand. In this way, a virtual machine can be scaled horizontally, by configuring multiple parallel machines, or vertically, by configuring machines to allocate more power to a virtual machine.

One of the problems with virtual machines is that the virtual operating system simulation layer is quite “thick,” and the time required to load and configure each VM typically takes some time. In a DevOps environment, changes occur frequently. This load and configuration time is important, because failures that occur during the load and configuration can further delay the instantiation of the VM and the application.

The idempotent characteristic of modern configuration management tools such as Puppet, Chef, Ansible and SaltStack do help to reduce the chance for errors, but when configuration errors are detected, delays to reload and reconfigure the stacks take time. These delays constitute significant delays for each DevOps stage, and the accumulated time for the series of stages needed for a DevOps pipeline can be a significant bottleneck.

VMs are used in production IT environments because of the flexibility to support different configurations. However, the time to reload and configure VMs can be a bottleneck during release reconfigurations, and can delay mean-time-to-repair when failures occur.

Containers, such as those supported by Docker, have a very lightweight operating system simulation layer (the Docker ecosystem) that is tailored specifically to each application stack. Container systems such as Docker guarantee isolation between application stacks run over the same Docker layer.

Compared to VMs, the smaller “footprint” of containerized application stacks allows more application stacks to run on one bare metal machine or virtual machines, and they can be instantiated in seconds rather than minutes. These desirable characteristics make it easy to justify a migration from running an application stack on bare metal machines or VMs. Instead of time-consuming loading and configuring an application stack and OS layer for each machine, instantiation of a complete container image is loaded, and a small number of configuration variables are instantiated in seconds. This capability to quickly create and release containerized applications allows for the infrastructure to be immutable.

In thirty minutes, someone can go from having nothing on their machine to a full dev environment and the ability to commit and deploy. Containers are the fastest means to launch short-lived, purpose-built testing sandboxes as part of a continuous integration process.

Containers are the result of a build pipeline (artifacts-to-workload). Test tools and test artifacts should be kept in separate test containers. Containers include minimal runtime requirements of the application. An application and its dependencies bundled into a container is independent of the host version of the Linux kernel, platform distribution or deployment model.

Benefits of Containers
Benefits of containers include the following:

The small size of a container allows for quick deployment.
Containers are portable across machines.
Containers are easy to track and it is easy to compare versions.
More containers than virtual machines can run simultaneously on host machines.
The challenge with containers is to get your application stack working with Docker. Making containers for a specific application stack is a project easily justified by the ROI of reduced infrastructure costs and the benefits provided by immutable infrastructures such as fast mean-time-to-restore-service (MTTRS) during failure events.

Containerized infrastructure environments sit between the host server (whether it’s virtual or bare metal) and the application. This offers advantages compared to legacy or traditional infrastructure. Containerized applications start faster because you do not have to boot an entire server.

Containerized application deployments also are “denser,” because containers don’t require you to virtualize a complete operating system. Containerized applications are more scalable because of the ease of spinning up new containers.

Recommended Container Engineering Practices
Here are some recommended engineering practices for containerized infrastructure:

Containers are decoupled from infrastructure.
Container deployments declare resources needed (storage, compute, memory, network).
Place specialized hardware containers in their own cluster.
Use smaller clusters to reduce complexity between teams.
Serverless computing is a cloud computing execution model in which the cloud provider runs the server and dynamically manages the allocation of machine resources. Pricing is based on the actual resources consumed by an application, rather than on pre-purchased units of capacity. Serverless computing can simplify the process of deploying code into production. Scaling, capacity planning and maintenance operations may be hidden from the developer or operator. Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices. Alternatively, applications can be written to be purely serverless and use no provisioned servers at all.

What This Means
This blog explained how containers compare to bare metal, virtual machines and serverless solutions. Those who are serious about DevOps would do well to learn about the advantages that containers offer as part of a DevOps solution. To learn more about containers, refer to my book Engineering DevOps.

Successful software companies manage to deploy releases promptly because they’re great at DevOps. Without DevOps, there will still be a glaring schism between the development and software teams of businesses, making it hard to collaborate and align goals. But with DevOps, both groups work together in all stages of software development to allow for faster fixes, resulting in a better product for the end user.

DevOps practitioners are in great demand, as users expect more from the companies that develop the digital products they use. If you want to become a DevOps engineer, check out the Dynamic 2021 DevOps Certification Training Bundle.

This five-course training package focuses on Git, CompTIA Cloud, Docker, and Ansible, all of which are used in building infrastructure. But first, you’ll start with an in-depth primer on DevOps fundamentals so you can have a full grasp of how it works. Then, you’ll learn how to create repositories in Git, discover Docker technologies such as Docker Hub, Docker Compose and Docker Swarm, and master the open-source tool Ansible to elevate productivity and improve business outcomes. You’ll also get to hone your expertise in preventive maintenance, installation, security, troubleshooting, and networking.

The courses are all self-paced, so you can learn when it’s best for your schedule. Also, the courses are taught by industry insiders with years of experience.

Global Continuous Deployment Software Market Research Report 2021

Global Continuous Deployment Software Market present insights on the current and future industry trends, enabling the readers to identify the products and services, hence driving the revenue growth and profitability. The research report provides a detailed analysis of all the major factors impacting the market on a global and regional scale, including drivers, constraints, threats, challenges, opportunities, and industry-specific trends. Further, the report cites global certainties and endorsements along with downstream and upstream analysis of leading players. The research report comes up with the base year 2021 and the forecast between 2021 and 2027.

Drivers and Risks

The report pays special attention to factors which contribute to the Continuous Deployment Software Market growth also known as market drivers. Any changes in these market dynamics directly affect the market growth hence the report provides a future insight into important factors that should be monitored and which could be leveraged by companies, vendors, distributors and all stakeholders alike to their advantage. The report also provides an insight into the challenges faced by the market and the strategies used by existing players to overcome or avoid these risks.

Segment by Type

Cloud Based
Web Based
Segment by Application

Large Enterprises
SMEs
Regional overview

As already mentioned, the report covers different regions such as North America, Latin America, Asia Pacific, Europe, and the Middle East & Africa. The different strategies employed by different players in different regions has been studied extensively in order to gain an understanding of the global market. It is important to understand where the Continuous Deployment Software market has been, currently is and where it is projected to go so that an accurate picture of the future may be painted. Studying the Continuous Deployment Software market allows an outlook, the latest trends, and prospects in the period of 2021 to be embraced and understood.

Latest industry news

The key players in the global Continuous Deployment Software market have been busy acquiring startups and participating in collaborations, mergers, and innovations. This report highlights how the most prominent vendors in the market have been contributing to the market. In addition to highlighting the most prominent vendors, the report also takes a look at promising new players in the global Continuous Deployment Software market.

Key questions answered in the report:

What is the growth potential of the Continuous Deployment Software market?
Which product segment will grab a lion’s share?
Which regional market will emerge as a frontrunner in the coming years?
Which application segment will grow at a robust rate?
What are the growth opportunities that may emerge in the Continuous Deployment Software industry in the years to come?
What are the key challenges that the global Continuous Deployment Software market may face in the future?
Which are the leading companies in the global Continuous Deployment Software market?
Which are the key trends positively impacting the market growth?
Which are the growth strategies considered by the players to sustain hold in the global Continuous Deployment Software market?

The Continuous Deployment Software market research report completely covers the vital statistics of the capacity, production, value, cost/profit, supply/demand import/export, further divided by company and country, and by application/type for best possible updated data representation in the figures, tables, pie chart, and graphs. These data representations provide predictive data regarding the future estimations for convincing market growth. The detailed and comprehensive knowledge about our publishers makes us out of the box in case of market analysis.

Reports and Markets is not just another company in this domain but is a part of a veteran group called Algoro Research Consultants Pvt. Ltd. It offers premium progressive statistical surveying, market research reports, analysis & forecast data for a wide range of sectors both for the government and private agencies all across the world. The database of the company is updated on a daily basis. Our database contains a variety of industry verticals that include: Food Beverage, Automotive, Chemicals and Energy, IT & Telecom, Consumer, Healthcare, and many more. Each and every report goes through the appropriate research methodology, Checked from the professionals and analysts.

First authored around 2009, the term DevOps alludes to a way to deal with IT that stresses coordinated effort between the turn of events and tasks gatherings. It emerged out of the dexterous programming improvement development and applies a portion of similar standards to the Application Lifecycle Management (ALM) measure. DevOps is hard to characterize in light of the fact that it’s all the more a development or a way of thinking than an inflexible arrangement of rules or practices. Open source DevOps instruments are utilized as an approach to smooth out the cycle of advancement and sending.
TOP OPEN SOURCE DEVOPS TOOLS
A full DevOps send pipeline should comprise of something other than assemble and engineer apparatuses. It additionally should oblige establishing and overseeing the creation climate through code. However for reasons unknown, really running creation (what used to be called Ops) through mechanization appears to get quick work.

The way of thinking is straightforward: Optimize for quick stream from advancement to creation, coordinate input from creation into advancement, and consistently trial to improve that cycle. These standards show themselves in programming groups as ceaseless conveyance (and ideally sending), profoundly coordinated telemetry, and learning and experimentation drive the way of life. All things considered, certain instruments make accomplishing stream, input, and learning simpler. You don’t need to dish out tons of money to outsider merchants however. You can assemble a DevOps esteem stream with set up open source apparatuses.
1. Ansible – Ansible is the simplest way to automate apps and IT infrastructure.

