Managing dependencies in software development is a crucial part of the development process. Dependency management tools help automate the management of external libraries and components that your project relies on, ensuring smooth integration, version control, and updates. In this post, we explore the Top 21 Dependency Management Tools and their major features, which can help streamline the process and enhance your software development workflow.

1. Apache Maven

Major Features:

• Centralized Dependency Management: Maven allows developers to define all dependencies in a Project Object Model (POM) file, ensuring a central management approach.
• Repository System: It integrates with Maven Central Repository to retrieve libraries and plugins automatically.
• Transitive Dependencies: Handles transitive dependencies (i.e., dependencies of your dependencies) automatically, eliminating manual management.
• Build Automation: Beyond dependency management, Maven also automates the build process, including compiling, testing, and packaging.

2. Gradle

Major Features:

• Flexibility: Gradle offers the ability to define dependencies with both Maven and Ivy repositories, giving flexibility in choosing the repository format.
• Incremental Builds: Gradle can automatically skip tasks that have not changed, speeding up build times and optimizing dependency resolution.
• Multi-Project Dependency Management: Ideal for multi-project builds, Gradle allows dependencies to be shared and resolved across projects.
• Kotlin DSL Support: Gradle allows for Kotlin-based scripting, which provides a modern alternative to the traditional Groovy syntax.

3. npm (Node Package Manager)

Major Features:

• JavaScript and Node.js Dependency Management: npm is the default package manager for Node.js and JavaScript projects.
• Centralized Package Registry: It connects to the npm registry, which hosts a vast collection of JavaScript libraries and tools.
• Version Control: npm handles different versions of dependencies efficiently, allowing developers to specify version ranges.
• Package Scripts: Developers can define custom scripts for building, testing, and deploying their projects, all integrated with npm.

4. Yarn

Major Features:

• Faster Dependency Resolution: Yarn is faster than npm due to its offline caching and parallelized dependency installation.
• Lock Files: Yarn generates a yarn.lock file, which ensures that dependencies are installed with exactly the same version across all environments.
• Deterministic Builds: Ensures that dependencies are resolved and installed in a consistent manner across all developers and CI/CD pipelines.
• Workspaces: Yarn workspaces help manage multiple packages within a project, optimizing dependency management in monorepos.

5. Pip (Python)

Major Features:

• Python Package Management: Pip is the default package manager for Python and is used to install and manage dependencies.
• Integration with PyPI: Pip integrates seamlessly with the Python Package Index (PyPI), where most of the Python libraries are hosted.
• Requirements Files: It allows developers to list project dependencies in a requirements.txt file, simplifying installations.
• Version Pinning: Supports version pinning, allowing developers to lock specific versions of libraries to avoid compatibility issues.

6. Composer (PHP)

Major Features:

• PHP Dependency Management: Composer is the dependency management tool for PHP, and it simplifies the installation and management of PHP packages.
• Composer.json: Dependencies are defined in the composer.json file, and Composer ensures they are downloaded and installed accordingly.
• Autoloading: Composer provides automatic autoloading for installed libraries, eliminating the need for manual file includes.
• Version Control: Composer manages version constraints for libraries, ensuring compatibility across different versions.

7. Bundler (Ruby)

Major Features:

• Ruby Dependency Management: Bundler is the official tool for managing dependencies in Ruby projects.
• Gemfile and Gemfile.lock: Bundler uses a Gemfile to specify dependencies and a Gemfile.lock to lock the exact versions used in development.
• Environment Isolation: Bundler allows for isolated environments, ensuring dependencies are consistent across different machines and platforms.
• Optimized for RubyGems: It integrates seamlessly with the RubyGems package manager, ensuring all Ruby libraries are easily installed and updated.

8. NuGet

Major Features:

• .NET Dependency Management: NuGet is the official package manager for .NET applications, supporting dependency management for both libraries and tools.
• Integrated into Visual Studio: NuGet is deeply integrated into Visual Studio, providing a streamlined experience for developers working with .NET.
• Versioning and Updates: NuGet supports versioning and dependency resolution, ensuring that the right versions of libraries are used in your project.
• Private Repositories: Developers can host private NuGet repositories for internal packages, enabling better control over dependencies.

9. Ivy

Major Features:

• Ant Integration: Ivy is a dependency management tool designed to work seamlessly with Apache Ant, helping automate build processes.
• Flexible Repository Support: Ivy supports both Maven and Ivy repositories, providing flexibility in choosing where to fetch dependencies from.
• Transitive Dependency Handling: Like Maven, Ivy automatically manages transitive dependencies and handles complex dependency trees.
• Customizable: Ivy allows developers to customize dependency resolution logic, making it highly adaptable to different project structures.

10. Bower

Major Features:

• Front-End Dependency Management: Bower is a package manager for front-end development, focusing on managing dependencies like JavaScript libraries and CSS files.
• Dependency Resolution: Bower helps manage the installation of front-end dependencies, including resolving version conflicts and ensuring the proper files are included in projects.
• Works with Git Repositories: Bower allows dependencies to be installed directly from Git repositories, making it easy to manage libraries hosted outside package registries.
• Multi-Project Management: Bower supports managing dependencies across multiple front-end projects, making it a great choice for large-scale web applications.

11. Conan

Major Features:

• C/C++ Package Management: Conan is a package manager specifically designed for C and C++ projects, helping manage libraries and dependencies.
• Remote and Local Repositories: It supports both remote repositories and local caches for dependency management, enabling flexibility in sourcing packages.
• Cross-Platform Support: Conan supports Windows, Linux, and macOS, making it ideal for cross-platform C/C++ development.
• Versioning and Flexibility: Conan provides flexibility with version constraints and enables easy package distribution among teams.

12. Spack

Major Features:

• High-Performance Computing (HPC) Dependency Management: Spack is designed to manage dependencies in HPC environments and scientific computing applications.
• Multiple Versions of Dependencies: Spack enables the installation of multiple versions of dependencies, which is especially useful for scientific research environments.
• Customizable Build Processes: It allows you to define custom build processes for dependencies, making it versatile for complex software stacks.
• Cross-Platform and Multicore Support: Spack is designed to support various systems, including Linux and macOS, with optimizations for multicore builds.

13. SBT (Scala Build Tool)

Major Features:

• Scala and Java Dependency Management: SBT is the default build tool for Scala and integrates well with Java projects.
• Incremental Compilation: SBT offers incremental compilation to speed up builds by compiling only the modified parts of the project.
• Flexible Dependency Resolution: SBT uses Maven repositories for fetching dependencies and supports fine-grained version control.
• Plugins for Scala Projects: It offers several plugins for handling common tasks such as testing, packaging, and deployment.

14. Artifactory

Major Features:

• Universal Repository Manager: Artifactory is a powerful repository manager that integrates with a variety of dependency management tools like Maven, Gradle, and Ivy.
• Multi-Repository Support: It supports both local and remote repositories, enabling you to manage dependencies from different sources in one place.
• Advanced Metadata Management: Artifactory offers advanced metadata management, allowing you to track and search through your dependencies with detailed information.
• CI/CD Integration: It integrates with popular CI/CD tools like Jenkins, Bamboo, and TeamCity for automated dependency management in build pipelines.

15. Dependency-Check

Major Features:

• Automated Dependency Scanning: Dependency-Check is a tool for identifying known vulnerabilities in the libraries your project depends on.
• Integration with CI/CD: It integrates easily with CI/CD pipelines, allowing you to automatically check for vulnerabilities during the build process.
• Vulnerability Reports: Provides detailed vulnerability reports based on known security threats in public databases.
• Supports Multiple Build Tools: Works with tools like Maven, Gradle, and Ivy to provide a comprehensive vulnerability check for your dependencies.

16. Pipenv

Major Features:

• Python Dependency Management: Pipenv is a dependency manager for Python that automatically creates and manages a Pipfile for project dependencies.
• Virtual Environments: Pipenv handles virtual environments automatically, ensuring that dependencies are isolated and compatible.
• Enhanced Security: It offers security checks for dependencies, making it easier to detect vulnerabilities in installed libraries.
• Version Locking: The Pipfile.lock file locks the versions of all dependencies, ensuring consistency across different environments.

17. Bundler

Major Features:

• Ruby Dependency Management: Bundler is the official dependency manager for Ruby applications.
• Gemfile and Gemfile.lock: Dependencies are managed via the Gemfile, and Bundler ensures the same versions are used across environments by creating a Gemfile.lock.
• Automatic Dependency Resolution: Bundler resolves and installs required dependencies, ensuring compatibility between them.
• Ecosystem Integration: Bundler integrates seamlessly with RubyGems, the default Ruby package manager.

18. Pip (Python)

Major Features:

• Python Package Management: Pip is the default package manager for Python and installs dependencies from the Python Package Index (PyPI).
• Requirements Files: Dependencies can be listed in a requirements.txt file, making it easier to install all necessary libraries for a project.
• Version Control: Pip allows for version pinning to avoid issues with incompatible library versions.
• Virtual Environments: Works in conjunction with tools like virtualenv to manage project-specific environments and dependencies.

19. Carthage

Major Features:

• iOS and macOS Dependency Management: Carthage is a dependency manager for iOS and macOS projects that focuses on simplicity.
• No Build Automation: Unlike CocoaPods, Carthage does not automate builds, allowing developers to manually control the process and more flexibility.
• Pre-built Binaries: Carthage can fetch pre-built binaries for dependencies, saving time during the build process.
• Flexible Integration: Works well with Xcode, providing a more flexible alternative to CocoaPods for managing iOS dependencies.

20. CocoaPods

Major Features:

• Objective-C and Swift Dependency Management: CocoaPods is a dependency manager for iOS, macOS, and watchOS applications.
• Integration with Xcode: Seamlessly integrates with Xcode for easy management of dependencies in iOS and macOS projects.
• Centralized Repository: CocoaPods uses a central repository to host open-source libraries, ensuring easy access to commonly used components.
• Version Control: Manages library versions, ensuring compatibility and preventing version conflicts.

21. Zigzag

Major Features:

• Go Dependency Management: Zigzag is a dependency management tool for Go programming language, designed to simplify library and module management.
• Version Constraints: Allows you to lock dependencies to specific versions to ensure compatibility.
• Fast Dependency Resolution: Zigzag ensures quick dependency resolution, saving time in the build process.
• Minimal Configuration: It works with minimal configuration, allowing developers to quickly get started with dependency management.

This post provides a comprehensive overview of Top 21 Dependency Management Tools that can help streamline the process of managing dependencies in your projects. Let me know if you need more tools or specific details!

Both DevOps and Security Information and Event Management (SIEM) play crucial roles in modern IT and security operations, but they focus on different aspects of system management and operations. DevOps is a set of practices aimed at improving collaboration between development and operations teams to streamline software development and deployment, while SIEM is a solution focused on security monitoring, incident response, and compliance management through the collection and analysis of security-related data.

In this post, we will explore the key differences between DevOps and SIEM, detailing their major features, and goals, and how they serve distinct yet complementary purposes in an organization’s IT and security landscape.

1. Definition and Scope

DevOps:

• Collaboration and Automation:
  • DevOps is a cultural and technical approach designed to improve collaboration between development and IT operations teams. It emphasizes automation, continuous integration, and continuous delivery (CI/CD) to accelerate the software development lifecycle.
• Focus on Software Delivery:
  • The primary goal of DevOps is to streamline the development, testing, and deployment of software. By automating repetitive tasks and promoting collaboration, DevOps helps reduce deployment times and increase the frequency of software releases.
• End-to-End Process:
  • DevOps covers the entire software development lifecycle, from planning and development to testing, deployment, and ongoing monitoring and maintenance.

SIEM:

• Security Monitoring and Incident Management:
  • SIEM refers to a security management approach that provides real-time analysis of security alerts generated by applications, hardware, and other infrastructure components. It focuses on aggregating and analyzing log data to identify potential security threats.
• Centralized Security Data:
  • SIEM systems aggregate log and event data from various sources, such as firewalls, intrusion detection systems (IDS), and servers, to provide a centralized view of an organization’s security posture.
• Security Operations Center (SOC) Integration:
  • SIEM tools are typically integrated with Security Operations Centers (SOCs) to help security analysts monitor, investigate, and respond to security incidents quickly and effectively.

