https://www.techtarget.com/searchitoperations/definition/DevOps
DevOps is a software development approach that brings development and IT operations teams together to deliver applications faster and more reliably.
The philosophy promotes better communication and collaboration between the two teams -- and others -- in an organization. It includes adopting iterative software development, automation and programmable infrastructure deployment and maintenance. DevOps also includes cultural changes, such as building trust and cohesion between developers and systems administrators and aligning technological projects to business requirements. DevOps can transform software delivery processes, job roles, tools and best practices.
DevOps isn't a specific technology, but DevOps environments do use common methodologies:
A DevOps approach is one of many techniques IT staff use to execute IT projects that meet business needs. DevOps doesn't have an official framework, but the CALMS framework (culture, automation, lean, measurement and sharing) is a popular implementation model.
Some professionals believe that the simple combination of development and IT ops isn't enough, and that DevOps should include business (BizDevOps) and other areas. For example, DevSecOps, which is the integration of security into the DevOps lifecycle, is increasingly important in today's cybersecurity landscape.
DevOps has been shown to improve software quality and development project outcomes for the enterprise. Such improvements take several forms:
A well-executed DevOps environment enables a business to deliver more competitive, higher-quality software products to market faster, with lower support and maintenance demands than traditional development approaches.
DevOps benefits include the following:
DevOps is a methodology meant to improve work throughout the software development lifecycle (SDLC). You can visualize a DevOps process as an infinite loop, comprising these DevOps pipeline stages: plan, code, build, test, release, deploy, operate, monitor and -- through feedback -- plan, which resets the loop.
Ideally, the cyclical loop that comprises each DevOps iteration alleviates significant stress on development outcomes.
DevOps gives organizations far more flexibility in developing and releasing software that matures systematically over time, allowing teams to learn, adjust and experiment in ways that traditional development methods don't support.
To align software with expectations, developers and stakeholders communicate about the project, and developers work on small updates that go live independently of one another.
To avoid wait times, IT teams use CI/CD pipelines and other automation to move code from one step of development and deployment to another. Teams review changes immediately and can rely on policies and tools to enforce policies and ensure releases meet standards.
To deploy good code to production, DevOps adherents use containers or other methods to ensure the software behaves consistently from development through testing and into production. They deploy changes individually so that problems are traceable. Teams rely on automation and configuration management for consistent deployment and hosting environments. Problems they discover in live operations lead to code improvements, often through a blameless post-mortem investigation and continuous feedback channels.
Developers might support the live software, which puts the onus on them to address runtime considerations. IT ops administrators might be involved in the software design meetings, offering guidance on how to use resources efficiently and securely. Anyone can contribute to blameless post-mortems.
The core pillars of DevOps culture are collaboration, shared ownership and accountability, automation, and learning and continuous improvement. Each of these pillars plays a vital role in realizing the full benefits of DevOps and quickly delivering reliable software at scale.
Although there's no one way to establish a DevOps culture, here are some best practices to consider:
Leaders should model core values, set clear expectations without micromanaging and offer incentives to teams that meet DevOps metrics.
Code repositories. Version-controlled source code repositories enable multiple developers to work on code. Developers check code out and in and can revert to a previous version if needed. These tools keep a record of modifications made to the source code -- including who made the changes and when. Without tracking, developers might struggle to follow which changes are recent and which versions of the code are available to end users.
In a CI/CD pipeline, a code change committed in the version-control repository automatically triggers the next steps, such as a static code analysis or build and unit tests.
CI/CD pipeline engines. CI/CD enables DevOps teams to frequently validate and deliver applications to end users through automation during the development lifecycle. The continuous integration tool automates processes so developers can create, test and validate code in a shared repository as often as needed without manual effort. Continuous delivery extends these automated steps into production-level tests and release management configurations. Continuous deployment goes a step further, invoking tests, configuration and provisioning, and providing monitoring and potential rollback capabilities.