2. Docker – Docker helps developers bring their ideas to life by conquering the complexity of app development.

3. Git – Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

4. Jenkins– an open source automation server which enables developers around the world to reliably build, test, and deploy their software.

5. Puppet Enterprise – uppet is the industry standard for IT automation. Manage and automate more infrastructure and complex workflows in a simple, yet powerful way.

6. Selenium – Primarily it is for automating web applications for testing purposes

7.Splunk – that produces software for searching, monitoring, and analyzing machine-generated big data via a Web-style interface.

8.Nagios – Nagios provides enterprise-class Open Source IT monitoring, network monitoring, server and applications monitoring.

9.codescan.io – CodeScan is the leading static code analysis solution used exclusively for Salesforce DevOps team

Change is an essential part of IT, but it’s often disruptive. An adjustment to one asset can throw other resources out of alignment — sometimes in ways no one anticipated. Those misconfigurations can result in poor performance, application inconsistencies or noncompliance.

To avoid those outcomes, configuration management delivers documentation, consistent maintenance and change controls. These capabilities help an organization not only identify its IT assets but also understand the relationships between those assets.

What are configuration management tools and what are they used for?
The automation built into configuration management tools enables sysadmins to create checks and redundancies that keep assets in a desired state. That higher level of automation improves overall efficiency and helps admins to offset problems that result from human error and manual server configurations. These benefits are amplified when an organization shifts to a DevOps workflow.

Effective configuration management, or CM, can boost productivity, reduce IT costs and help to ensure continuous delivery of IT services. A standard approach for successful management is through the deployment of CM agents installed on multiple servers that take commands from the master server. An administrator can send a configuration file to the master server to execute specific actions on multiple target hosts, whether on premises, in the cloud or in a hybrid environment.

Let’s explore the top configuration management tools in DevOps, evaluate their features and consider key aspects that set them apart. All of these tools offer versions for Linux, Unix, Windows and macOS.

Ansible
Ideal for small DevOps teams that need a fast, lightweight configuration management tool, Ansible offers a foundation for automation across organization-wide systems. Administrators can send individual shell commands to entire sets of services and flexibly organize their environments. In addition to accessing Ansible Galaxy for role frameworks and playbooks, sysadmins can deploy modules for diverse tasks, from dynamic AWS integrations and container orchestration to basic configuration files. Ansible users need to write large amounts of procedural code; familiarity with Python lessens this burden.

Chef
Chef, either on premises or hosted in the cloud, is a useful DevOps tool for achieving speed, scale and consistency. It requires IT to run a master server for storing infrastructure state and then deploy agent software for the configuration of multiple servers. An open source version of Chef offers a standalone configuration format titled Chef Solo. The integrated suite of Chef tools enables IT teams to manage configurations in the cloud, on premises or in hybrid environments. Chef incorporates recipes written in the open source Ruby programming language. The Chef Enterprise Automation Stack represents the commercial distribution and offers unified security, compliance, infrastructure and application automation with monitoring. Progress Software acquired Chef in 2020, and offers combinations of Chef components (Habitat, Infra, Automate) called Infrastructure Management and App Delivery.

CFEngine
A widely used and established open source configuration management tool, CFEngine incorporates Promise theory to implement configurations. It relies on voluntary cooperation from lightweight agents on the managed resources. CFEngine runs on the C language and, because of its small memory footprint, performs faster with fewer dependencies than most other tools. While the customization process can seem overwhelming, the tool’s enthusiastic community offers support and guidance.

Consul
Consul offers a straightforward management product for configuration storage and access, and it provides HTTP and DNS APIs for service discovery. In addition to being easy to deploy and use, Consul is written in Go and available as a native binary, making it effective across large, distributed systems. Through dynamic service discovery, Consul provides health checking, key/value stores and support for maintenance of multiple data centers.

Puppet
Puppet’s model-driven system and reliance on the Ruby language help simplify its setup process and use. It offers the ability to automate tasks, from installing packages to automatically updating configurations. Puppet requires a master server for storing state information, offers easy-to-manipulate modules and relies on the push model for sending updates. The open source edition of Puppet is free, while Puppet Enterprise integrates well with major DevOps tools and is free for up to 10 nodes.

Rudder
A derivative of CFEngine, Rudder offers a UI that may specifically appeal to configuration management novices. While its web front end is built with the Scala language, local agents are written in C. It implements the Desired State Configuration feature, which enables PowerShell scripts to specify the config parameters of Windows-based servers. This open source CM tool deploys light local agents and identifies node characteristics to further simplify system configurations.

SaltStack
Offering master or masterless configuration approaches, SaltStack provides fast, event-driven automation using ZeroMQ as a brokerless, asynchronous messaging library. It was created for high-speed data collection and offers integrations with the major cloud providers, supporting the infrastructure as code approach. SaltStack’s features are designed for environments that rely on cloud computing, virtualization and containerization — all key elements of the DevOps approach. VMware announced its acquisition of SaltStack in late 2020, and has integrated it with the vRealize Automation suite.

Terraform
As a configuration management tool geared to provisioning, Terraform enables IT teams to codify APIs for easy editing, revising and versioning shared configurations. An organization that relies on containers and virtual machine images will find Terraform to be especially useful. The tool employs an immutable configuration approach to prevent drift and to keep servers synced at a desired state. For monitoring cloud-based configurations, Terraform relies on the cloud provider’s APIs; admins can simply use API keys for authentication

Are you an AWS DevOps Engineer who is keen to lead and define the DevOps practices of an organization going through a major transformation? Reporting to the CTO you will have the opportunity to work closely with the architects and delivery team and define how operations work. You will be responsible for delivery DevOps best practice and will help define how the operations will work.

Key Benefits of this role

Opportunity to be a lead in a transformation programme
Very competitive salary and benefits
Challenging role with ability to make a real difference to the delivery process
The Role

You will be required to

1 Provide technical leadership in effectively managing the AWS environment and DevOps toolchain
2 Automate deployment of container applications/services in Kubernetes, system configurations and security settings
3 Provide guidance and support during deployment
4 Create and manage CI/CD pipelines in Jenkins
5 Write and maintain Terraform scripts
6 Build DevOps data flow architecture map
7 Help define development standards, procedures and guidelines to improve the overall  development process
The Person:

1 You will have experience as a technically hands on DevOps Engineer (with leadership experience)
2 Demonstrable experience of driving DevOps best practice and creating and managing CI/CD pipelines and ideally have experience with Jenkins
Experience with Kubernetes
3 Strong experience in AWS administration and development
4 Experience of configuration management tools such as Chef, Puppet, Ansible
5 Excellent communication skills and ability to lead and get buy in for new project roll outs
Strong people management and leadership skills

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.”

Major Vendors in the DevOps Platform Market

The DevOps toolchain is crowded with both established enterprise vendors and specialist open-source-backed companies. Organisations evaluating platforms will typically encounter the following key players:

• Puppet Labs – Configuration management and infrastructure automation
• Chef (Progress) – Policy-based infrastructure automation and compliance
• Docker Inc. – Container runtime, image registry, and developer tooling
• Red Hat (Ansible) – Agentless automation, OpenShift container platform
• Atlassian – Jira, Bitbucket, and Confluence for planning and collaboration
• SaltStack (now part of VMware) – Event-driven automation and configuration management
• CA Technologies (now Broadcom) – Enterprise release automation and value-stream management
• Rackspace – Managed DevOps services and multi-cloud operations
• XebiaLabs (now Digital.ai) – Release orchestration and DevOps intelligence
• VersionOne (now Digital.ai) – Agile planning and value-stream management
• Cisco – Network automation and AppDynamics APM
• CollabNet (now Digital.ai) – ALM and agile planning tools
• HP (Micro Focus) – ALM, load testing, and release automation
• IBM – UrbanCode Deploy, Tekton-based pipelines on OpenShift
• Microsoft – Azure DevOps Services and GitHub Actions
• Spirent Communications – Network test automation
• VMware – Tanzu portfolio, acquired SaltStack
• DBmaestro – Database DevOps and release automation

Market Segmentation by Platform Maturity

Market research typically classifies DevOps platform adoption into three maturity tiers. Understanding where your organisation sits helps in selecting the right tooling and investment level:

• DevOps Ready – The organisation has assessed its DevOps readiness and has a roadmap in place but has not yet deployed integrated toolchains at scale.
• DevOps Enabled – Core automation pipelines (source control, CI, artifact management) are operational, with partial adoption of monitoring and feedback loops.
• DevOps Capable – End-to-end automation, continuous delivery, security integration (DevSecOps), and measurable value-stream management are in production.

Key Industry Verticals Driving Adoption

DevOps platform adoption is broad, but several verticals consistently lead in spending and maturity:

• IT and Technology – Software companies and SaaS providers are the earliest and heaviest adopters, driven by competitive release velocity.
• Banking, Financial Services, and Insurance (BFSI) – Regulatory compliance, fraud detection, and mobile banking modernisation push investment in automated pipelines and security scanning.
• Retail and e-Commerce – Seasonal traffic spikes and omnichannel delivery requirements make continuous deployment and auto-scaling critical.
• Telecom – Network function virtualisation (NFV) and 5G rollouts depend heavily on infrastructure-as-code and automated testing.
• Education – Cloud migration of learning management systems and EdTech platforms is increasing DevOps adoption.
• Other sectors – Healthcare, manufacturing, and government are growing adopters.