2. Objectives and Goals

DevOps:

• Accelerating Software Delivery:
  • DevOps aims to shorten the development cycle, allowing teams to develop, test, and deploy software faster and more reliably. This is achieved through continuous integration, automated testing, and automated deployments.
• Improved Collaboration:
  • DevOps fosters a culture of collaboration between development, IT operations, and other stakeholders. By aligning goals and workflows, DevOps reduces friction between teams, ensuring that all parties are focused on delivering high-quality software.
• Scalability and Automation:
  • DevOps practices, such as infrastructure automation and configuration management, ensure that systems can scale efficiently and without downtime. Tools like Terraform and Docker enable automation at every stage of the lifecycle.

SIEM:

• Real-Time Threat Detection:
  • The primary goal of SIEM is to provide continuous monitoring of security events to detect and respond to threats in real-time. SIEM systems help organizations identify suspicious activities, data breaches, and vulnerabilities before they escalate.
• Compliance and Auditing:
  • SIEM systems are also used to ensure compliance with regulatory requirements, such as GDPR, HIPAA, or PCI-DSS. They provide detailed logging and reporting capabilities to help organizations meet auditing and compliance standards.
• Incident Response and Forensics:
  • SIEM tools provide valuable insights that aid in security incident response and forensics. By analyzing security data and logs, SIEM systems help teams understand the nature of incidents, trace their origins, and mitigate their impact.

3. Tools and Technologies

DevOps:

• CI/CD Tools:
  • DevOps heavily relies on continuous integration and continuous delivery tools such as Jenkins, GitLab, Travis CI, and CircleCI to automate code integration, testing, and deployment.
• Infrastructure Automation:
  • DevOps uses tools like Terraform, Ansible, Chef, and Puppet for automating infrastructure provisioning, configuration management, and deployment.
• Monitoring and Logging:
  • DevOps practices often include monitoring and logging tools like Prometheus, Grafana, and ELK Stack to track application performance, system health, and overall infrastructure reliability.

SIEM:

• Log Aggregation and Analysis:
  • SIEM tools aggregate logs and event data from various sources for analysis. Common SIEM platforms include Splunk, IBM QRadar, ArcSight, and SolarWinds.
• Threat Detection and Analysis:
  • SIEM platforms are equipped with advanced algorithms and analytics to detect security incidents. They use techniques like correlation rules, machine learning, and pattern recognition to identify unusual behavior in security events.
• Incident Management:
  • SIEM platforms often integrate with incident management tools like ServiceNow or PagerDuty to provide streamlined workflows for responding to security incidents, assigning tasks, and tracking resolutions.

4. Collaboration and Roles

DevOps:

• Shared Responsibility:
  • DevOps promotes shared responsibility between development, operations, security, and other teams. Everyone involved in the software lifecycle, from developers to operations personnel, works together to ensure the software is delivered and maintained efficiently.
• Cross-Functional Teams:
  • DevOps fosters the creation of cross-functional teams that collaborate on code development, testing, deployment, and monitoring. This improves communication and speeds up problem resolution.
• Automation and Feedback Loops:
  • Automation plays a key role in DevOps, ensuring that repetitive tasks are handled automatically. Feedback loops, from testing and staging environments to production monitoring, help drive continuous improvement.

SIEM:

• Security Analysts and Operations Teams:
  • SIEM is typically used by security analysts, SOC teams, and incident responders who are responsible for monitoring and investigating security incidents. These teams rely on the data collected by SIEM platforms to detect, assess, and respond to potential threats.
• Collaboration Between IT and Security:
  • While DevOps promotes collaboration between developers and operations teams, SIEM requires collaboration between IT operations and security teams. These teams must work together to interpret security data and respond to incidents.
• Security and Compliance Roles:
  • SIEM tools also support roles that focus on security compliance and auditing. These teams use SIEM reports and logs to ensure that the organization adheres to security standards and regulatory requirements.

5. Impact on Development and Operations

DevOps:

• Faster Time-to-Market:
  • DevOps enables faster time-to-market by automating the software delivery pipeline. This leads to more frequent releases and faster feedback, which accelerates the development process and increases business agility.
• Reliability and Stability:
  • DevOps practices such as automated testing, CI/CD pipelines, and continuous monitoring ensure that software is stable and reliable, even during frequent updates or scaling operations.
• Efficiency and Cost Reduction:
  • By automating manual tasks and optimizing workflows, DevOps helps reduce operational costs and improve resource utilization. The automation of deployment and infrastructure management also minimizes downtime and operational overhead.

SIEM:

• Enhanced Security Posture:
  • SIEM improves an organization’s security posture by providing real-time visibility into security threats and vulnerabilities. It helps prevent data breaches and cyberattacks by detecting malicious activities early.
• Proactive Threat Management:
  • SIEM enables teams to take a proactive approach to security. Instead of reacting to incidents after they happen, SIEM systems help identify threats in real-time, enabling rapid response and minimizing damage.
• Regulatory Compliance and Risk Management:
  • SIEM plays a crucial role in managing compliance and reducing risk by providing the necessary logs, alerts, and reports to satisfy regulatory requirements. It also helps organizations identify and mitigate risks before they escalate.

6. Integration and Use Cases

DevOps:

• Software Development Lifecycle:
  • DevOps is widely used in environments where software needs to be developed, tested, and deployed rapidly. It is commonly used for web applications, mobile applications, and microservices architectures.
• Cloud and Hybrid Environments:
  • DevOps integrates well with cloud-based infrastructure and hybrid environments, where scalable and flexible resources are needed to support dynamic workloads.
• Continuous Monitoring and Improvement:
  • DevOps ensures that applications are continuously monitored, and performance issues are quickly detected and addressed, leading to continuous improvement.

SIEM:

• Security Operations and Incident Response:
  • SIEM is used primarily in security operations to monitor networks, systems, and applications for suspicious activities and potential threats. It is critical for incident detection, response, and forensics.
• Compliance and Auditing:
  • SIEM tools are crucial for industries requiring strict security and compliance standards, such as healthcare, finance, and government sectors.
• Data Breach Prevention:
  • SIEM systems are widely used to detect and prevent data breaches by monitoring system logs and correlating data to identify potential vulnerabilities or unauthorized access.

DevOps vs SIEM

In conclusion, while DevOps and SIEM serve different purposes, they complement each other. DevOps focuses on improving the speed and reliability of software delivery through automation, collaboration, and continuous improvement. In contrast, SIEM focuses on the security of systems by providing real-time monitoring, threat detection, and incident response capabilities.

Both DevOps and SIEM are essential for modern IT and security operations. By integrating both practices, organizations can ensure faster, more secure software delivery while maintaining a strong security posture and compliance with industry regulations.

Columbus, OH, June 25, 2021 –(PR.com)– Today, Proven Optics LLC, a practitioner-founded software and services company, announced the Proven Optics Enterprise Budgeting & Forecasting Application and the ITFM Cost Modeling Application from its Financial Management Application Suite are now certified as part of the ServiceNow Built on Now Program. This new Application Suite combines the platform native capabilities with over twenty years of Technology Business Management (TBM) practitioner experience to bring a modern approach to financial management. These solutions have met the high standards of the ServiceNow Built on Now Program designed to recognize partners with proven ServiceNow expertise that creates value for customers across industries.

The Financial Management Application Suite combines an industry agnostic experience with digital workflows to evolve the end user, financial manager, and leadership user experience. The Enterprise Budgeting & Forecasting Application manages the annual budgeting process, monthly forecasting, and actuals monitoring on the ServiceNow platform. The ITFM Cost Modeling Application has service-based costing that enables next generation ITFM Cost Modeling for IT leaders to drive strategic decision-making capabilities and better business outcomes. Accompanying the Cost Modeling Application is an application that facilitates customer invoicing and chargeback of the different IT services customers are consuming in the cost model.

“Building on the Now Platform created easy accessibility for our customers to onboard into these applications and completely divorce themselves from 90% of the technical challenges that come from implementing a standalone point solution,” said William Miller, Founding Partner of Proven Optics.

Leveraging the Now Platform’s native functionality, these capabilities have redefined what ease-of-use means for the stakeholder. Features like workflow automation, CMDB integrations, and automatic allocation tables eliminate data maintenance and clean up across multiple teams and drives the focus towards outcomes and analysis for leadership.

You can find the Proven Optics Enterprise Budgeting & Forecasting Application and the Proven Optics ITFM Cost Modeling Application on the ServiceNow store today. Public Sector versions of these Applications are also available.

The ServiceNow Built on Now program empowers partners to build, test, certify, distribute and sell applications for the Now Platform. Built on Now-designated solutions deliver Now Certified digital workflows for the Now Platform, at scale, through the ServiceNow Store, OEM, and Service Provider (SP) channels.

Proven Optics is a software and services company that focuses on one thing: Financial Management. We help clients in both IT and Finance organizations implement financial management toolsets on SaaS platforms that leverage our 20+ years of practitioner experience and 100+ Commercial & Federal implementations. Our solutions enable financial management modernization to provide IT & Finance leaders with the necessary analytics and insights to make better business decisions. For information or demonstration of our products, please contact Ben Perkins at ben.perkins@provenoptics.com.

ServiceNow, the ServiceNow logo, Now, Now Platform, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries.

The latest research report on Change and Configuration Management Software market intends to provide opportunities to organizations operating in this industry through a detailed analysis of historical data along with the latest developments. The report outlines the top-winning strategies of the leading players, as prevailing trends, and major prospects.

The report meticulously describes the growth catalysts and restraints that will influence the business dynamics over 2021-2026 It also provides actionable insights into the growth potential of the sub-markets over the estimate time frame. Moreover, it analyses the effect of COVID-19 pandemic across the various regional markets to impart a deeper understanding of the changing landscape to stakeholders.

Product terrain

Product gamut of the Change and Configuration Management Software market constitutes Cloud-based CCMS and On-premises CCMS.
Revenue garnered and market share grabbed by each product segment
Estimated growth rate of each product type over the analysis timeframe
Application gamut

The application scope of the Change and Configuration Management Software market is divided into Healthcare & Life Science , Government & Public Sector , Telecom & IT , Retail & Consumer Packaged Goods , Others , ,By Region , North America , United States , Canada , Europe , Germany , France , U.K. , Italy , Russia , Nordic , Rest of Europe and Asia-Pa.
Insights pertaining to the product demand share and market share held by each application segment.
Growth rate of the application segments over the estimated timeframe
Regional landscape

Regional bifurcation of the Change and Configuration Management Software market comprises North America, Europe, China, Japan, Southeast Asia, India and Other Regions.
Total sales recorded, and revenue amassed by each region
Yearly growth rate of each region during 2021-2026
Competitive arena

Leading companies in the Change and Configuration Management Software market size are HPE IBM Microsoft Oracle VMware BMC Software Broadcom Computer Sciences Corporation eG Innovations Oracle VMware LANDesk Software SAP Serena Software.
Market concentration ratio assessment
Company product portfolio, with specifications and top applications
Important metrics like pricing model, returns, sales graph, and market share of each company
Key development, including comprising of mergers, acquisitions, and expansion plans
In conclusion, the Change and Configuration Management Software market size has been examined deeply through multiple segmentations, and further extends through sales channel and supply chain analysis, which comprises of critical data regarding raw materials suppliers, distributors, and buyers in the industry.

Some of the key questions answered in this report:

What will the market growth rate, growth momentum, or acceleration market carry during the forecast period?

Which are the key factors driving the Change and Configuration Management Software market?

What was the size of the emerging Change and Configuration Management Software market by value in 2020?

What will be the size of the emerging Change and Configuration Management Software market in 2026?

Which region is expected to hold the highest market share in the Change and Configuration Management Software market?

What trends, challenges, and barriers will impact the development and sizing of the Global Change and Configuration Management Software market?

What is the sales volume, revenue, and price analysis of top manufacturers of the Change and Configuration Management Software market?

What are the Change and Configuration Management Software market opportunities and threats faced by the vendors in the global Change and Configuration Management Software Industry?

Shipa Corp., a Kubernetes application development and management platform, today announced the launch of Shipa Cloud that will assist developers, DevOps teams and platform engineers with the management and support of cloud-native applications.