Artifact repositories. Source code is compiled into an artifact for testing. Artifact repositories enable version-controlled, object-based outputs. Artifact management is a good practice for the same reasons as version-controlled source code management.
Configuration management and IaC. Configuration management systems enable IT to provision and configure software, middleware and infrastructure using scripts or templates. The DevOps team can set up deployment environments for software code releases and enforce policies on servers, containers and VMs through a configuration management tool. Changes to the deployment environment can be version-controlled and tested, enabling DevOps teams to manage infrastructure as code (IaC).
Containers. Containers are isolated runtimes for software on a shared OS. Containers provide abstraction that enables code to work the same way across different underlying infrastructures from development to testing and staging, and then to production.
GitOps. GitOps espouses declarative source control over application and infrastructure code. Everything about the software, from feature requirements to the deployment environment, comes from a single source of truth. GitOps is associated with change management and deployment techniques, such as immutable infrastructure, which dictates replacing or reinstancing -- rather than upgrading or changing -- deployed code each time a change is made.
Cloud environments. DevOps organizations often concurrently adopt cloud infrastructure because they can automate its deployment, scaling and other management tasks. Many cloud vendors also offer CI/CD services.
Cloud-based DevOps pipelines. Public cloud providers offer native DevOps tool sets for use with workloads on their platforms. Cloud adopters can use pre-integrated services or run third-party tools.
As-a-service models. DevOps as a service is a delivery model for a set of tools that facilitates collaboration between an organization's software development and IT ops teams. In this delivery model, the provider assembles a suite of tools and handles the integrations to seamlessly cover the overall process of code creation, delivery and maintenance.
In other cases, service providers act as consultants, assisting businesses with DevOps projects or supplementing expertise that might be lacking across the DevOps process. Service providers should be evaluated based on factors including time in business, proven experience -- particularly in related market verticals -- and compatibility with existing DevOps tools and practices.
Monitoring and observability. Monitoring and observability tools enable DevOps professionals to oversee the performance and security of code releases on systems, networks and infrastructure. They can combine monitoring with analytics tools that provide operational intelligence. DevOps teams use these tools together to analyze how code changes affect the overall environment. Observability specifically uses metrics, logs and traces to understand why something is happening.
DevOps vs. Agile vs. Waterfall. In terms of strategy, DevOps is associated with Agile software development because Agile practitioners promoted DevOps as a way to extend the methodology into production. This mindset has even been labeled a counterculture to the IT service management practices championed in ITIL. In traditional Waterfall development, teams used an all-or-nothing approach, gathering requirements upfront and then writing, testing and releasing code as events. They addressed any performance or reliability issues as an afterthought.
To refine their practices, organizations should understand the related contexts of DevOps, Agile and Waterfall development, site reliability engineering (SRE) and SysOps, and even the variations within DevOps. These approaches influence how organizations structure teams and define responsibilities.
Depending on the type of organization, there are several DevOps roles that IT leaders should consider for the team, as they each bring valuable skills to the table. The job descriptions vary, and not all are needed due to overlapping responsibilities, but here's a basic overview of the different types of roles:
IT leaders can establish DevOps roles in one of three ways:
In addition to business acumen, DevOps team members should have a variety of skills in software development, infrastructure management and project management.
More specifically, DevOps engineers should be familiar with various platforms, programming and scripting languages, configuration management, version management, IaC, provisioning, deployment, security, tracking and assessing release performance, network optimization, troubleshooting, integration, communication and team management.
There are many DevOps certifications and training courses available, including, but not limited to, the following:
The adoption of DevOps or other CD paradigms can be disruptive to software and management teams. There are inevitable changes to workflows, processes, tool sets and even staffing that will drive the need for more training. DevOps adoption can easily get off track and eventually fall by the wayside. Below are some tips to help ease DevOps adoption and increase the chances of DevOps success.
DevOps transformations don't happen overnight. Many companies start with a pilot project -- a simple application where they can get a feel for new practices and tools. DevOps teams look for quick, easy wins to refine workflows, learn the tools and prove the value of DevOps principles. For large-scale DevOps adoption, try moving in stages.