Regional Market Landscape

DevOps platform investment is distributed globally, with adoption levels influenced by cloud infrastructure maturity, developer talent pools, and digital transformation spending:

• North America – Historically the largest market, driven by US hyperscaler ecosystems (AWS, Azure, GCP) and a mature enterprise software industry.
• Europe – Strong in the UK, Germany, and the Netherlands; GDPR compliance requirements are accelerating DevSecOps investment.
• Asia-Pacific – Fast-growing, with China, Japan, South Korea, India, and Australia leading investment in cloud-native platforms.
• South America – Brazil and Mexico are the primary growth markets, with adoption concentrated in BFSI and retail.
• Middle East and Africa – Emerging adoption driven by government digital transformation programmes and smart city initiatives.

Core Forces Driving Market Growth

Several structural trends are sustaining DevOps platform expansion globally:

• Cloud-native migration – Kubernetes, microservices, and serverless architectures require robust CI/CD, observability, and secrets management tooling.
• Security integration – Shift-left security practices (SAST, DAST, SCA in pipelines) are turning DevSecOps from a differentiator into a baseline requirement.
• Regulatory compliance – Auditable pipelines and automated policy enforcement reduce compliance overhead in regulated industries.
• Developer experience focus – Internal developer platforms (IDPs) and platform engineering teams are emerging to reduce cognitive load and standardise toolchains.
• AI-assisted development – Code review automation, anomaly detection in pipelines, and AIOps are becoming expected platform features.

Competitive Landscape and Consolidation Trends

The DevOps platform market has undergone significant consolidation since 2018. Notable acquisitions include:

• Broadcom acquired CA Technologies (2018)
• Digital.ai merged XebiaLabs, VersionOne, CollabNet, and Arxan (2019–2021)
• VMware acquired SaltStack (2020)
• Microsoft acquired GitHub (2018) and deepened Azure DevOps integration
• Progress acquired Chef (2020)

This consolidation reflects a market shift toward unified value-stream management platforms rather than point tools. Buyers are increasingly evaluating end-to-end solutions that cover planning, coding, building, testing, securing, releasing, deploying, and monitoring — often referred to as the full DevOps lifecycle.

What to Look for When Evaluating a DevOps Platform

When assessing vendors for your organisation, consider the following criteria:

1. Integration breadth – Does the platform integrate with your existing SCM, ticketing, cloud, and monitoring tools?
2. Self-hosted vs. SaaS – Regulated industries often require on-premises or private-cloud deployments.
3. Scalability – Can the platform support thousands of pipelines and distributed teams without degradation?
4. Security features – Native SAST/DAST scanning, secrets detection, and role-based access control (RBAC) are baseline requirements.
5. Observability integration – Deployment frequency, lead time, MTTR, and change failure rate (DORA metrics) should be measurable from within or alongside the platform.
6. Vendor support and community – Assess the size of the community, quality of documentation, and enterprise support SLAs.
7. Total cost of ownership – Include licensing, training, migration, and ongoing maintenance in your evaluation.

Summary

The global DevOps platform market encompasses a wide range of vendors — from open-source automation specialists to large enterprise suites. Adoption is accelerating across North America, Europe, and Asia-Pacific, with BFSI and retail verticals leading investment. The market is maturing rapidly through consolidation, with buyers favouring integrated platforms over fragmented point tools. Engineers and architects evaluating DevOps platforms should focus on integration capability, security posture, observability, and the total cost of operating the toolchain at scale.

What Is the DevOps Platform Market?

The DevOps Platform market encompasses the tools, platforms, and services that enable organizations to adopt DevOps practices — integrating software development and IT operations to shorten delivery cycles, improve deployment frequency, and increase system reliability. The market includes a wide range of products: configuration management tools, container platforms, CI/CD pipelines, collaboration software, and infrastructure automation frameworks.

Market research firm Contrive Datum Insights published an industry analysis of this market, examining vendor strategies, adoption trends across verticals, regional demand, and the impact of the COVID-19 pandemic on enterprise technology procurement.

Key Vendors in the DevOps Platform Market

The report profiles a broad set of established and emerging players. Understanding each vendor’s positioning helps DevOps practitioners evaluate toolchain options and helps organizations assess competitive dynamics when choosing platforms. The vendors covered include:

• Puppet Labs – Infrastructure automation and configuration management
• Chef (Progress) – Policy-based infrastructure automation and compliance
• Docker Inc. – Container runtime and developer tooling
• Red Hat / Ansible – Agentless automation and OpenShift Kubernetes platform
• Atlassian – Developer collaboration, issue tracking (Jira), and CI/CD (Bamboo, Bitbucket Pipelines)
• SaltStack (now part of VMware) – Event-driven automation and remote execution
• CA Technologies (now Broadcom) – Enterprise release automation and agile planning
• Rackspace – Managed cloud and DevOps professional services
• XebiaLabs (now Digital.ai) – Release orchestration and DevOps intelligence
• VersionOne (now Digital.ai) – Agile and scaled agile planning
• Cisco – Network automation and AppDynamics observability
• CollabNet (now Digital.ai) – Enterprise Agile and DevOps toolchain
• HP (Micro Focus) – ALM, testing, and release automation
• IBM – DevSecOps toolchain, UrbanCode Deploy, and hybrid cloud
• Microsoft – Azure DevOps, GitHub Actions, and cloud-native tooling
• Spirent Communications – Test automation for networking and cloud infrastructure
• VMware – Tanzu portfolio for Kubernetes and multi-cloud delivery
• DBmaestro – Database DevOps and deployment automation

This is a diverse field that spans pure-play DevOps vendors, large enterprise software companies, and cloud hyperscalers — each competing across overlapping capability areas such as CI/CD, infrastructure-as-code, monitoring, and security integration.

Market Segmentation by Type

The report classifies DevOps platform offerings into three maturity-based categories, reflecting how deeply an organization or a platform has embedded DevOps principles into its operations:

• DevOps Ready – Platforms or organizations at the early stage of DevOps adoption. Tooling exists but integration and automation coverage is limited.
• DevOps Enabled – Intermediate adoption where core pipelines, automation, and collaboration practices are in place and delivering measurable improvements.
• DevOps Capable – Fully mature implementations with end-to-end automation, continuous feedback loops, security integration (DevSecOps), and measurable business outcomes tied to delivery performance.

Market Segmentation by Industry Vertical

DevOps platform adoption is not uniform across industries. The report segments demand by the following verticals:

• IT & Technology – The primary adopter segment, driven by the need for rapid software releases and infrastructure agility.
• BFSI (Banking, Financial Services & Insurance) – Increasing adoption driven by regulatory compliance automation, fraud detection systems, and digital banking transformation.
• Retail – E-commerce platforms, supply chain systems, and personalization engines require frequent deployments and high availability.
• Telecom – Network function virtualization (NFV) and OSS/BSS modernization are driving DevOps adoption among carriers.
• Education – Learning management systems and digital learning platforms increasingly use cloud-native DevOps practices.
• Others – Healthcare, government, manufacturing, and energy sectors are at varying stages of DevOps adoption.

Regional Coverage

The report covers global demand across the following regions:

• North America – United States, Canada, Mexico
• Europe – Germany, United Kingdom, France, Italy, Russia, Turkey, and others
• Asia-Pacific – China, Japan, India, Australia, South Korea, Vietnam, Malaysia, Philippines, Thailand, Indonesia
• South America – Brazil and surrounding markets
• Middle East & Africa – GCC countries and Egypt

North America and Europe represent the most mature DevOps markets, with high cloud adoption and established enterprise toolchain ecosystems. Asia-Pacific is recognized as a high-growth region, driven by digital transformation initiatives across financial services, manufacturing, and telecommunications.

COVID-19 Impact on the DevOps Platform Market

The COVID-19 pandemic accelerated several trends already underway in enterprise IT. Remote work mandates pushed organizations to fast-track cloud migration, requiring more robust CI/CD pipelines and infrastructure automation. Industries that had previously been slow to adopt DevOps — such as healthcare and education — faced sudden pressure to deliver and scale digital services rapidly.

The Contrive Datum Insights report covers both pre- and post-COVID market dynamics, examining how vendor revenues, enterprise procurement patterns, and platform priorities shifted during and after the pandemic disruption period.

Report Structure and Scope

For readers evaluating whether to procure the full report, the table of contents covers the following areas:

1. Introduction and market overview
2. Industry cost structure and economic impact
3. Emerging trends and new technologies, with key player profiles
4. Global market analysis, growth factors, and trend lines
5. Application-level analysis and business potential
6. Market segmentation by type, application, and region
7. Cross-tabulated analysis by application, type, and end-user
8. Detailed vendor profiles
9. Development trend analysis
10. Conclusions and strategic recommendations

Why This Market Analysis Matters for DevOps Practitioners

Industry market reports like this one serve several practical purposes for DevOps engineers and engineering managers:

• Toolchain decisions: Understanding which vendors are investing in which capabilities helps teams anticipate the long-term viability of the tools they adopt.
• Organizational benchmarking: Vertical-specific adoption data helps teams understand where their industry peers are on the DevOps maturity curve.
• Budget justification: Market sizing and growth projections are frequently used to support internal business cases for DevOps investment.
• Vendor negotiation: Competitive landscape data provides context when evaluating vendor pricing and enterprise licensing terms.

The DevOps platform market continues to consolidate — several vendors listed above (XebiaLabs, VersionOne, CollabNet) have merged under the Digital.ai umbrella, and SaltStack was acquired by VMware. Teams relying on this or similar reports should verify current vendor ownership and product roadmaps independently.

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.

Why Choose Open Source Development Tools?