Shipa Cloud provides a secure developer-centric platform for managing operating applications on Kubernetes. This includes the automatic creation and deployment of all objects.

It operates within the application layer and ensures that developers can observe the app’s entire context without interacting with infrastructure or tinkering with Kubernetes under the hood. As a result, the developers and engineers involved in the process do not need Kubernetes expertise.

“Kubernetes is a powerful and requisite tool for modern application development, but for too many enterprises now leveraging it, it remains frustratingly complex to manage,” said Bruno Andrade, chief executive of Shipa. “We launched Shipa in 2020 to take many of those infrastructure tasks off developers’ plates.”

Shipa Cloud features and benefits include the elimination of existing YAML and Helm charting, post-deployment observability, easy setup and governance and out-of-the-box integration with many cloud-native tools.

Upon installing Shipa Cloud, DevOps teams no longer need to update YAML files constantly and maintain policies for automated governance. The company says it will do that itself to deploy applications, so teams can stay in touch with Kubernetes environments through the interface.

Once deployed, Ship Cloud provides in-depth observability across all applications for statuses, objects, dependencies and network policies. It also connects with numerous pre-built connections into existing management tools for application lifecycle history and version management.

Shipa Cloud also allows DevOps teams to set policies for governance easily– for example, policies can be applied across the entire application stack. Once deployed, it can apply to network security, user roles, resource consumption and much more.

“We enable developers to focus on application deployment and management, while also empowering DevOps to set up the control and compliance policies they require,” said Andrade.

The platform also integrates with numerous cloud-native tools popular on the market such as Vault by HashiCorp Inc., Datadog Inc., JFrog Ltd., Circle Internet Services Inc., Traefik Labs and Istio.

In 2011, the Center for Devices and Radiological Health (CDRH) initiated the Case for Quality, which provided guidance on how software validation processes can be improved and streamlined for the medical device, pharmaceutical, and biotech industries. By refocusing on patient and product safety, quality assurance, and data integrity, some suggest that validation documentation can be reduced (between 20% and 40%, in my experience) by applying automated testing and deployment. The benefits are accurate code, faster development processes, and reduced validation documentation.

This article is part one of a three-part series and continues the discussion on computer software assurance (CSA), introduces new technologies and methods to achieve continuous software development, provides insight into new standards (e.g., ISO 9001 and ISO 13485-2016), and concludes with a few good reasons to join the growing number of medical device, pharma, and biotech companies with software specialists (or companies that work with software development organizations) who are creating and/or using test automation tools and applying them throughout the software development life cycle (SDLC) phases: inception, design, implementation, maintenance and monitoring, audit, and disposal.

As we await FDA’s communication on the CSA guidance, we have an opportunity to reevaluate the phases of the SDLC and start to think about using new software development methods, such as a combination of artificial intelligence (AI) and adaptive machine language (ML) to provide human-like instructions for automated testing. Challenges include how to evaluate your SDLC phases and make the transition to continuous test automation. What is most puzzling to many is the impact of making this transition from traditional computer system validation (CSV), effectively and efficiently, to a continuous validation life cycle, while applying the tenets of CSA: critical thinking, risk management, patient and product safety, quality assurance, and data integrity.

ISO Standards Address Risk Management
For those in the medical device industry, your software development team (or your software supplier that you work with) are required to comply with medical device regulations and standards, such as ISPE GAMP 5, ISO 9001, and ISO 13485-2016 – Medical Devices. The regulations and standards include a risk-based assessment (RBA) for all computerized software systems. ISO 9001 requires this assessment during the initial phase of the SDLC; ISO 13485-2016, however, requires that a risk-based assessment be updated at every stage of the SDLC to determine the level of risk and the validation and/or change control actions required to be compliant.

Applying the Agile methodology enables you to find opportunities to improve, implement, and comply with the regulations and standards since it uses an iterative approach to ensure quality: continuous code reviews, continuous testing, continuous deployment, continuous monitoring and maintenance, and continuous audit and disposal. Many software development organizations are already performing automated testing and updating their SDLC. Agile testing methods, such as behavior-driven development (BDD), test-driven development (TDD), and acceptance test-driven development (ATDD), are all different approaches to validating code and may be used for automated testing. With the Agile method and progress in development of intelligent technologies, manual testing and/or unscripted testing for low-risk features may become obsolete.

Information Technology Alignment With Software Engineering
Intelligent systems require IT and DevOps personnel, along with software developers, programmers, and software engineers, to acquire new skills and knowledge while applying the principles of software engineering. The ability to get back to basics and skills in software engineering principles, mathematics, and machine language will continue to be highly desired. Making the transition to continuous validation and continuous testing will not be an easy task, especially for mature companies that have been performing traditional validation since 2003 or earlier. Typically, the quality organization has been responsible for ensuring that the software application(s) are compliant and meet all required regulations for software validation. The process seemed straightforward: inception, design (analyze) implementation (build, test, deploy), maintenance and monitoring, audit, and disposal.

Quality assurance’s (QA) role was to oversee the validation effort by reviewing all computer system validation processes and documentation to ensure that they followed the company’s policies and standard operating procedures (SOPs) for compliance and met the associated regulations and standards. Deviations were documented, errors were corrected, and final documentation was reviewed, approved, and stored following 21 CFR Part 11 regulations. With continuous life cycle management for software development, QA’s focus will be on patient and product safety rather than manual testing and documentation, which will be replaced by test automation to enable continuous validation.

Opportunities For Continuous Life Cycle Management
By applying the concept of continuous life cycle management for software development, advantages such as the ability to address risk (critical, high, medium, etc.) during each stage of the development process are feasible. Performing iterative code reviews and automated testing enables early detection of errors, resulting in error-free code that can be shared with other software developers and programmers, minimizing change control actions after software is released. Organizations that will need to reinvent themselves include, but are not limited to, the following:

DevOps groups have developed a set of practices for software development (Dev) and IT operations (Ops). The purpose is to streamline the SDLC, applying validation methodologies, such as Agile, to software development, and providing continuous delivery.
Quality groups will need to change as intelligent technologies replace repetitive and mundane validation tasks by providing automated assurance that the software is performing as it was intended and according to the user requirements specifications.
Intelligent technologies and methods (e.g., AI and ML) will replace traditional/legacy technologies and methods that will over time become obsolete.
SDLC needs to be modernized and get back to basics by applying software engineering discipline and principles to new applications that enable continuous life cycle management.
AI And Advanced Technology And Research
AI presents a modern way for quality organizations to be compliant using test automation. AI is also a method used to advance technology and research by directing computers to perform automated tasks (using algorithms) through the application and translation of machine language. AI can teach machines to learn for themselves and find new avenues for learning.

As the life sciences industry starts taking advantage of AI and ML, its leaders will be known as future thought leaders, visionaries, and influencers. When we think of AI, some examples that come to mind are: adaptive (i.e., robust, efficient, and agile), prescriptive, and actionable data analytics; machine learning, automated administrative tasks (i.e., for patients, doctors, and healthcare personnel), as well as intelligent medical devices; and machines that can be designed to help and assist humans. Some of the top uses include, but are not limited to, diagnostic imaging, surgical robots, and faster, smarter, and secure tools. In fact, when looking at the world of robotics, machines can be designed in such a way as to imitate humans. By integrating engineering fields (i.e., mechanical engineering with computer engineering), software engineers can now develop programs in human-like language.

Some new challenges for software developers and software validation leads may include, but are not limited to, how do you test code when the outcome of the prescribed code potentially provides different results each time you test it? How do you test code when the inputs vary and the outputs are based upon other factors? How do you leverage the extensive work of the software developer/software engineer without duplicating the code? Answers to these and other questions will be discussed as we do a deeper dive into AI and ML.

Concepts For Intelligent Technologies
Concepts that enable intelligent technologies include, but are not limited to, the following:

AML: ACPI Machine Language (AML) is platform independent code.
Machine learning: Can machines learn by themselves? Maybe, if machines were coded to think like humans, learn to read text, and figure out the purpose of the text and/or understand music.
Neural networks are computer systems that simulate the human brain and can be taught to understand things based on their structure. Applied intelligence is AI services coupled with analytics and automation to create a strategy for your organization.
Predictive analytics uses data, statistical algorithms, and ML techniques to predict trends, human behaviors, and patterns based on current and historical data.
Conclusion

Biopharma, medical device, and pharmaceutical companies understand the benefits of test automation and many have already included continuous integration (CI) and continuous development and deployment (CDD) into their SDLC, while others are waiting for the new CSA guidance from FDA on how continuous testing will impact current validation regulations. Either way, intelligent, automated systems (e.g., AI and ML) are already here and will continue to be the future direction of technology development. The impact on these industries’ software and on the validation life cycle will be huge. The next article in this three-part series will continue to expand on validation challenges and next-generation intelligent technologies.

Informatica on Tuesday is officially unveiling its intelligent data management cloud (IDMC), an AI-powered platform designed to serve a broad base of users working with data in multi-cloud environments. Along with that, the company is announcing a series of partnerships and integrations with Microsoft Azure, Amazon Web Services and Google Cloud Platform.

Informatica has been in the business of data management tools for more than 20 years, and in that span of time, data has become increasingly valuable, Informatica Chief Product Officer Jitesh Ghai told ZDNet.

“We recognize our community of data-led practitioners has grown well beyond technical ETL experts, well beyond data engineers and data scientists,” he said. Now, it includes “non-technical users who want to operate with facts. Gut-based decision making has been laid bare as insufficient moving forward.”

As data becomes more valuable, so does data management, Informatica argues. Its IDMC offers more than 200 intelligent cloud services, powered by Informatica’s AI engine CLAIRE. It applies AI to metadata to give an organization an understanding of its “data estate,” Ghai explained.

The “data estate” tells you about the fragmentation of data — its location and the various domains of data. “And through that insight,” Ghai said, Informatica will “automate the ability to connect to data, to build data pipelines, process data, provision it for analytics… to apply advanced transformations to cleanse that data and trust it… to match, merge and build a single source of truth.”

From there, the platform aims to make data more accessible to business users with features like the “data marketplace.” With the marketplace, users can “shop for data” much as one would shop for consumer goods on the Amazon marketplace, Ghai explained.

The IDMC is micro-services based and API-driven, with elastic and serverless processing. It’s built for hybrid and multi-cloud environments. The platform is already running at scale, processing more than 17 trillion transactions each month. It’s leveraging over 11 petabytes of active metadata, Ghai said, to drive the data management that thousands of organizations are using for everything from customer experience modernization to supply chain management and financial transformations.

Unilever, for example, is using Informatica to get a “360 view” of their customers, Ghai said. The consumer goods conglomerate is leveraging its data to learn how to deeply engage with customers via their resellers. It’s also using data to manage its supply chain.

“More organizations want to be data-led than ever before,” Ghai said. “In the old world, we were focused on Fortune 500. In the new world, we’re focused well beyond the Global 2000.”

To reach as many customers as possible, Informatica is partnering with Microsoft to make the IDMC free on Azure for customers who want a simple testing opportunity. Otherwise, the IDMC is available in a consumption-based pricing model. Informatica is also expanding its Azure global footprint with new IDMC regions in Asia and Europe.

The free service provides 100 compute hours per month at no charge for Cloud Data Integration Services, Cloud Mass Ingestion Services, and out-of-the box connectivity to the most popular on-premise, cloud, and SaaS data sources and applications.

Meanwhile, Informatica is partnering with AWS to launch integrated cloud-native data governance and catalog as-a-service. The solution offers Informatica and Amazon Redshift integration, enabling customers to speed up data onboarding.

On Google Cloud, Informatica is making available Cloud Data Integration (CDI) Elastic, and it’s improving Cloud Mass Ingestion and API Management. Informatica’s partnership with Google Cloud has seen 135 percent year-over-year growth since 2019, the company said.

As business technology modernizes, data’s role in monetization has dramatically increased. It’s no surprise organizations have connected their overall success to the effective collection and use of data. However, it can be a challenge to maintain proper data posture in the cloud as data sprawl or siloes are common pitfalls. Additionally, there is now increased scrutiny of data never experienced before. The essence of data is constantly expanding, which has constructed a significant problem for many businesses in collecting, storing and leveraging information.