Initially, DevOps can mean a commitment from development and IT ops teams to understand the concerns and technical constraints at each stage of the software project. Agree upon KPIs to improve, such as shorter cycle times or fewer bugs in production. Understand how DevOps practices map to current development and deployment practices and plan suitable workflow changes to enhance software quality, security and compliance. Lay the groundwork for continuous processes by communicating across job roles.
Evaluate the existing tools for software development and IT operations. More or different tools might be needed. Identify process shortcomings, such as a step that's always handled manually -- for example, moving from a code commit to testing -- or a tool without APIs to connect with other tools.
Consider standardizing on a single DevOps pipeline across the whole company. With one pipeline, team members can move from one project to another without reskilling. This enables security specialists to harden the pipeline and eases license management. The tradeoff is that DevOps teams give up the freedom to use what works best for them.
Simply adopting DevOps isn't enough to ensure success. Understand the need for DevOps in the first place -- what problems it is intended to solve, or what benefits it is intended to deliver. Select metrics and KPIs that will show those outcomes and then plan to measure and report on those metrics as an objective gauge of DevOps success.
Specific metrics will vary across organizations, but leaders should incorporate a mix of delivery and deployment, reliability and stability, operational efficiency, and business and customer impact KPIs.
Start with the five DORA metrics, an industry-standard benchmark for delivery and reliability established by Google Cloud's DevOps Research and Assessment team:
The DevOps maturity model illustrates five principal phases of adoption, ranging from novice to well-established. Organizations can use the DevOps maturity model as a guide to adoption by identifying their place in the model:
The DevOps paradigm introduces complexities and changes that can be difficult to implement and manage within a busy organization. Common DevOps challenges include the following:
In short, DevOps doesn't solve every business problem or benefit every software development project in the same way.
DevOps is a mindset, not a tool set. But it's hard to do anything in an IT team without suitable and well-integrated tools. In general, DevOps practitioners rely on CI/CD pipelines, containers and cloud hosting. Tools can be open source, proprietary or supported distributions of open source technology.
Here are some examples of the different types of tools available:
As DevOps became popular, organizations formalized DevOps approaches. Retailer Target originated the DevOps Dojo training method, for example. Vendors touted DevOps-enabling capabilities in tools, from collaboration chatbots to CI/CD suites built into cloud services.
Technologies such as microservices, virtual containers and public cloud services offered a natural fit for the fast, flexible nature of DevOps.
DevOps continues to evolve, as AI surfaces to aid in everything from code creation to incident management. AI for DevOps means smarter automation, even shorter wait times and seamless translation of business needs into technology offerings.
The role of AI in DevOps practices affects teams in other ways as well. Established processes and DevOps roles and responsibilities are evolving as automation use in the SDLC increases. The tools that DevOps teams use are also getting smarter, ultimately leading to tool consolidation.
Other key DevOps trends in 2026 include platform teams joining DevOps teams and the use of intent-driven infrastructure, which enables teams to think less about the environment in which their software will be deployed, as AI determines the best fit based on workload analysis.
In addition, organizations are encouraging DevOps teams to be even more cost-conscious amid higher overall cloud spending. Organizations are also asking that regulatory concerns and recent geopolitical issues be at the forefront of DevOps teams' minds when developing and deploying software.
Currently, DevOps teams are building and customizing software to incorporate AI and automation, while the future of DevOps sees teams focusing more on high-level business issues and less on the tasks that AI and automation can handle.
Stephen J. Bigelow, senior technology editor at TechTarget, has more than 20 years of technical writing experience in the PC and technology industry.
Ryann Burnett, executive managing editor, has 10 years of experience at TechTarget Editorial, covering virtualization, containers, monitoring, observability, data centers, server hardware, IoT and other technologies.
Meredith Courtemanche and Alexander S. Gillis also contributed to this article.
28 Apr 2026