The tools that make up your development stack will vary depending on your programming language, deployment targets, and team workflows. Common categories include source code management, integrated development environments (IDEs), text and source editors, continuous integration (CI) servers, and configuration management systems.

Development teams can always license tools from proprietary vendors, but open source alternatives offer several meaningful advantages:

• Cost: Many open source tools are free to use, with optional paid tiers for enterprise support, allowing teams to evaluate tools before committing budget.
• Extensibility: Widely adopted open source tools typically spawn rich ecosystems of plugins, add-ons, and community-maintained extensions.
• Broad compatibility: Many open source tools are platform-agnostic or explicitly designed to integrate with a large number of platforms and languages.
• Longevity: Community-maintained projects often continue to receive support long after an original sponsoring organization steps back, reducing vendor lock-in risk.

10 Top Open Source Development Tools

1. Git

Git is a distributed version-control system that is the de facto standard for source code management in modern software development. It is commonly paired with web-based hosting platforms such as GitHub and GitLab, which add pull requests, code review workflows, and CI/CD integrations on top of Git’s core branching and merging capabilities. Teams working primarily on Windows should be aware that Git’s Linux roots mean some edge-case behaviors and tooling integrations can feel less polished on Windows than on Linux or macOS, though this gap has narrowed considerably in recent years.

2. Apache Subversion (SVN)

Apache Subversion, widely known as SVN, is a centralized version-control system. Unlike Git, which defaults to local repositories, SVN stores all code history on a central server. This centralized model can simplify access control and auditing in regulated environments. Teams that need to interoperate with both SVN and Git repositories can use the git-svn bridge, which allows standard Git commands to read from and write to Subversion repositories.

3. Eclipse IDE

Eclipse is a mature, open source integrated development environment written primarily in Java. It is most widely used for Java development but supports a broad range of programming languages through its plugin marketplace. That extensibility is one of Eclipse’s greatest strengths, though it also introduces a potential complication: some plugins declare dependencies on other plugins, which can make it difficult to add or remove individual extensions without inadvertently breaking existing functionality.

4. Apache NetBeans

NetBeans is another Java-based open source IDE that supports development across many programming languages. Where Eclipse leans on its plugin ecosystem to unlock functionality, NetBeans takes a more batteries-included approach, providing a wider range of features out of the box. This can mean less initial configuration work, though it may also mean a heavier default installation footprint. NetBeans became an Apache project in 2016, which strengthened its governance and long-term support story.

5. GNU Emacs

Emacs is a highly extensible open source text editor with roots in the GNU project dating to the mid-1980s. Beyond basic editing, Emacs can be configured into a full IDE with support for language servers, debuggers, version control, and email. It supports complex automation through its macro system and the built-in Emacs Lisp scripting language. The trade-off is a notoriously steep initial learning curve and a time investment in configuration before the environment feels productive.

6. Vim

Vim is another venerable open source text editor with a loyal user base. It starts quickly and runs efficiently even on resource-constrained systems. Like Emacs, Vim can be extended into a near-complete development environment through plugins. The long-running debate over which editor has the steeper learning curve — Vim or Emacs — is unlikely to be settled here, but both remain excellent, proven choices for developers who prefer staying close to the terminal. Neovim, a modern fork of Vim, has gained significant traction for its improved plugin architecture and built-in support for the Language Server Protocol (LSP).

7. Atom

Atom was developed by GitHub and marketed as a “hackable” text editor aimed at modern development workflows. It offered deep GitHub integration, built-in collaborative editing via Teletype, and a large package ecosystem. However, GitHub officially sunset Atom in December 2022, citing the growth of Visual Studio Code as a primary reason. Teams currently using Atom should plan migration to an actively maintained alternative such as VS Code, Neovim, or Helix.

8. Jenkins

Jenkins is one of the most widely deployed open source CI/CD servers in the industry. Its extensive plugin ecosystem — numbering in the hundreds of plugins — enables integration with nearly any version control system, build tool, testing framework, or deployment target. Jenkins can run on any modern operating system and also inside Docker containers, making it flexible for both on-premises and cloud-based CI pipelines. Common operational considerations include plugin compatibility management and the maintenance overhead of keeping a self-hosted Jenkins instance patched and performant.

9. Chef

Chef is an open source configuration management tool that uses a Ruby-based domain-specific language to define infrastructure as code. Administrators write “cookbooks” and “recipes” that describe the desired state of a system; Chef then converges the actual system state to match those specifications. Chef provides cross-platform support for Linux, macOS, and Windows. The Ruby DSL offers significant expressive power but adds a learning curve for teams not already familiar with Ruby.

10. Ansible

Ansible is an agentless open source automation and configuration management tool that uses YAML-based playbooks to define infrastructure and application configuration. Because it connects to managed nodes over SSH rather than requiring a dedicated agent, initial setup is generally simpler than Chef. This agentless design also reduces the attack surface on managed hosts. The trade-off is that Ansible’s declarative model and module library, while broad, may be less suited to highly complex, custom configuration scenarios where Chef’s full Ruby expressiveness provides an advantage. Windows support exists but is generally considered less mature than Linux support.

Choosing the Right Tool for Your Stack

No single tool excels in every context. The right open source development stack depends on your team’s programming languages, operating system targets, existing infrastructure, and operational maturity. Start by identifying the category of tooling you need — version control, IDE, CI server, or configuration management — then evaluate the options in that category against your specific requirements. The open source community around each of these tools means documentation, tutorials, and community support are readily available regardless of which tools you choose.

Original article reference: searchapparchitecture.techtarget.com

What Is a DevOps Platform?

A DevOps platform is a toolchain or integrated suite that supports the continuous planning, development, integration, delivery, and operation of software. Platforms range from point tools that excel at a single stage of the pipeline (such as configuration management or container orchestration) to fully integrated suites that cover the entire software delivery lifecycle. Market analysts typically classify platforms into three capability tiers:

• DevOps Capable: Tools that support isolated DevOps practices but require significant integration effort to connect stages of the pipeline.
• DevOps Enabled: Platforms with built-in integrations between key stages, reducing manual handoffs and enabling measurable flow metrics.
• DevOps Ready: End-to-end platforms designed from the ground up to support the full DevOps lifecycle, including planning, source control, CI/CD, monitoring, and feedback loops.

Key Vendors in the DevOps Platform Market

The following companies have been identified in market research as significant participants in the global DevOps platform space. Each occupies a distinct position in the ecosystem:

• Puppet Labs: Infrastructure-as-code and configuration management, widely adopted in large enterprise environments.
• Chef (Progress): Configuration management and compliance automation with a strong Ruby-based DSL ecosystem.
• Docker Inc.: Container runtime and image management, foundational to modern CI/CD pipelines.
• Red Hat (Ansible): Agentless automation and orchestration platform, tightly integrated with the Red Hat OpenShift ecosystem.
• Atlassian: Collaboration-first toolchain including Jira, Confluence, Bitbucket, and Bamboo.
• SaltStack (acquired by VMware): Event-driven automation and configuration management with strong remote execution capabilities.
• Broadcom: Enterprise software portfolio following the acquisition of CA Technologies, including Rally for Agile planning.
• Rackspace: Managed cloud services supporting DevOps transformation engagements.
• XebiaLabs (Digital.ai): Release orchestration and deployment automation for large, complex pipelines.
• VersionOne (Digital.ai): Agile and SAFe planning platform for scaled enterprise delivery.
• Cisco: Network infrastructure and security tooling increasingly integrated into DevSecOps pipelines.
• CollabNet: Application lifecycle management and Agile planning tools.
• IBM: Broad DevOps portfolio including IBM DevOps Deploy (formerly UrbanCode) and cloud-native toolchains.
• Microsoft: Azure DevOps and GitHub, covering planning, source control, CI/CD, and artifact management.
• VMware: Tanzu portfolio for Kubernetes-based application delivery and operations.
• DBmaestro: Database DevOps automation, focused on bringing release automation discipline to database change management.
• HP (Micro Focus): Enterprise ALM, testing, and release management tools.
• Spirent Communications: Test automation for network and application performance.

Primary Industry Verticals Driving Adoption

DevOps platform adoption is not uniform across industries. Market research segments demand by end-user vertical, with the following sectors representing the largest areas of investment:

• Information Technology: Software vendors and IT service providers are the earliest and heaviest adopters, driven by competitive pressure to shorten release cycles.
• Banking, Financial Services, and Insurance (BFSI): Regulatory compliance requirements are converging with DevOps practices through DevSecOps adoption, making this a high-growth segment.
• Retail: Omnichannel commerce demands rapid feature delivery and high availability, accelerating DevOps investment.
• Telecommunications: Network function virtualisation (NFV) and 5G rollouts are driving infrastructure automation and continuous delivery adoption.
• Education: Growing adoption of learning management platforms and remote education infrastructure is increasing DevOps tooling investment in this sector.

Regional Market Breakdown

The DevOps platform market is global, but adoption patterns and growth rates differ significantly by region. Analysts segment the market as follows:

• North America: The United States, Canada, and Mexico. North America consistently represents the largest share of DevOps platform revenue, driven by a mature cloud ecosystem and high concentration of software-first enterprises.
• Europe: The UK, France, Germany, Italy, Spain, BeNeLux, and Russia. GDPR compliance requirements are shaping DevSecOps adoption patterns in this region.
• Asia-Pacific: India, China, Japan, South Korea, Indonesia, Thailand, Singapore, and Australia. Rapid digital transformation programmes and a growing number of technology startups are driving strong growth in this region.
• South and Central America: Argentina, Chile, Brazil, and broader LATAM markets, where cloud adoption is accelerating DevOps platform demand.
• Middle East and Africa: Saudi Arabia, UAE, Israel, Turkey, Egypt, and South Africa, with government-led digital transformation programmes contributing to growth.