Here are three tips to help improve your organization’s data management in the cloud:

Always look ahead
Once you migrate to the cloud, your job is nowhere close to being done. The moment a migration is complete is when the real work starts. Tracking and controlling costs, keeping up with the evolving security landscape and optimizing overall performance become critical parts of the process. Below are some questions that must be answered ongoing:

Where will data live and why?
How will data be collected, cataloged, and leveraged?
What is the established process?
Do you have a master data management strategy with supporting security structures in place?
Businesses should have a clear strategy and delegation of tasks in place to answer each question. The major cloud players like AWS and Microsoft Azure, provide native tools in their environments that can help accomplish these goals. If your company doesn’t use either of those platforms, there are also many non-native solutions that can be used in any public cloud. No matter the solution it’s always smart to seek counsel from a cloud managed services provider who will identify possible improvements, underused resources, and solutions that align with organizations’ goals.

AI/ML accelerating a business’s time-to-value

When collecting, storing and analyzing data, artificial intelligence (AI) and machine learning (ML) can play a huge role. By using AI and ML, businesses are able to monetize information at a faster, more effective rate. In order to get the most out of AI/ML, data must continue to be easily accessible without sacrificing security, making the cloud a perfect option.

An increase in flexibility, scalability and speed are just a few of the advantages displayed by the public cloud compared to a pure infrastructure system, which cannot operate at the same level. The cloud combined with a successful AI/ML strategy allows companies to accelerate their value to levels never seen before.

Add a solution provider to your team
When operating in the cloud, one common challenge that often boils to the surface is finding the right personnel while ensuring business-critical objectives are still top of mind. Many organizations are used to maintaining on-premise data centers, creating a skills gap when moving to a cloud infrastructure.

Candidates with cloud-focused experience are hard to come by, so many organizations look for external help from solution providers. Cloud managed service providers are experts on completing seamless, secure cloud migrations, and can help develop strategic plans to migrate only the necessary data based on your business’s needs. According to Emergent Research and Intuit, 80 percent of U.S. small businesses will deploy cloud computing in 2020.

Preparing for the future
If the past year has taught us anything it’s that businesses can never be too prepared for the future. When looking ahead, it’s critical to keep in mind the continued role the cloud will play for competitiveness. As part of this planning, identify the best strategy to leverage the cloud’s benefits — flexibility, scalability, security, and accessibility. COVID-19 has increased the rate of change in the modern business landscape, meaning cloud consumption is no longer a run-of-the-mill tool: it’s essential.

Despite all the talk of cybersecurity capabilities being built in versus bolted on, security remains an afterthought for a vast majority of digital transformation activities such as mobility, cloud services and customer experience programs.
Too often, security is seen as slowing down a project rather than enabling its success, and with time pressure to get a project up and running, the lack of sound security considerations is a problem for organisations striving for true business resilience.

Ensuring that cyber risk management is part of your business resilience plan is not something that can be added after the event. It must be included from the outset and embedded across the organisation, from your technologies right through to your culture. Today, the pressure in the digital economy is to be ‘always on’, offering a continuously available service to customers. And that means that – more than protecting the enterprise – the challenge now is to ensure its resilience.

Red Hat is the world’s leading provider of enterprise open source solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. They help you standardise across environments, develop cloud-native applications, and integrate, automate, secure, and manage complex environments with award-winning support, training, and consulting services.

Through Red Hat’s services, your business will be able to combine business continuity planning with risk management planning to better navigate disruptive change and protect shareholder value, this spills over into being strategic about cloud migration too.

As the world becomes more turbulent, organizations need to accelerate their business resilience planning.
As organisations continue to expand their digital footprint, the risks associated with digital business are increasing in quantity and complexity and the need to provide continuously available services to customers requires organizations to become more reliable and more resilient.

As organizations rapidly adopt cloud networks, due to flexibility, scalability, cost effectiveness and more, security needs to be at the front and centre. It is against this background that the virtual Cloud & Security Forum 2020 is designed to assist in driving an impartial and informed dialogue in the rapidly evolving information security industry. The virtual event will unfold on the 18th and 19th of March.

Having continued to create an environment for making new connections, the summit with visionary speakers at the nexus of new technologies and cyber security solutions purposes to share their insights and demonstrate their ability to safeguard customer data.

From new applications being consistently added to networks to employees taking access control shortcuts and credentials being compromised, it is clear that there are endless vulnerabilities to detect and manage.

DENVER, March 3, 2021 – Leaders of the software development industry today announced the formation of the Value Stream Management Consortium (VSMC). Founded by leading technology providers, Digital.ai, HCL Software, Plutora, ServiceNow, and Tasktop, the VSMC charter is to help organizations around the world improve performance and drive customer value through the adoption of value stream management (VSM).

Still in its infancy, the purpose of VSM is to delight customers by delivering software products that provide and create value for them. VSM achieves this through a comprehensive software lifecycle orchestration process that provides value stream managers, release managers, DevOps managers, product managers, and leadership with the data, visibility, and problem-solving tools necessary to continuously improve software development and delivery.

“At this stage in the development of value stream management it’s important that we create and foster a community of experts to further VSM practices, innovation, and adoption,” said Helen Beal, Chair of the Value Stream Management Consortium. “By creating this community, we will increase and accelerate the use of VSM, while developing and instilling best practices and standards. And, ultimately, just like the practice of VSM itself, we will help deliver the utmost value to industry practitioners.”

About The Consortium

The consortium will serve as a central hub of information and education pertaining to the practice and adoption of value stream management. Ongoing research will inform how organizations measure value and become higher performing as a result. Training and certifications will support member collaboration worldwide and help make VSM the industry standard way of working.

The Consortium’s inaugural research offering will be the `The State of Value Stream Management Report’ which will measure how teams are applying value stream management principles, practices, and metrics to influence their value stream management outcomes. The survey will be launched today, and its findings will be available in early May.

The Board of Directors is comprised of Chair, Helen Beal and representatives from the founding companies, including Richard Knaster, Chief Scientist, Value Stream Management at Digital.ai; Brian Muskoff, Director of Product Management and Development at HCL Software; Jeff Keyes, VP of Product at Plutora; Rohit Jainendra, VP and GM for ITBM and DevOps, at ServiceNow; and Neelan Choksi, President and COO at Tasktop. Advisors to the Board of Directors include Alistair Watkins, Bryan Finster; and Steve Pereira.

The VSMC is a professional membership association open to all. Members will receive the latest updates and unique learning opportunities evolving out of the growing VSM ecosystem, as well as participation in a fast-growing community of peers.

Lean enterprises perform better and deliver value more reliably, faster, and with higher quality and lower cost. They do this by applying value stream management to maximize flow, accelerate innovation, and improve value delivery efficiency and effectiveness, said Richard Knaster, Chief Scientist, Value Stream Management at Digital.ai. “Put simply, you need to go from managing projects to guiding long-lived value streams that focus on creating business outcomes vs. outputs. The VSMC will help organizations reach the next level in their Lean, Agile and DevOps practices to accelerate digital transformation and enable continuous delivery of customer value.”

“Software delivery is prime to make another leap and the timing of the Value Stream Management Consortium could not be better. We are excited to be part of this organization as the industry starts to put VSM theories into practice to improve productivity, business results and quality of work life for tech teams across the world,” said Brian Muskoff, Director of Product Management and Development, HCL DevOps. “Over the last decade, I’ve worked with a wide variety of industries and organization types – big and small – to help deliver their DevOps initiatives, and one thing stands out in all of those discussions; value stream management is the practice that will advance DevOps into its next phase. With so many different applications and ways that organizations can take advantage of value stream management, I am eager to see what shape the VSM market takes, and how we at the VSMC can help.”

“Guiding any organization through a digital transformation journey is a daunting task and can feel like you’re being pulled in a million directions,” said Jeff Keyes, VP of product, Plutora. “Working with the VSMC and emphasizing the importance of the tools we provide to a wider market will only help me with my most important task at hand, delivering value to our customers. The customer is key, and value stream management is how software development teams are able to consistently meet their evolving needs.”

“Maximizing value from software investments is critical for businesses in order to deliver great experiences for their customers and employees,” said RJ Jainendra, VP and GM for ITBM and DevOps, ServiceNow. “By partnering with the VSMC, ServiceNow is furthering the adoption of VSM to improve end-to-end value delivery processes, ultimately assisting organizations with driving impactful digital transformations.”

“Every CIO of a large, traditional company thrust into digital transformation shares the same struggle: quantifying and optimizing the value of their investments. Technical metrics, proxy metrics, simply do not translate to business outcomes. The industry requires a common language, standardized measurements and unified tools or many costly digital transformation efforts will fail,” said Neelan Choksi, President and COO at Tasktop. “Value Stream Management (VSM) transforms software delivery from the top, giving CIOs insights needed to adapt to market dynamics and optimize based on business outcomes, rather than process, while also providing actionable information for the IT teams doing the work. The VSMC will help to set and accelerate these standards, propelling enterprises into a future of innovation, without friction.”

The Value Stream Management Consortium

The Value Stream Management Consortium is the world’s leading organization creating, curating, and collaborating on research about the frameworks and principles of Value Stream Management. The VSMC delivers guidance around leveraging the best of Lean, Agile, DevOps, Systems Thinking, and beyond combined with world class technical solutions, integrations, and automation to accelerate the performance of organizations across the globe.

Google Cloud on Feb. 1 began offering healthcare organizations its new Intelligent Vaccine Impact Solution, which is a digital toolset that delivers data insights on COVID-19 vaccine distribution efforts.

Six details:

1. Google Cloud’s Intelligent Vaccine Impact Solution helps regional and local governments manage COVID-19 public health strategies including vaccine scheduling, analytics and virus forecasting.

2. The first component of the toolset features COVID-19 forecasting delivered via a machine learning approach combining artificial intelligence and epidemiology insights. The tool creates prediction models that can be applied to decision making for COVID-19 response and other infectious disease policy interventions.

3. The new toolset also comprises a vaccine information portal, which lets people search for information related to the COVID-19 vaccine when registering for an appointment on participating public health departments’ websites.

4. To help with scheduling vaccine appointments, Google Cloud’s tool lets individuals interact with AI-powered virtual agents to help determine users’ eligibility, get registered and schedule appointments.

5. The new Google toolset also includes a user sentiment and feedback section, which lets individuals engage with government organizations about COVID-19 response and vaccination efforts.

6. Google Cloud said it has already deployed the Intelligent Vaccine Impact solution in numerous states; for example, North Carolina is using the tools across several agencies to help manage vaccine rollouts.

The productivity of cloud computing ordinarily envisages that IT operations for a company should have as many managers as possible. Numerous public cloud players have emerged to help different necessities “as-a-service,” from a simple virtual instance. “CloudOps” is an advancing term and pattern that endeavors to guarantee that the advantages of cloud-based frameworks can be very much protected without IT operations losing control.

Cloud operations management is a process that takes care of planning, managing, controlling, and eventually redesigning cloud operational processes. This includes the management of both software and hardware as well as network infrastructures to encourage a productive and lean cloud.

IT tasks, operations and strategies usually are manual, repetitive and unbending to assure that changes are controlled and perceived to forestall unplanned blackouts. Automation of IT processes and operations becomes as crucial as any environmental shift towards agile infrastructure where speed is viewed as everything. A situation like this is especially appropriate for cloud conditions where the framework is virtual and scalable, with users requesting instant access and full control of deployed services.

Numerous organizations’ IT teams have moved to the cloud incredibly, and they currently have a blend of cloud setups—regardless of whether they call it hybrid IT, hybrid cloud, or multicloud. The approaching X-factor is the way to deal with the resulting complexity. They’re prepared to set up standard working systems for long-term cloud operations.

Cloud operations and management can be perceived through different qualities like business process management, cloud infrastructure and capacity planning, infrastructure monitoring, performance monitoring, and incident management. Cloud tasks offer huge flexibility and fabulous options compared to traditional computing or storage options.

The cloud requires less hardware than customary computing structures which give more noteworthy flexibility and a lower cost. Proper planning of capacity prevents you from paying for assets that aren’t being utilized efficiently and saves you from pointless expenses. A cloud-based process management offers a wide range of groundbreaking capabilities within the company as well as stretches out to investors, customers and partners.

Since cloud systems are out of the direct actual control of operations teams, proper consideration should be taken by the way they do tasks. Often, the operations team is reliant upon the cloud supplier for all data, and the supplier plans and executes most platform-related fixes.

This absence of control really adds to the benefit of utilizing the public cloud. You turn over a large portion of the direct control to the public cloud supplier, which ordinarily includes giving up the tedious control of platforms down to the crude metal. In uncommon situations, it’s conceivable to keep up that control with some public cloud suppliers, however very few.

With continuous monitoring and regular updates, customers can accomplish a reduction in time with the assistance of observing and provisioning of the servers managed by the actual software. With regular monitoring, proactive and managed solutions are given to assess and expand the business objectives.

Continuous infrastructure monitoring defeats service disturbances like system outages, performance bottlenecks, and application failures, which are extremely hard to recognize in the n-level modern-day application stack. Incident Management gives a solid way to address SLA episodes by covering viewpoints to service runtime in the cloud with the assistance of monitoring and analysis of occasions that may not cause SLA breaches.

A report by the Cloud Industry Forum inferred that UK companies dedicate 19% of their IT budget plans to cloud framework, only in front of the 18% spent on-premises infrastructure, and that by 2022, only 12% of IT budget plans will be spent on legacy technology, as cloud utilization increments. Yet, conventional frameworks actually comprise the majority of systems that run businesses.

Overview: Six Years of DevOps Research, One Clear Trend

The DORA (DevOps Research and Assessment) Accelerate State of DevOps 2019 report represents one of the most comprehensive longitudinal studies in the industry. Drawing on more than 31,000 survey responses gathered across six years of research, and produced in collaboration with Google Cloud, the report tracks how DevOps adoption and performance have evolved — and what separates elite performers from the rest of the field.

Two themes dominate the 2019 findings: the growing performance gap between top-tier DevOps teams and their peers, and the outsized role that cloud computing plays in enabling that performance. A third finding challenges a long-standing industry assumption — that heavyweight change approval processes improve stability.

Elite Performers Are Growing — and They’re Cloud Specialists

According to the 2019 report, the proportion of highest-performing DevOps teams has nearly tripled compared with earlier editions of the study, now representing approximately 20% of all respondents. This cohort continues to widen its lead over low and medium performers across key software delivery metrics including deployment frequency, lead time for changes, mean time to restore, and change failure rate.

Critically, cloud usage emerges as a strong differentiator. The report found that elite performers were 24 times more likely than low performers to be genuine cloud specialists. The study defined cloud specialisation using the five essential characteristics outlined in the NIST definition of cloud computing:

• On-demand self-service — teams can provision compute resources without requiring human interaction from the provider.
• Broad network access — capabilities are available over the network and accessible via standard mechanisms.
• Resource pooling — provider resources serve multiple consumers using a multi-tenant model.
• Rapid elasticity — capabilities can be scaled up or down quickly to meet demand.
• Measured service — resource usage is monitored, controlled, and reported transparently.

Organisations that operated across all five of these dimensions were far more likely to be classified as elite performers, suggesting that superficial cloud adoption — lifting and shifting workloads without embracing cloud-native operating models — does not deliver the same performance benefits.

The Problem with Heavyweight Change Approval Processes

One of the more provocative findings in the 2019 report concerns change management. For years, formal Change Approval Boards (CABs) and heavyweight approval workflows have been standard practice in ITSM-aligned organisations. The intuition behind them is understandable: if software releases are causing incidents, slow things down and add more gates.

The DORA data challenges this assumption directly. The report found that formal change approval processes — particularly those requiring sign-off from an external Change Approval Board — were associated with worse software delivery performance, not better. As the report states:

“Heavyweight change approval processes negatively impact speed and stability. In contrast, having a clearly understood process for changes drives speed and stability, as well as reductions in burnout.”

The research investigated a specific hypothesis: that requiring fewer, more formally approved releases would be associated with lower change failure rates. The data did not support it. Adding process gates in response to production incidents is, in the report’s framing, a red herring — one that slows delivery without improving reliability.

The Alternative: Shift Left, Automate, and Peer Review

Rather than relying on external approval boards, the report recommends moving quality and risk assessment earlier in the development lifecycle — a principle commonly described as “shifting left.” The report’s recommended approach combines human judgement with automation:

“Organisations should shift left to peer review-based approval during the development process. In addition to peer review, automation can be leveraged to detect, prevent, and correct bad changes much earlier in the delivery lifecycle. Techniques such as continuous testing, continuous integration, and comprehensive monitoring and observability provide early and automated detection, visibility, and fast feedback.”

In practical terms, this means replacing after-the-fact approval gates with engineering practices built into the development workflow:

• Peer code review — changes are reviewed by fellow engineers before merging, embedding risk assessment into the team’s normal workflow.
• Continuous integration (CI) — automated builds and tests run on every commit, catching integration problems early.
• Continuous testing — automated test suites cover unit, integration, and acceptance scenarios, reducing reliance on manual QA gates.
• Monitoring and observability — production telemetry enables fast detection and rollback when issues do reach production, reducing mean time to restore.

This approach does not eliminate process — it relocates it to where it is most effective and least disruptive to delivery flow.

Transformation Strategy: Why “Big Bang” Rarely Works

The 2019 report also addresses how organisations should approach DevOps transformation itself. The data suggests that incremental, sustained improvement consistently outperforms large-scale, all-at-once transformations — sometimes called a “big bang” strategy.

“One thing is clear: a DevOps transformation is not a passive phenomenon. No profiles report strong use of a ‘big bang’ strategy — though low performers use this the most often — and that’s probably for the best.”

The report elaborates on why big-bang approaches tend to struggle:

“In our experience, this is an incredibly difficult model to execute and should only be attempted in the most dire of situations, when a ‘full reset’ is needed. In the ‘big bang’, everyone needs to be on board for the long haul, with resources dedicated for a multi-year journey. This may explain why this method is seen most often among our low performers.”

The implication for engineering leaders is significant: organisations that attempt to transform everything at once — tooling, culture, process, and organisational structure simultaneously — face higher execution risk and tend to see worse outcomes than those who pursue targeted, iterative improvement.

Key Takeaways for DevOps and Platform Engineers

• Cloud specialisation matters. Adopting the full NIST model of cloud computing — not just migrating workloads — correlates strongly with elite DevOps performance.
• Change Approval Boards slow you down without improving stability. The data does not support the assumption that fewer, more formally approved releases reduce change failure rates.
• Shift quality left. Peer review, CI, continuous testing, and observability are more effective risk controls than external approval gates.
• Iterate, don’t reset. Incremental DevOps transformation outperforms big-bang approaches in the DORA dataset. Sustained, focused improvement is the pattern associated with elite performance.

The DORA Accelerate State of DevOps reports are published annually. For the full methodology and findings, refer to the official DORA research publications available through Google Cloud.

What Is Service Level Management Software?

Service Level Management software provides the tooling required to create and manage SLAs, operational-level agreements (OLAs), and underpinning contracts (UCs). Core capabilities typically include:

• SLA definition, tracking, and alerting
• Real-time dashboards showing service performance against agreed targets
• Escalation workflows triggered when thresholds are breached
• Reporting for stakeholder communication and compliance evidence
• Integration with ITSM platforms, monitoring tools, and CMDB systems

SLM software is a formal discipline within the ITIL service management framework, making it a standard component of enterprise IT service desks and managed service provider (MSP) platforms.

Key Vendors in the SLM Software Market

The market includes a mix of broad ITSM platform vendors that embed SLM capabilities and specialist tools focused on SLA and service desk management. Vendors commonly cited in market analyses include:

• ServiceNow – Enterprise ITSM platform with deep SLA management, workflow automation, and AI-assisted service operations.
• Micro Focus – Provides ITSM and IT operations management tooling oriented toward large enterprise environments.
• SysAid – Mid-market IT service desk platform with built-in SLA tracking and automation.
• Ivanti – Offers ITSM solutions with SLM capabilities, targeting both enterprise and mid-size organizations.
• Alemba – ITIL-aligned service management platform with strong SLA management features.
• Marval – Service management software focused on ITIL compliance and SLA monitoring.
• Interlink Software – Focuses on IT operations and service management integration.
• PhaseWare – Customer support and SLA management platform primarily for software vendors.
• NetHelpDesk – Help desk and ITSM tool with SLA configuration for MSPs and internal IT teams.
• SMART Service Desk – Cloud and on-premise ITSM solution with SLA tracking.
• Autotask (now part of Datto) – PSA platform popular among MSPs, with SLA and contract management.
• bpm’online (now Creatio) – Low-code CRM and service management platform with SLA support.

The competitive landscape ranges from large-scale enterprise platforms to focused MSP tooling, which means organizations need to evaluate vendors against their scale, integration requirements, and ITIL maturity.

Deployment Models: Cloud-Based vs. On-Premise

SLM software is available in two primary deployment models, each with distinct trade-offs:

Cloud-Based SLM

Cloud-hosted SLM platforms have gained adoption as organizations prioritize lower infrastructure overhead and faster time-to-value. Key advantages include:

• No hardware provisioning or maintenance burden on the IT team
• Subscription pricing that scales with usage or seat count
• Automatic updates and feature rollouts from the vendor
• Accessibility for distributed or remote teams

On-Premise SLM

On-premise deployments remain relevant for organizations with strict data residency requirements, complex integrations with internal systems, or regulatory constraints that limit use of public cloud services. Trade-offs include higher initial capital expenditure and ongoing maintenance responsibility.

Market Segmentation by Region

SLM software adoption is global, with demand driven by the growth of IT service operations, managed service providers, and digital transformation initiatives. Regional segments typically analyzed in market research include:

• North America (United States, Canada, Mexico) – Largest market by revenue, driven by mature enterprise IT spending and a large MSP ecosystem.
• Europe (UK, Germany, France, Italy, Spain, and others) – Strong ITIL adoption and regulatory drivers such as GDPR influence SLM tool selection.
• Asia-Pacific (China, Japan, India, South Korea, ASEAN, and others) – Fast-growing region as organizations in these markets invest in IT service operations maturity.
• Middle East and Africa (GCC, UAE, Turkey, South Africa, and others) – Emerging adoption, particularly in government and financial services sectors.
• Latin America (Brazil, Argentina, Colombia, and others) – Growing MSP and enterprise IT services markets driving incremental demand.

Factors Driving SLM Software Adoption

Several operational and strategic trends are contributing to sustained interest in SLM tooling:

• ITIL and service management frameworks – SLM is a defined process in ITIL 4, meaning organizations pursuing service management maturity need formal SLM capabilities.
• Growth of managed service providers – MSPs rely on SLA tracking and reporting as core contractual obligations to their clients.
• Hybrid cloud complexity – Managing service levels across on-premise, private cloud, and public cloud environments requires tooling that can aggregate data from multiple sources.
• Customer experience focus – Internal IT teams and external service providers face greater scrutiny on service quality, driving the need for measurable commitments and transparent reporting.
• Automation and AI integration – Modern SLM platforms increasingly incorporate machine learning to predict SLA breaches before they occur and suggest remediation actions.

Key Evaluation Criteria When Selecting SLM Software

When assessing SLM platforms, IT operations and service management teams should consider:

• Integration depth – Does the platform connect to your existing monitoring, CMDB, ticketing, and communication tools?
• SLA flexibility – Can you model complex, multi-tiered SLAs including nested OLAs and customer-specific exceptions?
• Reporting and audit trails – Does the platform produce defensible, exportable reports that satisfy contractual and regulatory requirements?
• Escalation automation – Are breach notifications and escalation workflows configurable without custom code?
• Scalability – Can the platform handle your current ticket volume and scale as the organization grows?
• Deployment model – Cloud, on-premise, or hybrid, depending on your security and compliance constraints.
• Total cost of ownership – Licensing, implementation, integration, and ongoing administration costs.