Competitive Landscape

Competition in the DevOps platform market is intensifying on several fronts:

• Consolidation through acquisition: Notable examples include VMware acquiring SaltStack, Digital.ai merging XebiaLabs and VersionOne, and Broadcom absorbing CA Technologies. This trend is reducing the number of independent point-tool vendors and creating broader platform players.
• Open-source as a competitive moat: Vendors such as Red Hat (Ansible), HashiCorp, and the broader Kubernetes ecosystem use open-source projects to drive adoption before monetising through enterprise support and SaaS offerings.
• Cloud-native platform bundling: Hyperscalers (AWS, Azure, Google Cloud) bundle DevOps tooling with their cloud platforms, creating pricing pressure for independent vendors.
• AI-assisted development and operations: An emerging differentiator, with vendors integrating AI-driven code review, anomaly detection, and predictive pipeline insights into their platforms.

What DevOps Engineers Should Take From This Market Overview

Market research reports on the DevOps platform sector are primarily aimed at investors, procurement teams, and business analysts. For practising DevOps engineers, the more useful signals from this landscape are:

• Vendor longevity risk: Consolidation means tools you adopt today may be acquired, rebranded, or discontinued. Favour tools with strong open-source communities or standards-based integrations (such as OCI-compliant container tooling or OpenTelemetry-compatible observability).
• Platform vs. best-of-breed: Integrated platforms reduce integration overhead but can introduce vendor lock-in. Evaluate whether your organisation’s pipeline complexity justifies a single-vendor platform or a curated best-of-breed toolchain.
• Vertical-specific compliance requirements: If you work in BFSI or a regulated industry, prioritise platforms with built-in audit trails, policy enforcement, and compliance reporting.
• Regional data residency: For organisations operating across multiple geographies, confirm that your chosen platform can satisfy data residency requirements in each region before committing to a rollout.

Note: The market research summarised in this article was originally published by HTF Market Intelligence and cited by industrytoday.co.uk in 2020. Vendor positions, market shares, and ownership details may have changed since that publication date. Always verify current product status and ownership directly with vendors before making procurement decisions.

Overview

The global DevOps Platform market attracted significant analyst attention in 2020 as organisations accelerated software delivery pipelines in response to remote-work pressures amplified by the COVID-19 pandemic. A report titled Global DevOps Platform Market 2020 by Company, Regions, Type and Application, Forecast to 2026, published by MarketsandResearch.biz, examined market size, competitive dynamics, and growth trajectories across product types, application verticals, and geographic regions for the period 2020–2026.

The research combined qualitative and quantitative analysis — including Porter’s Five Forces, bottom-up and top-down sizing approaches, and data triangulation — to evaluate market share, profitability trends, and expansion strategies of the leading vendors.

Key Vendors Covered

The report profiled a broad set of vendors spanning open-source ecosystems, cloud-native platforms, and enterprise incumbents:

• Puppet Labs – infrastructure automation and compliance
• Chef (Progress) – configuration management and policy-as-code
• Docker Inc. – container runtime and developer toolchain
• Red Hat (Ansible) – agentless automation and OpenShift container platform
• Atlassian – Jira, Bitbucket, and Confluence for planning and collaboration
• SaltStack – event-driven automation and remote execution
• CA Technologies (Broadcom) – enterprise value-stream management
• Rackspace – managed cloud and DevOps-as-a-service
• XebiaLabs (Digital.ai) – release orchestration and intelligent DevOps
• VersionOne (Digital.ai) – agile planning and portfolio management
• Cisco – network automation and application-centric infrastructure
• CollabNet (Digital.ai) – ALM and DevOps platform
• HP (Micro Focus) – testing and ALM toolchains
• IBM – cloud-native toolchains and AI-driven operations
• Microsoft – Azure DevOps and GitHub
• Spirent Communications – network and application testing
• VMware – Tanzu application platform and vRealize automation
• DBmaestro – database DevOps and release automation

Product Type Segments

The report categorised DevOps platforms along a maturity spectrum:

• DevOps Capable – tools that support isolated DevOps practices (e.g., source control, basic CI) without deep integration across the software delivery lifecycle.
• DevOps Enabled – platforms that integrate multiple pipeline stages — build, test, release — providing consistent workflows but still requiring significant custom glue code.
• DevOps Ready – end-to-end platforms offering native integration across planning, development, security, and operations with out-of-the-box automation and observability.

Revenue, volume projections, production patterns, and market-share data were reported for each segment through 2026.

Application Verticals

DevOps platform adoption was analysed across the following industry verticals:

• IT – the largest adopter segment, driven by software product companies and managed-service providers optimising release velocity.
• BFSI – banks and insurers accelerating digital channels while navigating compliance and audit requirements.
• Retail – e-commerce operators requiring frequent, low-risk deployments to support seasonal demand spikes.
• Telecom – network function virtualisation and 5G rollout creating demand for infrastructure-as-code tooling.
• Education – growing adoption of online learning platforms necessitating reliable continuous delivery pipelines.
• Others – healthcare, manufacturing, government, and other sectors with emerging DevOps programmes.

Regional Breakdown

The report provided market sizing and forecasts across five major geographies:

North America typically leads DevOps platform adoption owing to high cloud maturity and a dense concentration of software vendors. Asia-Pacific was identified as a fast-growth region, driven by digital transformation initiatives in India and Southeast Asia.

COVID-19 Impact on the DevOps Platform Market

The pandemic created both headwinds and tailwinds for the DevOps platform market in 2020. Budget freezes in sectors like retail, travel, and hospitality reduced discretionary tooling spend. At the same time, the forced shift to distributed engineering teams accelerated demand for cloud-hosted CI/CD pipelines, collaboration tools, and infrastructure automation — areas where DevOps platforms provide the most immediate value. Organisations that had already adopted DevOps practices were generally better positioned to maintain delivery cadence under remote-work constraints.

Research Objectives

According to the report summary, the study aimed to:

• Quantify global DevOps platform market size (value and volume) by company, region, product type, and application for historical years and through 2026.
• Identify key market segments and sub-segments.
• Pinpoint growth drivers, opportunities, and industry-specific challenges and risks.
• Project market value and volume at the regional and country level.
• Profile leading vendors with company background, product specifications, production capacity, and market share data.

Research Methodology

The report was structured around three analytical frameworks:

• Porter’s Five Forces – competitive rivalry, supplier power, buyer power, threat of new entrants, and threat of substitutes.
• Bottom-up and top-down sizing – reconciling vendor-level revenue data with macro-level market estimates.
• Data triangulation – cross-validating findings from primary interviews, secondary sources, and internal analyst models.

Takeaways for DevOps Practitioners

While market research reports are aimed at investors and vendor strategists, they carry practical signals for engineering and platform teams:

• Vendor consolidation is continuing. Several of the vendors listed (XebiaLabs, VersionOne, CollabNet) have since merged under the Digital.ai umbrella — a trend worth monitoring when evaluating long-term toolchain risk.
• Platform breadth matters. The “DevOps Ready” tier reflects buyer preference for integrated platforms over point solutions, reducing integration overhead and context switching.
• Enterprise incumbents (IBM, Microsoft, Red Hat) are competing directly with DevOps specialists, bundling capabilities into cloud platform subscriptions that can undercut standalone tools on total cost of ownership.
• Regulated verticals (BFSI, healthcare) represent growing opportunity for vendors who can demonstrate compliance-friendly audit trails, policy-as-code, and role-based access controls.

For precise market-size figures, compound annual growth rates (CAGRs), and vendor share tables, refer to the original MarketsandResearch.biz report directly.

What Is SNMP and Why Does Monitoring It Matter?

Simple Network Management Protocol (SNMP) is one of the most widely deployed protocols for monitoring and managing network infrastructure. Defined in a series of IETF RFCs, SNMP allows management systems to collect performance data, receive alerts, and in some cases reconfigure devices — all over a standardised UDP-based interface (port 161 for queries, port 162 for traps).

SNMP is supported by virtually every enterprise-grade router, switch, firewall, server, UPS, and storage device, making it a foundational layer of network observability. Even in environments that have adopted modern telemetry protocols such as gNMI or OpenTelemetry, SNMP often remains the only option for older or embedded hardware.

Core SNMP Architecture Components

Understanding what SNMP monitoring tools actually manage requires familiarity with the four main architectural components that any tool in this space must handle:

• SNMP Manager — The central management station (or software process) that sends queries (GET, GETNEXT, GETBULK) to devices and receives trap notifications. This is the engine of any SNMP monitoring tool.
• SNMP Agent — Software running on the managed device (router, server, printer, etc.) that listens for manager requests, reads the relevant counters or state variables, and returns responses. Agents also proactively send traps when threshold events occur.
• Managed Devices — The physical or virtual infrastructure being monitored: network switches, routers, firewalls, servers, storage arrays, environmental sensors, and any other SNMP-capable endpoint.
• Management Information Base (MIB) — A hierarchical, tree-structured schema that defines every object an agent can expose. Each object has a unique Object Identifier (OID). Vendors publish proprietary MIBs alongside the standard MIBs defined by the IETF (e.g., MIB-II, IF-MIB).