Summary

Service Level Management software occupies an important role in mature IT service operations, providing the structure needed to define commitments, measure performance, and demonstrate accountability to stakeholders. The vendor landscape spans large ITSM platforms such as ServiceNow through to focused MSP tools like Autotask. Deployment choice between cloud and on-premise remains a meaningful decision driven by compliance needs, integration complexity, and operational preference. As ITIL adoption continues to spread and hybrid cloud environments add service delivery complexity, the operational case for dedicated SLM tooling remains strong.

ServiceNow recognized for its ability to execute and completeness of vision

ServiceNow named a Leader in Gartner Magic Quadrant for IT Service Management Tools (Graphic: Business Wire

September 05, 2019 12:31 PM Eastern Daylight Time

SANTA CLARA, Calif.–(BUSINESS WIRE)–For six years running, ServiceNow (NYSE: NOW), the company that makes work, work better for people, has been named a Leader in the 2019 Gartner Magic Quadrant for IT Service Management Tools.¹ In the 2019 report, ServiceNow is positioned the highest for its ability to execute. ServiceNow ITSM transforms the impact, speed and delivery of IT so customers can deliver great experiences, increase productivity and achieve new insights.

“We believe our position in the market reflects our continued focus on enabling digital transformation as a strategic partner to the world’s largest enterprises.”Tweet this

ServiceNow had 51.1% of the global Experience Management: IT Service Management (ITSM) market share in 2018 according to Gartner.² The company was also named an August 2018 Gartner Peer Insights Customers’ Choice for IT Service Management Tools,³ which recognizes vendors in the market by verified end-user professionals, taking into account both the number of reviews and the overall user ratings.

“ServiceNow’s leadership in ITSM stems from our belief that people’s experiences with technology at work should be as simple, easy and intuitive as they are in their personal lives,” said Pablo Stern, senior vice president of IT Workflow Products at ServiceNow. “We believe our position in the market reflects our continued focus on enabling digital transformation as a strategic partner to the world’s largest enterprises.”

Unchain Innovation With ITSM

Gartner defines the IT service management (ITSM) tools market as follows: “ITSM tools help infrastructure and operations (I&O) organizations manage the consumption of IT services, the infrastructure that supports the IT services and the IT organization’s responsibility in delivering these services. These are most heavily used by IT service desks and IT service delivery functions to support the tasks and workflows for processes including incident, request, problem, change, service level, knowledge and configuration management.”

As IT leaders look to transform their service delivery model across IT, ServiceNow lets them unify the IT experience on a single platform. Customers can ensure IT is meeting service commitments while aligning to business goals and empowering the organization with insights into service delivery while identifying trends that may impact long term plans.

With ServiceNow, a leading credit reporting company redirected IT resources from putting out fires to delivering a superior customer experience and IT now spends 80% of its time on innovation. A children’s apparel company consolidated IT systems and accelerated service delivery, saving $3 million in license, maintenance, and hardware costs.

Key recent ServiceNow ITSM innovations include:

• Virtual Agent: Resolve common requests, increase customer satisfaction and keep agents focused on what matters with advanced AI and machine learning intelligence in ServiceNow’s enterprise chatbot solution
• Agent Workspace: Improve agent efficiency, prioritize work and take action with a workspace built to facilitate resolution
• ITSM Mobile: Get work done from anywhere with a native mobile experience
• Predictive Intelligence: Resolve issues faster by using built-in machine learning to automatically prioritize and assign issues

Built on the Now Platform, ServiceNow ITSM includes powerful capabilities that drive cross-functional communication and processes, including a single-data model to eliminate silos, automated workflows to reduce bottlenecks and knowledge management to manage policies in one location. Customers gain native artificial intelligence and machine learning capabilities to predict, prioritize and proactively manage the work that matters most.

Additional Information

• Gartner Report: 2019 Gartner Magic Quadrant for IT Service Management Tools
• ServiceNow Blog: Gartner names ServiceNow an ITSM Magic Quadrant Leader again
• Gartner ITSM Market Share: Market Share: All Software Markets, Worldwide, 2018
• Gartner Peer Insights: ServiceNow Named a November 2018 Gartner Peer Insights Customers’ Choice for IT Service Management Tools

¹ Gartner, ‘Magic Quadrant for IT Service Management Tools’ by Rich Doheny, Chris Matchett, Siddharth Shetty, August 29, 2019.

² Gartner, “Market Share: All Software Markets, Worldwide, 2018” by Terilyn Palanca, Hai Swinehart, Neda Gupta, Vanitha Dsilva, Laurie Wurster, Balaji Abbabatulla, Robert Anderson, Fabrizio Biscotti, Alan Dayley, Sid Deshpande, Jime Hare, Bindi Bhullar, Wararu Katsurashima, John Kostoulas, Rustam Malik, Sharat Menon, Chandra Mukhyala, Chris Pang, Julian Poulter, Michael Warrilow, Alys Woodward, Yanna Dharmasthira, Craig Roth, April 8, 2019.

³ Gartner, Best IT Service Management Tools (ITSM) Software of 2018 as Reviewed by Customers

Gartner Disclaimer

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Gartner Peer Insights Customers’ Choice constitute the subjective opinions of individual end-user reviews, ratings, and data applied against a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.

About ServiceNow

ServiceNow (NYSE: NOW) is making the world of work, work better for people. Our cloud-based platform and solutions deliver digital workflows that create great experiences and unlock productivity for employees and the enterprise. For more information,

© 2019 ServiceNow, Inc. All rights reserved. ServiceNow, the ServiceNow logo, Now, Now Platform, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries. Other company names, product names, and logos may be trademarks of the respective companies with which they are associated.

What Is Software Configuration Management?

Software Configuration Management (SCM) is the discipline of tracking and controlling changes to software systems throughout their lifecycle. SCM tools typically handle:

• Version control – recording changes to source code and configuration files over time.
• Baselining – establishing a known, stable reference point for a software release.
• Change tracking – logging who changed what, when, and why.
• Configuration identification – uniquely identifying every component in a system.
• Defect tracking – some platforms extend SCM to link code changes directly to bug reports and issue queues.

In modern DevOps pipelines, SCM tooling is foundational. Infrastructure-as-Code (IaC) practices rely on the same versioning and change-control principles that SCM tools enforce for application source code, extending configuration management to servers, containers, and cloud resources.

Key Players in the SCM Tools Market

The SCM tools landscape is broad and includes vendors spanning traditional version control, infrastructure automation, and full configuration-management platforms. Prominent players identified in the 2019 market overview include:

• Puppet – declarative, model-driven configuration management widely used in enterprise Linux environments.
• Ansible (Red Hat) – agentless automation platform using YAML playbooks; popular for its low barrier to entry.
• Chef – Ruby-based configuration management with a strong ecosystem of community cookbooks.
• SaltStack / SaltStack Platform – event-driven automation and remote execution engine suited for large-scale infrastructure.
• IBM – enterprise SCM and DevOps toolchain offerings including IBM UrbanCode.
• Microsoft – Azure DevOps (formerly VSTS) and PowerShell DSC for Windows-centric configuration management.
• AccuRev (Micro Focus) – stream-based version control aimed at parallel development workflows.
• CFEngine – one of the earliest configuration management tools; known for lightweight agents and high scalability.
• Canonical – Juju and related tooling for cloud application modelling on Ubuntu infrastructure.
• Atlassian – Bitbucket and associated CI/CD integrations for source control and pipeline management.
• TeamCity (JetBrains) – CI/CD server with deep integration into JetBrains IDEs and broader DevOps toolchains.
• Octopus Deploy – specialised deployment automation tool focusing on release management and environment promotion.
• Rudder – open-source continuous configuration and compliance tool targeting mixed Linux/Windows estates.
• Kamatera – cloud infrastructure provider; its inclusion in an SCM tools list is unusual and may reflect managed-service positioning.

Market Segmentation

By Deployment Type

• Cloud-based – SaaS and hosted configurations reduce infrastructure overhead and suit distributed teams. Most major vendors now offer cloud-hosted tiers.
• On-premise – preferred by regulated industries (finance, healthcare, government) where data residency or air-gapped environments are required.

By Organisation Size

• Large Enterprises – typically require audit trails, role-based access control (RBAC), and integration with ITSM platforms such as ServiceNow or Jira Service Management.
• SMEs (Small and Medium Enterprises) – often prioritise ease of onboarding, open-source availability, and low operational cost. Tools like Ansible and Git-based workflows are popular at this scale.

By Geography

The report segments the global market across the following regions:

• North America
• Europe
• China
• Rest of Asia Pacific
• Central & South America
• Middle East & Africa

Market Drivers and Trends

Several forces were shaping the SCM tools market as of 2019 and continue to be relevant:

• DevOps adoption – organisations investing in continuous integration and continuous delivery (CI/CD) pipelines create direct demand for robust configuration management tooling.
• Cloud migration – hybrid and multi-cloud architectures increase configuration complexity, driving the need for policy-as-code and drift detection capabilities.
• Security and compliance – regulatory pressure (GDPR, HIPAA, PCI-DSS) requires auditable, repeatable configuration states, a core strength of dedicated SCM platforms.
• Infrastructure as Code (IaC) – tools like Terraform, combined with configuration managers like Ansible or Puppet, blur the boundary between provisioning and configuration management.
• Container and Kubernetes adoption – while containers shift some configuration concerns into image layers and Helm charts, configuration management tools are increasingly used to manage the underlying node and cluster configurations.

Competitive Landscape

The SCM tools market is highly fragmented. No single vendor dominates across all use cases—organisations routinely combine tools (for example, Git for source control, Ansible for server configuration, and Octopus Deploy for release orchestration). Key competitive dimensions include:

• Agent vs. agentless architecture – agent-based tools (Puppet, Chef, CFEngine) offer richer reporting and enforcement; agentless tools (Ansible, SaltStack SSH mode) are simpler to deploy.
• Declarative vs. imperative models – declarative tools describe the desired end state; imperative tools specify the exact steps. Most modern platforms support both.
• Open-source community vs. commercial support – open-source cores (Puppet Open Source, Ansible community edition) lower entry costs while vendor-supported enterprise editions provide SLAs and additional features.
• Ecosystem integrations – depth of integration with cloud providers (AWS, Azure, GCP), ITSM platforms, and CI/CD pipelines is increasingly a deciding factor.

Choosing an SCM Tool: Practical Considerations

When evaluating SCM tools for your organisation, consider the following:

1. Scale – How many nodes will you manage? CFEngine and SaltStack are recognised for handling tens of thousands of nodes efficiently.
2. Team skill set – Ansible’s YAML syntax has a gentler learning curve than Chef’s Ruby DSL. Match tooling to your team’s existing skills.
3. Windows vs. Linux – Ansible, Puppet, and Chef all support Windows, but depth of Windows support varies. PowerShell DSC is a strong native option for Windows-only environments.
4. Compliance requirements – Tools with built-in compliance reporting (Puppet Compliance, Chef InSpec) reduce the effort of producing audit evidence.
5. Vendor roadmap and community health – Assess GitHub activity, release cadence, and commercial backing before committing to a platform.

Summary

The Software Configuration Management Tools market encompasses a wide spectrum of products—from pure version-control platforms to full-stack infrastructure automation suites. As DevOps practices mature and cloud adoption accelerates, the demand for reliable, auditable, and scalable configuration management continues to grow. Organisations that invest in the right combination of SCM tooling gain faster delivery cycles, stronger compliance posture, and reduced configuration drift across complex environments.

Overview

Quantitative screening models give investors a structured way to compare companies across multiple financial dimensions simultaneously. This article breaks down a set of quant signals for two NYSE-listed companies — ServiceNow, Inc. (NYSE:NOW), an enterprise cloud software platform, and Waste Management, Inc. (NYSE:WM), a large-cap environmental services business — covering valuation composites, price momentum, return quality, and earnings integrity metrics.

Q.i. Value: Identifying Undervaluation

The Q.i. Value ranks companies using four ratios: EBITDA Yield, Free Cash Flow (FCF) Yield, Liquidity, and Earnings Yield. A lower score generally suggests the company is more undervalued relative to peers.

• ServiceNow (NOW): Q.i. Value of 55.00
• Waste Management (WM): Q.i. Value of 39.00

On this metric, Waste Management scores materially lower, suggesting it appeared relatively more undervalued than ServiceNow at the time of measurement.