A capable SNMP monitoring tool must be able to parse and walk MIBs, poll agents on configurable intervals, correlate traps to known thresholds, and visualise or alert on the resulting data.

SNMP Versions: v1, v2c, and v3

Most tools on the market support all three SNMP versions, but the choice matters for security:

• SNMPv1 — The original 1988 specification. Community-string authentication only; data sent in plain text. Avoid in production where possible.
• SNMPv2c — Adds GETBULK for efficient bulk retrieval and 64-bit counters (critical for high-speed interfaces). Still uses plain-text community strings.
• SNMPv3 — Introduces authentication (MD5 or SHA) and optional encryption (DES or AES). The only version suitable for environments with security or compliance requirements. Many organisations still run v2c internally due to device or tooling limitations.

Key Vendors in the SNMP Monitoring Tool Space

The market research report cited Cisco Systems, Nagios Enterprises, Microsoft, OpenNMS Group, HCL, and Zoho as notable players. Here is a brief, factual description of each vendor’s known position in this space:

Cisco Systems

Cisco is both a major producer of SNMP-capable devices and a vendor of network management platforms. Products such as Cisco Prime Infrastructure and Cisco DNA Center include built-in SNMP polling and MIB management for Cisco hardware.

Nagios Enterprises

Nagios is one of the most widely known open-source-rooted monitoring platforms. The core Nagios engine, along with Nagios XI (the commercial product), supports SNMP polling and trap handling through a rich ecosystem of community and commercial plugins. Nagios XI ships with built-in MIB management and trap translation.

Microsoft

Microsoft’s System Center Operations Manager (SCOM) includes network device discovery and SNMP-based monitoring. Windows Server also ships with an optional SNMP service that can expose Windows performance counters to external managers. Microsoft’s position in pure-play SNMP tooling is secondary to its role as a managed-device platform.

OpenNMS Group

OpenNMS is an open-source enterprise network management platform with strong SNMP capabilities including auto-discovery, SNMP data collection, MIB compiler, and trap daemon. The OpenNMS Group offers commercial support and the Horizon and Meridian distributions.

HCL Technologies

HCL has network and infrastructure management offerings, including tools that incorporate SNMP monitoring as part of broader IT operations management suites.

Zoho (ManageEngine)

Zoho’s ManageEngine division produces OpManager, a widely deployed network monitoring platform that supports SNMP v1/v2c/v3 polling, MIB browsing, and trap processing. ManageEngine also offers dedicated tools such as MibBrowser Free Tool and OpUtils.

Other Widely Used SNMP Monitoring Tools

The vendor list above is not exhaustive. Other tools with strong SNMP support that DevOps and network teams commonly deploy include:

• PRTG Network Monitor (Paessler) — Sensor-based model; dedicated SNMP sensors for standard and custom OIDs.
• Zabbix — Open-source; supports SNMP polling and traps natively with flexible MIB-based item discovery.
• LibreNMS — Open-source auto-discovering network monitoring system built on SNMP, with a large community MIB library.
• SolarWinds Network Performance Monitor — Commercial platform with deep SNMP integration and automated MIB compilation.
• Checkmk — Combines agent-based and SNMP-based monitoring with automated device discovery.

Typical Application Areas

SNMP monitoring tools are used across a range of operational scenarios:

• Network performance monitoring — Interface utilisation, error rates, packet loss, and latency on routers and switches.
• Hardware health monitoring — CPU and memory usage, fan speeds, temperature sensors, and power supply status on servers and appliances.
• Availability monitoring — Up/down detection via SNMP reachability and trap-based alerts.
• Capacity planning — Long-term trending of bandwidth, storage, and resource utilisation data collected via SNMP.
• Compliance and auditing — Verifying device configurations and software versions across a managed fleet.

Geographic Market Distribution

SNMP monitoring tool adoption is global, reflecting the ubiquity of enterprise networking. The market research report identified the following major regions as relevant to the analysis:

• North America (United States, Canada, Mexico)
• Europe (Germany, UK, France, Russia, Italy, Turkey, and others)
• Asia-Pacific (China, Japan, India, Australia, South Korea, Vietnam, Malaysia, Thailand, Philippines, Indonesia)
• South America (Brazil and others)
• Middle East and Africa (GCC countries and Egypt)

North America and Europe have historically represented the largest markets for enterprise network monitoring software, driven by large financial services, healthcare, and telecommunications sectors with complex infrastructure requirements.

Evaluating an SNMP Monitoring Tool: Key Criteria

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

• MIB support and compiler — Can the tool import vendor-specific MIBs and translate OIDs into human-readable names?
• SNMPv3 support — Is SNMPv3 with AES encryption fully supported, not just documented?
• Trap handling — Can the tool receive, parse, deduplicate, and alert on SNMP traps in addition to active polling?
• Scalability — How many devices and polling intervals can the system handle before performance degrades? Distributed pollers matter at scale.
• Discovery — Does the tool auto-discover devices using SNMP, CDP, LLDP, or network range scanning?
• Integration — Does it integrate with alerting systems (PagerDuty, Opsgenie), ITSM platforms (ServiceNow, Jira), or observability stacks (Grafana, Prometheus)?
• Licensing model — Per-device, per-interface, per-sensor, or subscription-based pricing has significant budget implications at enterprise scale.

SNMP in the Context of Modern Observability

SNMP coexists with — rather than being replaced by — modern observability tooling. Streaming telemetry protocols (gNMI/gRPC) offer lower latency and better scalability for high-end platforms, but SNMP remains the only supported management interface for a large proportion of installed network equipment. Most mature monitoring platforms support both, allowing teams to use streaming telemetry where available and fall back to SNMP elsewhere.

The practical approach for most organisations is to treat SNMP as a required baseline capability, layer modern telemetry on top for supported devices, and centralise all data into a unified observability platform.

Researchers Len Bass, Dr. Ingo Weber, and Dr. Liming Zhu have offered a widely cited academic definition: DevOps is “a set of practices intended to reduce the time between committing a change to a system and the change being placed into normal production while ensuring high quality.”

The Problem DevOps Solves

To understand what DevOps changes, it helps to understand the friction it replaces. In a traditional software organisation, developers and operations engineers work in separate silos with different priorities, tools, and mental models of the system.

The Developer’s Experience Without DevOps

Developers write code in a local or shared development environment. Once a batch of changes is ready, it gets handed off to operations for deployment — a process that might happen only once or twice a month. The developer moves on to the next feature while that batch sits in a queue.

When the code finally reaches production, it can behave differently than it did in development. Subtle environment differences — configuration, library versions, network rules — cause errors. The developer must now context-switch back to code they wrote weeks ago to diagnose and fix a problem they can barely remember writing.

The Operations Team’s Experience Without DevOps

The operations team owns the production environment. They manage servers, maintain uptime, and are ultimately accountable when something breaks in front of customers. Periodically, they receive a large bundle of new code from developers and must integrate it into a live system with as little disruption as possible.

Because deployments are infrequent and each one is large, they carry significant risk. Operations engineers often spend considerable time coaxing new code to behave correctly in an environment they maintain but did not design the code for. If errors follow a deployment, it is the operations team that must respond — even when root cause lies in code they did not write.

This structural tension — developers optimising for speed, operations optimising for stability — is the core problem DevOps addresses.

How a DevOps Team Works Differently

DevOps removes the handoff wall. Developers and operations engineers collaborate throughout the entire development lifecycle: design, coding, testing, deployment, and post-release monitoring. The key shifts are:

• Smaller, more frequent releases. Instead of batching weeks of work into a single deployment, teams ship small increments of code continuously. Smaller changes are easier to test, easier to debug, and easier to roll back.
• Automation first. Manual steps — building, testing, provisioning infrastructure, deploying code — are automated wherever possible. This reduces human error and makes the pipeline repeatable and auditable.
• Infrastructure as Code (IaC). Infrastructure is defined in version-controlled configuration files rather than configured manually. Tools like Terraform, Ansible, and Puppet make environments reproducible, closing the gap between development and production.
• Continuous monitoring. Application performance, error rates, and user experience are measured in near real-time. Both developers and operations engineers are responsible for acting on that data.
• Shared ownership. The team shares responsibility for the full lifecycle of a service, reducing the blame culture that arises from siloed work.

Core DevOps Principles

Several principles underpin the DevOps way of working:

• Continuous Integration (CI): Developers merge code changes into a shared repository frequently. Each merge triggers an automated build and test run, surfacing integration problems early.
• Continuous Delivery (CD): Every change that passes automated tests is automatically prepared for release to production. The decision to deploy can be made at any time.
• Continuous Deployment: An extension of CD where every passing change is automatically deployed to production without manual approval gates.
• Feedback loops: Short, fast feedback loops between production behaviour and developer action are central. Monitoring and alerting tools provide this signal.
• Blameless culture: Post-incident reviews focus on systemic improvements rather than individual blame, encouraging transparency and learning.

A Brief History of DevOps

DevOps did not emerge from a single moment. It evolved from the Agile System Administration and Enterprise Systems Management (ESM) movements that gained momentum in the mid-2000s, as practitioners began questioning why Agile principles applied inside development teams were not extending to operations.

Key milestones include:

• 2008 — Velocity Conference: O’Reilly’s Velocity conference, focused on web performance and operations, became a gathering point for engineers interested in developer-operations collaboration. Talks at the 2008 and 2009 editions helped crystallise the ideas that would become DevOps.
• 2009 — DevOpsDays, Ghent: Agile practitioner and project manager Patrick Debois organised the first DevOpsDays conference in Belgium, giving the movement its name and a dedicated community.
• 2012 — First State of DevOps Report: Alanna Brown at Puppet launched what became an annual industry survey tracking DevOps adoption, practices, and outcomes. Subsequent editions, produced in partnership with DORA (DevOps Research and Assessment), provided data on the business impact of DevOps practices.

Essential DevOps Toolchains

DevOps practices depend on integrated toolchains — sets of tools that automate and connect different stages of the delivery pipeline. The major categories are:

What DevOps Is Not

DevOps is frequently misunderstood. It is not a job title, a specific product, or a team you stand up and declare done. Hiring a “DevOps engineer” or deploying a CI/CD tool does not make an organisation DevOps. The tools support the practices, and the practices require a genuine cultural shift: shared ownership, trust between teams, tolerance for experimentation, and a commitment to learning from failure.

Why DevOps Matters

Organisations that successfully adopt DevOps practices can deploy code more frequently, recover from failures faster, and maintain higher levels of service stability. The underlying reason is structural: by removing handoff delays, automating repetitive work, and closing feedback loops between production behaviour and engineering decisions, teams spend more time on valuable work and less time on rework, incident response, and coordination overhead.

DevOps is not a destination. It is an ongoing discipline — one that rewards teams willing to continuously examine their own processes and improve them.

What Is the DevOps Tools Market?

DevOps is a software delivery philosophy that breaks down the traditional wall between development and operations teams. By combining cultural practices, collaborative workflows, and purpose-built automation tooling, DevOps enables organisations to ship applications faster, with greater reliability and reduced manual overhead.

The DevOps tools market encompasses the platforms and utilities that make this approach practical at scale: source control, continuous integration and delivery (CI/CD) pipelines, configuration management, container orchestration, infrastructure-as-code, monitoring, and collaboration tooling.

Market Size and Growth Projections (2020–2026)

According to the analyst report summarised by the original source, the global DevOps tools market was projected to reach approximately USD 6,660 billion in value and grow at a compound annual growth rate (CAGR) of roughly 14% over the forecast period 2020–2026.

Key demand drivers cited include:

• Accelerating digital transformation initiatives across enterprise sectors
• Growing adoption of cloud-native architectures and microservices
• Rising need to shorten software release cycles while maintaining quality
• Increased investment in automation to reduce operational toil
• Expansion of DevSecOps practices embedding security earlier in the pipeline

Key Vendors in the DevOps Tools Landscape

The report profiled a broad set of vendors operating across different layers of the DevOps toolchain. Notable players include:

Core DevOps Tool Categories

Understanding the market requires mapping vendors to the functional layers of a typical DevOps toolchain:

1. Source Control and Collaboration

Git-based platforms such as GitHub, GitLab, Bitbucket, and Azure Repos form the foundation. Teams use pull requests and branch strategies to manage code changes and enable code review workflows.

2. Continuous Integration and Continuous Delivery (CI/CD)

CI/CD pipelines automate the build, test, and deploy cycle. Tools in this space include Jenkins, GitLab CI, GitHub Actions, CircleCI, Bamboo, and Azure DevOps Pipelines. Shorter feedback loops mean defects are caught earlier and releases happen more frequently with lower risk.

3. Configuration Management and Infrastructure as Code

Ansible, Puppet, Chef, and SaltStack allow teams to define infrastructure state declaratively and enforce it consistently across environments. Terraform and AWS CloudFormation handle provisioning at the cloud infrastructure level.

4. Containerisation and Orchestration

Docker provides a standard container image format and runtime. Kubernetes has become the dominant orchestration layer for deploying, scaling, and managing containerised workloads in production. Managed Kubernetes offerings from AWS, Google Cloud, and Azure have accelerated adoption.

5. Monitoring, Observability, and Alerting

Production visibility tools—including Prometheus, Grafana, Datadog, New Relic, and the Elastic Stack—collect metrics, logs, and traces. Observability practices aim to understand system behaviour from external outputs without requiring prior knowledge of failures.

6. Release Orchestration and Value Stream Management

Enterprise organisations managing complex, multi-team releases use tools such as XebiaLabs (now Digital.ai), CA Release Automation (Broadcom), and similar platforms to coordinate deployments across systems and track the flow of value from idea to production.

Regional Market Breakdown

The analyst report examined both mature and emerging regional markets:

• North America: Historically the largest market, driven by early enterprise cloud adoption, a large pool of DevOps-skilled engineers, and significant investment from major technology vendors headquartered in the region.
• Europe: Strong growth driven by GDPR compliance pressure accelerating automation and audit tooling adoption, alongside cloud migration programmes.
• Asia-Pacific (China, Japan, India, Southeast Asia): Rapidly growing segment as digital-native companies scale and traditional enterprises modernise. India in particular has a large talent pool contributing to both tool adoption and vendor development capacity.

Market Segmentation Dimensions

Analysts typically break the DevOps tools market down along several axes:

• By deployment model: On-premises, cloud-hosted (SaaS), and hybrid
• By organisation size: Small and medium businesses (SMBs) vs. large enterprises
• By industry vertical: Financial services, healthcare, retail, manufacturing, telecom, government
• By tool category: As described in the toolchain layers above

Key Takeaways for DevOps Practitioners

Whether you are evaluating tools or planning a DevOps transformation, a few practical points stand out from this market landscape:

• Consolidation is ongoing. Many vendors listed here have been acquired (XebiaLabs, VersionOne, and CollabNet merged into Digital.ai; SaltStack was acquired by VMware; CA Technologies was acquired by Broadcom). Evaluate vendor stability and roadmap continuity before committing to a platform.
• Open-source tooling dominates adoption. Ansible, Docker, Kubernetes, Prometheus, and Git-based platforms have broad community ecosystems that reduce lock-in risk.
• No single vendor covers the full toolchain. Most organisations operate a curated mix of tools connected through APIs and pipeline integrations rather than a single vendor suite.
• Database DevOps is a growing gap. Tools like DBmaestro address a common bottleneck: database schema changes that are still managed manually while everything else is automated.
• 14% CAGR reflects genuine enterprise demand. Organisations are investing in DevOps tooling not as a cost centre but as a revenue enabler—faster delivery directly correlates with competitive advantage.

Note: Market figures in this article originate from the third-party analyst report cited in the original source (coleofduty.com, May 2020). Readers requiring current market sizing should consult up-to-date research from recognised analyst firms.

The Problem with Static Credentials in DevOps Pipelines

Modern DevOps pipelines rely on dozens of interconnected tools — Jenkins, Terraform, Ansible, Chef, Puppet, Kubernetes — each requiring credentials to authenticate to infrastructure and services. The traditional approach of hardcoding passwords or storing them in disparate, tool-specific vaults creates serious security and operational risks.

A centralized secrets vault solves the sprawl problem by replacing hardcoded credentials with a single API call to an encrypted, access-controlled, audited location. Tools request a secret when they need it and use it only for their specific task. However, even this model carries residual risk: what if the tool itself leaks the secret through improper memory storage, logging, or a misconfigured plugin?

This is the problem dynamic secrets are designed to solve.

What Are Dynamic Secrets?

Dynamic secrets — also called dynamic passwords or ephemeral secrets — are credentials that are generated on demand and automatically expire after a defined time-to-live (TTL). Unlike static secrets, they do not exist until a tool requests them, and they become worthless as soon as their TTL elapses.

Key properties of dynamic secrets:

• Created on demand: A new credential is generated each time a tool authenticates and requests access.
• Short-lived: The TTL is configured in advance; the secret expires automatically without manual rotation or revocation.
• Scoped by policy: Each dynamic secret is tied to a cloud IAM policy that limits what the credential can actually do — for example, only launching an EC2 instance, or only deploying code.
• Low attacker value: Even if a dynamic secret is intercepted or leaked, it is usable only within a narrow authorization scope and for a short window of time.

How Dynamic Secrets Work: An Ansible and AWS Example

The following walkthrough illustrates dynamic secrets in a real DevOps workflow involving Ansible, AWS, and a centralized secrets vault.

Pre-Configuration

Before any automation runs, an administrator configures the secrets vault with two items:

1. A base secret — a long-lived credential that gives the vault itself the authority to request new credentials from AWS on behalf of callers.
2. A dynamic secret definition — a template that specifies an AWS IAM policy (for example, ec2:RunInstances only) and a TTL. At this stage, no actual secret values exist.

Runtime Flow

1. Ansible needs to build an EC2 instance. It authenticates to the secrets vault.
2. The vault receives the request, calls AWS using its base secret, and asks AWS to issue a new ephemeral credential scoped to the pre-defined IAM policy.
3. AWS generates the ephemeral credential and returns it to the vault.
4. The vault passes the ephemeral credential to Ansible.
5. Ansible uses the credential to create the EC2 instance.
6. The TTL expires. The credential is automatically invalid — no rotation job or manual revocation required.

Fine-Grained Scoping Across Tasks

The same base secret can back multiple dynamic secret definitions, each with a different policy and TTL. For example:

• Dynamic secret A — policy: ec2:RunInstances, TTL: 10 minutes. Used by Ansible to build the server.
• Dynamic secret B — policy: deploy code, TTL: 5 minutes. Used by Ansible to push an application to the server it just built.

Breaking a pipeline into discrete secrets with narrow scopes means that compromising one secret gives an attacker only a tiny, time-limited capability — not broad access to the environment.