Value Composite Score (VC1 and VC2)

Developed by James O’Shaughnessy, the Value Composite (VC) score aggregates five valuation ratios: price-to-earnings (P/E), price-to-cash-flow (P/CF), EBITDA-to-enterprise value (EV), price-to-book (P/B), and price-to-sales (P/S). Scores run from 1 to 100, where scores closer to 0 indicate potential undervaluation and scores near 100 suggest overvaluation.

A second variant, Value Composite 2 (VC2), adds shareholder yield as a sixth input.

ServiceNow’s VC1 score of 80 and VC2 of 82 placed it toward the expensive end of the spectrum at snapshot date. Waste Management’s VC1 of 57 and VC2 of 48 indicated a more balanced to moderately valued profile, with shareholder yield improving its relative attractiveness in the VC2 calculation.

ERP5 Rank

The ERP5 Rank combines four factors — Earnings Yield, Return on Invested Capital (ROIC), Price-to-Book, and 5-Year Average ROIC — to help identify undervalued companies. Lower ranks indicate greater potential undervaluation.

• ServiceNow (NOW): ERP5 Rank of 14,508
• Waste Management (WM): ERP5 Rank of 8,113

Waste Management ranked considerably lower (better) on the ERP5 scale, consistent with its lower Q.i. and VC scores.

Historical Volatility

Historical volatility measures how much a stock’s price has deviated over a given period. Higher volatility generally implies greater risk and uncertainty. All figures below are percentage-based annualised volatility readings at the snapshot date.

ServiceNow exhibited roughly 2.5× the historical volatility of Waste Management across all measured periods, reflecting the higher price risk typically associated with high-growth software stocks versus mature, cash-generative industrials.

Price Index (Momentum)

The Price Index is calculated by dividing the current share price by the share price at a prior date. A value above 1.0 indicates price appreciation; below 1.0 indicates depreciation over that period.

ServiceNow (NOW)

Waste Management (WM)

Over longer horizons, ServiceNow significantly outpaced Waste Management in price appreciation — a 3-year index of 3.63 versus 1.90 — though this came with substantially higher volatility. Both stocks showed slight short-term weakness in their 1-month readings.

Return Metrics: ServiceNow (NOW)

Return on Assets (ROA)

Return on Assets (ROA) measures net income after tax divided by total assets, indicating how efficiently a company uses its asset base to generate profit.

• ServiceNow ROA: 0.000805 (approximately 0.08%)

This near-zero ROA is consistent with ServiceNow’s growth-phase profile at the time, where the company was investing heavily in sales, marketing, and R&D rather than optimising for near-term profitability.

Return on Invested Capital (ROIC)

ROIC is calculated by dividing net operating profit (EBIT) by employed capital (total assets minus current liabilities). The ROIC Quality ratio divides the 5-year average ROIC by the standard deviation of the 5-year ROIC — a higher figure indicates more consistent returns.

• ROIC (current): -0.015148
• ROIC 5-Year Average: -0.140710
• ROIC Quality: 0.306066

Negative ROIC figures reflect ServiceNow’s investment-heavy operating model at this point in its growth cycle, where operating losses were being generated while scaling the business.

FCF Yield 5-Year Average

The FCF Yield 5-Year Average divides the 5-year average free cash flow by the current enterprise value (market cap + debt + minority interest + preferred shares − cash). This gives a longer-term view of cash generation relative to business size.

• ServiceNow FCF Yield 5yr Avg: 0.003484 (approximately 0.35%)

Gross Margin Score

The Gross Margin Score (Marx) evaluates gross margin stability and growth over the previous eight years. The scale runs from 1 (best) to 100 (worst).

• ServiceNow Gross Margin Score: 8.00 — indicating strong, consistent gross margin improvement over the measured period.

Quality and Earnings Integrity Metrics: Waste Management (WM)

Current Ratio

The Current Ratio (current assets ÷ current liabilities) measures short-term liquidity. Very high ratios may suggest inefficient use of working capital; very low ratios may indicate difficulty meeting near-term obligations.

• Waste Management Current Ratio: 1.70 — indicating adequate short-term liquidity.

Gross Margin Score

• Waste Management Gross Margin Score: 7.00 — also near the top of the scale (1 = best), suggesting a highly stable gross margin profile over the prior eight years.

Beneish M-Score (Earnings Manipulation Indicator)

The M-Score, developed by accounting professor Messod Beneish, uses eight financial statement variables to estimate the likelihood that a company has manipulated its reported earnings. The eight inputs are:

• Days’ Sales in Receivables Index
• Gross Margin Index
• Asset Quality Index
• Sales Growth Index
• Depreciation Index
• SG&A Expenses Index
• Leverage Index
• Total Accruals to Total Assets

A score above −1.78 is a flag that earnings manipulation may be present. A score well below −1.78 indicates a lower probability of manipulation.

• Waste Management M-Score: −2.853 — below the −1.78 threshold, suggesting no strong signal of earnings manipulation at this date.

Piotroski F-Score

The Piotroski F-Score, developed by accounting professor Joseph Piotroski, rates financial strength on a scale of 1 to 9. It evaluates nine binary criteria across three categories:

• Profitability: ROA, operating cash flow, change in ROA, accruals (earnings quality)
• Leverage & Liquidity: Change in long-term debt ratio, change in current ratio, absence of new share issuance
• Operating Efficiency: Change in gross margin, change in asset turnover

A score of 9 indicates strong financial health; a score of 1 indicates weakness.

• Waste Management F-Score: 5 — a middling score suggesting a mix of positive and neutral signals, neither strongly bullish nor bearish on financial health criteria.

Summary Comparison

At the time of this snapshot, Waste Management scored more favourably on most traditional value metrics, while ServiceNow demonstrated far stronger long-term price momentum despite appearing expensive by composite valuation measures. These two stocks represent contrasting archetypes: a high-growth, high-multiple software company versus a durable, cash-generative industrial business.

Important Disclaimer

All data in this article reflects a single point-in-time snapshot from August 2019. Quantitative signals are screening tools, not buy or sell recommendations. Investors should conduct their own due diligence and consult a qualified financial adviser before making any investment decisions. Past price performance does not guarantee future results.

This article provides an independent overview of the incident management software landscape, covering the major platforms, their core capabilities, and how teams typically evaluate them. It draws on the context of a 2019 market report summary originally published on indiancolumnist.com and syndicated by HTF Market Intelligence, which identified key vendors active in this segment.

What Is IT/DevOps Incident Management Software?

Incident management software provides the workflows, alerting, escalation, and communication infrastructure needed to respond to IT and application failures. In a DevOps context, these tools are tightly integrated with monitoring systems, CI/CD pipelines, and collaboration platforms like Slack or Microsoft Teams.

Core capabilities typically include:

• Alert ingestion and deduplication – Receiving signals from monitoring tools (Datadog, Prometheus, Nagios, etc.) and suppressing alert noise.
• On-call scheduling and escalation policies – Routing incidents to the right engineer at the right time, with fallback escalation chains.
• Incident timelines and postmortem support – Capturing a chronological record of events to support blameless post-incident reviews.
• Integrations – Connecting with ticketing systems, observability stacks, version control, and chat tools.
• Reporting and SLA tracking – Measuring mean time to acknowledge (MTTA), mean time to resolve (MTTR), and other reliability metrics.

Key Platforms in the Market

The following platforms were identified as significant players in the incident management software market. Descriptions reflect each tool’s publicly known positioning as of the original publication context.

PagerDuty

PagerDuty is one of the most widely adopted on-call and incident response platforms. It offers sophisticated alert routing, escalation policies, on-call scheduling, and an event intelligence layer that uses machine learning to reduce alert noise. It integrates with hundreds of monitoring and observability tools and is commonly used by SRE and platform engineering teams.

Atlassian Jira Service Management (formerly Jira Service Desk)

Jira Service Desk—now rebranded as Jira Service Management after Atlassian’s acquisition of OpsGenie—combines ITSM ticketing with incident management workflows. It is particularly strong in organizations already using the Atlassian ecosystem (Jira Software, Confluence, Bitbucket). Its incident management capabilities were significantly enhanced by the OpsGenie integration.

OpsGenie

OpsGenie, acquired by Atlassian in 2018, focuses specifically on on-call management and alert routing. It supports flexible escalation policies, multiple notification channels (SMS, voice, push, email), and integrates with over 200 monitoring tools. Post-acquisition, it has been unified with Jira Service Management.

VictorOps (now Splunk On-Call)

VictorOps was acquired by Splunk and rebranded as Splunk On-Call. It emphasizes team-based incident response with a shared incident timeline, chat-based collaboration within incidents, and deep integration with the Splunk observability stack. It is well-suited to teams that prefer a collaborative, war-room-style incident workflow.

ServiceNow

ServiceNow is an enterprise ITSM platform with a mature IT Incident Management module. It is more commonly found in large enterprises with formal ITIL processes. Its strength lies in deep workflow automation, CMDB integration, and compliance reporting, though it is generally considered heavier and more process-oriented than developer-focused tools like PagerDuty.

Freshservice

Freshservice is a cloud-based ITSM tool from Freshworks that includes incident, problem, change, and asset management. It targets mid-sized organizations looking for an approachable, SaaS-delivered alternative to ServiceNow. Its incident management module follows ITIL conventions while offering a clean user interface.

Samanage (now SolarWinds Service Desk)

Samanage was acquired by SolarWinds and rebranded as SolarWinds Service Desk. It provides IT service management with incident and problem management, integrated asset management, and a service portal. It is commonly used by IT operations teams in SME environments.

NinjaRMM (now NinjaOne)

NinjaRMM (rebranded as NinjaOne) is primarily a remote monitoring and management (RMM) platform targeting managed service providers (MSPs). While it includes alerting and ticketing capabilities relevant to incident management, it serves a somewhat different use case than pure-play incident response tools.

Other Notable Platforms

• DERDACK Enterprise Alert – An on-premises and cloud alerting platform with strong support for complex enterprise environments and multi-channel notifications.
• SunView ChangeGear – An ITSM platform with ITIL-aligned incident and change management modules.
• Symantec (now Broadcom) – Symantec’s IT management portfolio was acquired by Broadcom; its positioning in the incident management space has evolved significantly since 2019.
• Web Help Desk (SolarWinds) – A ticketing and asset management tool geared toward IT support teams in education and small enterprise environments.

How the Market Segments

Incident management tools broadly segment across several dimensions relevant to buyers:

By Organization Size

• Large enterprises tend to gravitate toward ServiceNow, PagerDuty, or Jira Service Management, which offer enterprise-grade access controls, audit trails, and integrations with complex infrastructure stacks.
• SMEs and scale-ups often favor Freshservice, OpsGenie, or VictorOps/Splunk On-Call for faster deployment, lower overhead, and more flexible pricing.

By Primary Use Case

• On-call and alerting – PagerDuty, OpsGenie, Splunk On-Call
• ITSM / help desk – ServiceNow, Freshservice, Jira Service Management, SolarWinds Service Desk
• MSP / RMM – NinjaOne, Web Help Desk
• Enterprise on-premises – DERDACK, SunView

By Delivery Model

• SaaS / cloud-first – PagerDuty, OpsGenie, Freshservice, Splunk On-Call
• On-premises or hybrid – DERDACK, some ServiceNow deployments

What to Evaluate When Choosing a Platform

When assessing incident management tools, engineering and IT operations teams should consider the following criteria:

1. Integration depth – Does the tool connect natively with your existing monitoring, logging, and observability stack?
2. Alert routing flexibility – Can you define complex escalation policies, time-based routing, and override schedules?
3. Notification channels – Does it support SMS, voice calls, push notifications, and chat integrations your teams actually use?
4. Incident collaboration – Does the platform support a shared incident channel, stakeholder updates, and a live incident timeline?
5. Postmortem workflows – Are there built-in tools for retrospectives, or does the tool export data to support your existing postmortem process?
6. Reporting and metrics – Can you measure MTTA, MTTR, on-call load, and incident frequency over time?
7. Pricing model – Is it per-user, per-seat, or usage-based? How does it scale as your team grows?
8. Compliance requirements – For regulated industries, does the tool support audit logs, role-based access, and data residency options?