Cross-Account Access in AWS

Dynamic secrets also support cross-account access patterns. An administrator in a production AWS account can configure an IAM role with appropriate policies and link it to a developer’s account. When the developer’s automation requests the dynamic secret, the vault generates a credential scoped to the production account via that role — without permanently granting the developer account production access.

Why Dynamic Secrets Matter for Cloud Security

Infrastructure-as-a-service platforms — AWS, Microsoft Azure, and Google Cloud Platform — are high-value targets. Stolen or leaked cloud credentials can cause disruptions ranging from service outages to catastrophic data loss. DevOps tools introduce multiple potential leak vectors:

• Secrets written to disk or held in memory longer than necessary
• Secrets captured by logging systems (stdout, debug logs, CI/CD job logs)
• Secrets exposed through plugin vulnerabilities or misconfigurations
• Open-source library dependencies with unknown security posture

Because dynamic secrets are short-lived and narrowly scoped, they significantly reduce the blast radius of any single leak. An attacker who captures an ephemeral credential gains little: the credential expires quickly and cannot be used for actions beyond what the IAM policy permits.

Authentication Methods for a Cloud-Native Secrets Vault

A DevOps secrets vault deployed in the cloud should support the native identity mechanisms of each cloud platform so that tools and services can authenticate without requiring a separate static credential. Thycotic DevOps Secrets Vault, as described in the original source, supported authentication via:

• AWS IAM — authenticate using AWS instance roles or IAM credentials
• Microsoft Azure — authenticate using Azure managed identities
• Google Cloud Platform — authenticate via GCP service accounts, user accounts, Google Compute Engine (GCE) instance metadata, or Google Kubernetes Engine (GKE) service accounts
• Thycotic One — single sign-on with two-factor authentication via TOTP or SMS

Integrations, SDKs, and Certificate Issuance

For a secrets vault to be genuinely useful in a DevOps environment, it must integrate natively with the tools teams already use. As of early 2020, Thycotic DevOps Secrets Vault included integrations and SDKs for:

• CI/CD and orchestration: Jenkins, Kubernetes, Terraform, Ansible
• Configuration management: Chef, Puppet
• SDKs: Java, Go, Python, .NET, Ruby

The vault also supported X.509 certificate issuance. Once a customer’s root or intermediate certificate authority was imported into the vault, the vault could issue signed leaf certificates on demand — extending the same secrets-management model to PKI.

Key Takeaways

• Centralizing secrets management behind a single API-driven vault eliminates hardcoded credentials and credential sprawl across DevOps tools.
• Dynamic secrets add a second layer of protection: credentials that do not exist until needed and expire automatically reduce the value of any leak to near zero.
• Scoping dynamic secrets to narrow IAM policies per pipeline task limits the blast radius of a compromise.
• Cloud-native authentication (AWS IAM, Azure managed identity, GCP service accounts, GKE) removes the need for a separate static credential just to authenticate to the vault itself.
• SDK and integration coverage for common DevOps tools is essential for adoption — secrets management only works if every tool in the pipeline uses it.

What Is the DevOps Platform Market?

The DevOps platform market encompasses the tools, integrated suites, and cloud services that organisations use to plan, build, test, deliver, and monitor software continuously. Rather than stitching together a dozen point tools, many engineering teams now look for cohesive platforms that cover the full software delivery lifecycle — from source control and CI/CD pipelines through to configuration management, container orchestration, and observability.

Demand is driven by several converging pressures: the need to shorten release cycles, the shift to microservices and containers, growing adoption of public cloud infrastructure, and regulatory requirements around auditability and change management. These factors together make the market both large and strategically important for enterprises of all sizes.

Major Vendors in the DevOps Platform Space

A number of established vendors and open-source projects compete across different layers of the DevOps toolchain. The following companies were identified as key players in the original 2020 market report and remain significant participants in the space:

• Chef (now Progress Chef): One of the pioneers of infrastructure-as-code, Chef provides configuration management and compliance automation through its Chef Infra and Chef InSpec products. It is widely used in enterprises with complex, heterogeneous infrastructure.
• Docker Inc.: Docker popularised Linux containers and the image-based packaging model that underpins most modern CI/CD pipelines. Docker Desktop, Docker Hub, and the broader container ecosystem remain central to developer workflows, though orchestration at scale has largely moved to Kubernetes.
• Red Hat / Ansible: Red Hat’s acquisition of Ansible brought agentless automation into the Red Hat portfolio. Ansible Tower (now Ansible Automation Platform) is a leading choice for IT automation, particularly in organisations already invested in the Red Hat ecosystem including OpenShift.
• Atlassian: Atlassian’s suite — Jira, Confluence, Bitbucket, and Jira Service Management — covers planning, source control, and collaboration. While not a deployment platform in itself, Atlassian tools are deeply embedded in the planning and tracking layers of most DevOps toolchains.
• SaltStack (now part of VMware): SaltStack provided event-driven automation and configuration management at scale. Following its acquisition by VMware, its capabilities have been integrated into the VMware vRealize and Aria product lines.
• CA Technologies (now Broadcom): CA Technologies brought enterprise-grade release automation, value stream management, and mainframe DevOps capabilities to the market. After Broadcom’s acquisition, many of these products continue under the Broadcom Software portfolio.

Key Market Segments

DevOps platform offerings are generally segmented along two dimensions: deployment model and functional capability.

By Deployment Model

• SaaS / Cloud-hosted: Fully managed platforms such as GitHub Actions, GitLab.com, and Atlassian Cloud reduce operational overhead and are preferred by teams without dedicated platform engineering resources.
• Self-hosted / On-premises: Required by organisations with strict data residency, compliance, or air-gap requirements. Examples include self-managed GitLab, Jenkins, and Ansible Automation Platform.
• Hybrid: Many enterprises run a mix — cloud-hosted orchestration with on-premises runners or agents connecting to internal infrastructure.

By Functional Capability

• Source control and code review
• Continuous integration and continuous delivery (CI/CD)
• Configuration management and infrastructure-as-code
• Container and Kubernetes management
• Security scanning and compliance (DevSecOps)
• Monitoring, logging, and observability
• Value stream management and planning

Regional Demand Patterns

DevOps platform adoption is genuinely global, though the maturity and drivers differ by region:

• North America leads in both vendor presence and enterprise adoption, driven by large technology companies and financial services firms with sophisticated engineering organisations.
• Europe shows strong adoption with additional complexity around GDPR and data sovereignty, which influences deployment model choices.
• Asia-Pacific is the fastest-growing region by most analyst assessments, propelled by digital transformation initiatives in markets such as India, China, Australia, and Japan.
• Latin America and Africa represent emerging markets where cloud-first strategies are accelerating DevOps adoption without the legacy infrastructure baggage present in older markets.

Market Drivers and Growth Factors

Several structural forces continue to expand the DevOps platform market:

• Cloud-native adoption: The migration of workloads to AWS, Azure, and Google Cloud naturally pulls teams toward cloud-native CI/CD and infrastructure automation tools.
• Container and Kubernetes growth: The widespread standardisation on Kubernetes for production workloads creates demand for integrated deployment, security, and observability tooling.
• Security integration (DevSecOps): Organisations are shifting security testing left into the pipeline, driving demand for tools that embed SAST, DAST, dependency scanning, and secrets management into existing DevOps workflows.
• Platform engineering as a discipline: Internal developer platform (IDP) thinking is pushing organisations to consolidate toolchains, creating demand for integrated or interoperable platform suites over fragmented point tools.
• Regulatory compliance requirements: Industries such as financial services, healthcare, and government are formalising software delivery audit trails, change management, and policy-as-code — all of which DevOps platforms increasingly support natively.

Challenges and Restraints

Growth in the market is not without friction. Common challenges include:

• Toolchain fragmentation: Many organisations have accumulated dozens of DevOps tools over time, making consolidation politically and technically difficult.
• Skills gaps: Effective use of advanced automation and platform tooling requires skills that remain in short supply in most labour markets.
• Vendor lock-in concerns: Organisations are wary of deep dependency on a single platform vendor, particularly as pricing and licensing models evolve — a concern that open-source alternatives directly address.
• Cultural resistance: DevOps is as much an organisational change as a technical one. Tool adoption without the corresponding cultural and process change frequently fails to deliver expected outcomes.

Competitive Landscape Considerations

The competitive dynamics in this market have shifted significantly since 2020. Microsoft’s GitHub has become a dominant force through GitHub Actions and Copilot. GitLab has matured into a comprehensive DevSecOps platform. HashiCorp’s infrastructure tooling (Terraform, Vault) — now under IBM/HashiCorp following acquisition activity — occupies a critical position in the infrastructure-as-code layer. Meanwhile, cloud providers themselves (AWS CodePipeline, Azure DevOps, Google Cloud Build) compete directly with independent platform vendors.

The overall trajectory is toward consolidation: fewer, broader platforms that cover more of the lifecycle, supplemented by specialist tools in areas such as security and observability where depth matters more than breadth.

Summary

The DevOps platform market remains one of the more dynamic segments of the enterprise software industry. Organisations evaluating platforms should look beyond feature lists to assess integration depth, community health, licensing model sustainability, and the vendor’s roadmap around AI-assisted development and security. The vendors profiled here — Chef, Docker, Red Hat Ansible, Atlassian, SaltStack, and CA Technologies — represent a cross-section of the market as it stood in 2020; the landscape has continued to evolve through acquisitions, open-source community growth, and cloud-native platform consolidation.

For current market sizing and forecast data, consult analyst firms such as Gartner, Forrester, or IDC, which publish regularly updated DevOps and value stream management market guides.