Market Context

The 2019 HTF Market Intelligence report that inspired this article highlighted strong global demand for incident management software across North America, Europe, and Asia-Pacific, driven by increasing digital service complexity and enterprise adoption of DevOps practices. Since then, consolidation has continued—OpsGenie and Jira Service Desk merged into Jira Service Management, VictorOps became Splunk On-Call, and Samanage was folded into SolarWinds Service Desk—reflecting a maturing market where ITSM and DevOps-oriented incident response converge.

For DevOps and SRE teams, the practical implication is that tool selection increasingly comes down to cultural fit and ecosystem alignment: teams in the Atlassian ecosystem will often default to Jira Service Management and OpsGenie, Splunk users may lean toward Splunk On-Call, and teams seeking a best-of-breed on-call solution independent of observability vendor lock-in frequently choose PagerDuty.

Summary

The IT/DevOps incident management software market encompasses a broad range of tools—from lightweight on-call schedulers to full ITSM suites. The right choice depends on team size, existing toolchain, workflow maturity, and compliance requirements. As the market continues to consolidate and vendors expand their platforms, revisiting your tooling decisions annually is worthwhile to ensure your incident response capabilities keep pace with your infrastructure complexity.

What Is Release Management?

Release management is the discipline of planning, scheduling, controlling, and deploying software builds through different stages of the development pipeline and into production. It sits at the intersection of DevOps, ITSM (IT Service Management), and software delivery, covering everything from coordinating cross-team approvals to automating deployment pipelines and managing rollback procedures.

As organizations accelerate their software delivery cycles, structured release management becomes critical for reducing deployment risk, maintaining compliance, and improving the reliability of releases across major, minor, and emergency change categories.

Market Overview

A 2019 global market research report on the Release Management sector examined the competitive landscape, regional demand patterns, technology trends, and growth drivers shaping the industry. The report assessed the market in USD million terms and applied both primary and secondary research methods to compile its findings.

The study covered analysis across major geographies including the United States, China, Europe, Japan, Korea, and Taiwan, offering both global and regional perspectives on adoption rates and vendor activity.

Key Vendors in the Release Management Market

The 2019 report identified a broad competitive field of vendors operating across enterprise ITSM platforms, DevOps toolchains, and managed services. Key players mentioned include:

• Micro Focus – Enterprise software with strong ITSM and ALM tooling
• ServiceNow – Cloud-based ITSM platform with dedicated change and release management modules
• BMC Software – IT management solutions including Remedy and Helix for change/release workflows
• CA Technologies (now Broadcom) – Enterprise DevOps and release automation tooling
• Freshworks – Cloud-based service desk and ITSM tools targeting SMEs and mid-market
• Atmosera – Managed cloud services provider with DevOps delivery capabilities
• bpm’online (now Creatio) – Business process automation with service management features
• Sumo Logic – Cloud-native log analytics relevant to release observability
• Nexthink – End-user experience management with release impact monitoring
• EasyVista – IT service management platform with release workflow support
• Symphony SUMMIT – ITSM and automation platform
• Cutover – Runbook automation and release orchestration
• JanBask, Project Open, Vision Helpdesk, Global Vox, Grolimund + Partner, Coupa, ObjectGears, Avocado Consulting, SKS Solutions, BroadSource – Niche and regional players contributing to market diversity

Market Segmentation

By Release Type

• Major Release – Significant new functionality or architectural changes; highest risk and planning overhead
• Minor Release – Incremental feature additions or bug fixes; lower risk, more frequent cadence
• Emergency Release – Hotfixes and critical patches deployed outside the standard release cycle; requires expedited approval workflows

By Organization Size

• Large Enterprises – Complex multi-team release pipelines, regulatory compliance requirements, and integration with CMDB and ITSM systems
• Small and Medium-sized Enterprises (SMEs) – Lighter tooling, faster adoption of SaaS-based release management solutions, price sensitivity

Report Structure and Analysis Framework

The market research report was structured across 15 analytical segments. The key areas of investigation included:

• Market definition and classification – Scope of release management, application domains, and regional breakdown
• Supply chain and cost structure – Vendor ecosystem, raw input costs (primarily labor and infrastructure), and industry chain analysis
• Manufacturing and R&D landscape – Development capacity, innovation sources, and technology maturity
• Competitive market share analysis – Revenue and volume share by vendor, pricing analysis
• Regional market performance – Demand patterns across North America, Europe, and Asia-Pacific
• Trend analysis by product type and application – Growth trajectories for major, minor, and emergency releases across enterprise segments
• Value chain and distribution channels – Routes to market including direct sales, resellers, and managed service providers
• SWOT and competitive profiling – Strengths, weaknesses, opportunities, and threats for major vendors
• Conclusions and forecasts – Forward-looking projections for the release management market over the study period

Key Market Drivers

Several forces were identified as shaping demand for release management tooling and services as of 2019:

• Accelerating DevOps adoption – CI/CD pipelines increased deployment frequency, raising the need for structured release governance
• Cloud migration – Hybrid and multi-cloud environments introduced new complexity into coordinating deployments across infrastructure boundaries
• Regulatory compliance – Regulated industries (finance, healthcare) required auditable change management processes aligned with frameworks such as ITIL
• Digital transformation initiatives – Enterprises modernizing legacy systems needed release management to de-risk large-scale transitions
• SME SaaS adoption – Affordable, cloud-delivered release management tools lowered the barrier for smaller organizations

Analytical Methods Used

The report applied standard market research frameworks to evaluate competitive positioning and market outlook, including:

• Porter’s Five Forces – Assessing competitive rivalry, supplier power, buyer power, threat of substitutes, and barriers to entry
• SWOT Analysis – Per-vendor evaluation of strategic position
• Value Chain Analysis – Mapping the flow from technology development through to end-user adoption
• Primary and secondary research – Combining vendor interviews, public filings, and secondary data sources

Why Release Management Matters for DevOps Teams

For DevOps practitioners, release management is not just an ITSM checkbox — it is an operational discipline that directly affects deployment frequency, change failure rate, and mean time to recovery (MTTR), three of the four key DORA metrics used to measure software delivery performance.

Effective release management integrates with CI/CD tooling (such as Jenkins, GitLab CI, or Azure DevOps), tracks deployment artifacts through environments, manages feature flags, coordinates stakeholder communication, and provides a clear audit trail. Vendors like ServiceNow and BMC Software address the ITSM governance layer, while tools like Cutover focus specifically on orchestrating complex release runbooks.

Understanding the competitive landscape helps engineering and operations teams make informed build-vs-buy decisions and select tooling that fits their organizational maturity, compliance requirements, and deployment cadence.

Summary

The 2019 global release management market reflected a maturing but competitive space, with established ITSM vendors competing alongside newer DevOps-native and SaaS-first players. The segmentation between major, minor, and emergency releases — and between large enterprises and SMEs — continues to shape how vendors position their products. For DevOps teams evaluating release management tooling, this competitive landscape provides useful context for understanding where different platforms focus their capabilities.

The following four best practices give DevOps and cloud engineering teams a practical foundation for optimizing Azure resource management.

1. Use ARM Templates to Replicate Azure Resources

Infrastructure-as-code is one of the most powerful levers available to cloud operations teams. Azure Resource Manager (ARM) templates let you define your infrastructure in declarative JSON, enabling repeatable, consistent deployments across environments—whether for development, testing, staging, or disaster recovery.

ARM templates operate at the resource group level. You can trigger a deployment via an API call, the Azure CLI, Azure PowerShell, or directly through the Azure portal. Because templates are idempotent, re-running the same template against an existing resource group will bring resources into the desired state without duplicating what already exists.

Key Considerations

• Policy enforcement: Azure Policy can block deployments that violate organizational rules (for example, restricting VM SKUs or enforcing tagging). Test templates in a non-production subscription first to surface policy conflicts before they affect live workloads.
• VM image capture: Azure does not provide a direct VM clone operation. To replicate a VM, you must capture its image—a process that generalizes the machine (using sysprep on Windows or the Azure Linux Agent’s deprovision command on Linux) and renders the original VM unusable. Never perform this on a running production server without first creating a backup or snapshot.
• Modular template design: Break large templates into linked or nested templates to improve reuse and reduce deployment complexity as your environment grows.

// Minimal ARM template skeleton
{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {},
  "resources": []
}

2. Maximize Savings with Azure Reserved Instance Size Flexibility

On-demand pricing is convenient but expensive at scale. Azure Reserved VM Instances (RIs) let you commit to one- or three-year terms in exchange for significant discounts compared to pay-as-you-go rates. The size flexibility feature extends the value of an RI by allowing the discount to apply to differently sized VM instances within the same VM series (instance family), not just the exact SKU you originally purchased.

How to Get the Most from RI Flexibility

• Plan your workload profile before purchasing. The flexibility ratio—how many normalized units a given VM size represents—varies across instance sizes within a family. Larger instances consume more units, so a single large RI can partially cover several smaller VMs, or vice versa.
• Choose the right scope. A reservation scope can be set to a single subscription or shared across all subscriptions in a billing account. Shared scope is typically more efficient because Azure can automatically apply the discount wherever utilization is highest.
• Manage reservations actively. As workloads change, you may need to split a reservation, merge reservations, or adjust the scope. These operations are available in the Azure portal under Reservations.
• Monitor utilization. Unused RI capacity is wasted spend. Use Azure Cost Management to track reservation utilization and identify opportunities to exchange or return underused reservations within Microsoft’s allowed windows.

3. Build Resiliency with Azure Availability Zones

Availability zones (AZs) are physically separate data centers within a single Azure region. Each zone has independent power, cooling, and networking. Distributing workloads across AZs protects applications from single data center failures and is a foundational pattern for high-availability architectures on Azure.

Zonal vs. Zone-Redundant Services

Azure services that support availability zones fall into two categories:

• Zonal services: A resource—such as a virtual machine or a managed disk—is pinned to a specific zone at deployment time. You control zone placement and are responsible for distributing resources across zones manually.
• Zone-redundant services: Azure automatically replicates data and compute across zones. Examples include Azure Virtual Machine Scale Sets, Azure SQL Database, and Azure Storage with zone-redundant storage (ZRS) replication. These services handle zone distribution transparently.

Load Balancing Across Zones

To distribute traffic across VMs deployed in multiple zones, use the Azure Standard Load Balancer, which supports zone-redundant front-end IP addresses. The Basic Load Balancer SKU does not support availability zones, so teams running zone-aware workloads should ensure they are using the Standard SKU.

Not all Azure regions support availability zones. Before designing a zone-redundant architecture, verify that your target region includes at least three AZs in the official Azure documentation.

4. Optimize Azure Subscription Management

Azure subscriptions are the fundamental unit of resource access and billing. Every resource deployed in Azure belongs to a subscription, which defines who has access, what policies apply, and how costs are attributed. As organizations scale, ad hoc subscription growth leads to governance gaps, cost visibility problems, and security risks.

Subscription Design Principles

• Use Management Groups: Azure Management Groups let you apply policies and role-based access control (RBAC) across multiple subscriptions from a single point. Organize subscriptions into a hierarchy that reflects your organizational structure—for example, separating production, non-production, and sandbox environments.
• Apply RBAC at the right scope: Assign permissions at the management group or resource group level rather than directly on individual resources. This reduces administrative overhead and makes access reviews more manageable.
• Enforce governance with Azure Policy: Use Azure Policy to enforce compliance requirements—such as mandatory resource tagging, allowed locations, or permitted VM SKUs—consistently across all subscriptions in a management group.
• Separate workloads by subscription when needed: Subscriptions have service limits (quotas). High-scale workloads may require dedicated subscriptions to avoid hitting these limits. Also consider separating workloads with different compliance requirements into distinct subscriptions to simplify audit scope.
• Use Cost Management and budgets: Set budget alerts per subscription or resource group so teams are notified before they exceed spend thresholds.

Summary

Adopting these practices systematically—rather than addressing them reactively—gives DevOps teams the control they need to run Azure workloads reliably and cost-effectively. Start by auditing your current ARM template coverage and subscription structure, then layer in Reserved Instances and availability zone placement as workloads mature.

Original topic sourced from TechTarget (techtarget.com).