DevOps Lifecycle Explained: The Eight Phases of the Infinity Loop

The DevOps lifecycle is a set of eight continuous phases — plan, code, build, test, release, deploy, operate and monitor — that development and operations teams work through together to ship software faster and more reliably. These phases loop back on each other, forming the continuous infinity loop model.

Here is what every practitioner should know before going deeper:

• Eight named phases make up the DevOps lifecycle: plan, code, build, test, release, deploy, operate, monitor.
• The infinity loop shape signals that software delivery is continuous, not a one-time project.
• Agile shapes how you build features; DevOps shapes how you deliver and run them in production.
• Testing in DevOps starts at the code phase, not after the build, a practice called shift-left testing.
• Waterfall’s sequential, gate-by-gate structure makes it fundamentally incompatible with the continuous feedback that DevOps depends on.

The Eight Phases of the DevOps Lifecycle

The best way to understand the DevOps stages is to follow one small, concrete feature through all eight of them. Imagine an Indian fintech startup adding a UPI autopay toggle to its mobile app. Here is what happens at every phase.

Phase 1: Plan

The product manager writes a user story: “As a user, I want to set a UPI autopay mandate so I can pay subscriptions without manual approval.” The team estimates effort in a Scrum sprint planning session, assigns story points and adds the ticket to a backlog in Jira or Azure Boards. Planning feeds every subsequent loop because the monitor phase will later generate data that shapes the next sprint’s backlog.

Phase 2: Code

Developers write the feature in short, reviewable commits, pushing to a shared Git repository. Peer code reviews happen here. So does static analysis, where automated tools scan for security vulnerabilities and code smells before anyone runs the application. This is the first moment where quality gates kick in, long before a dedicated test environment exists.

Phase 3: Build

A CI server such as Jenkins, GitHub Actions or GitLab CI picks up the commit, compiles the code, resolves dependencies and packages the application into a deployable artefact. If the build breaks, the team is notified within minutes. Fast feedback at this stage is far cheaper than discovering a broken build three weeks later in staging. Many Indian SaaS teams in Pune and Hyderabad run build pipelines that complete in under five minutes, making this feedback loop genuinely useful rather than ceremonial.

Phase 4: Test

Automated test suites, unit tests, integration tests and API contract tests, run against the build artefact in an isolated environment. This is where shift-left testing becomes visible. Rather than handing finished software to a separate QA team at the end of a long cycle, tests are written alongside the code and executed automatically on every commit. According to the DORA State of DevOps Report 2023, elite-performing DevOps teams deploy 182 times more frequently than low performers, and automated testing is one of the core capabilities separating those groups.

Phase 5: Release

The tested artefact is approved, either automatically through a fully continuous delivery pipeline or manually through a change-advisory sign-off, and marked as ready for production. Release strategies like blue-green deployments or canary releases mean the UPI toggle can go live for 5% of users first, reducing the blast radius if something goes wrong.

Phase 6: Deploy

Infrastructure-as-code tools such as Terraform or Ansible spin up the target environment, and the container image or package is pushed to production servers or a Kubernetes cluster. Deployment in a mature DevOps cycle is scripted and repeatable, not a manual process that depends on one senior engineer’s memory of the server layout.

Phase 7: Operate

The feature is live. The operations team, or an SRE function, keeps the service healthy: managing uptime SLAs, handling incident response and scaling infrastructure as traffic grows. In many Indian SaaS companies, on-call rotations are now shared between developers and ops engineers, which means the people who wrote the code are also accountable for keeping it running. That accountability changes how carefully code gets written in the first place.

Phase 8: Monitor

Observability tools such as Prometheus, Grafana, Datadog and the ELK Stack collect metrics, logs and traces from the live feature. Is the autopay toggle causing API timeouts? Are drop-off rates higher on Android than iOS? This data feeds directly back into the plan phase, completing the DevOps lifecycle loop and starting the next sprint with real evidence instead of assumptions.

Why the DevOps Lifecycle Infinity Loop Matters

The DevOps lifecycle diagram is almost always drawn as an infinity symbol, and that shape is doing real conceptual work. A line implies a start and an end. The waterfall model is a line: requirements, design, development, testing, deployment, done. The problem is that “done” is a fiction in software. User needs change. Bugs surface in production. Competitors ship features you have not considered yet.

Why Waterfall Struggles Here

Waterfall’s gate-by-gate structure means a requirements error found in the testing phase requires walking back through design and development, a process that can take months. The Standish Group CHAOS Report 2020 found that only 31% of waterfall projects were delivered on time and on budget, compared to 42% for agile-influenced projects. DevOps compounds those agile gains by extending continuous feedback all the way into production.

The loop model also encodes continuous feedback as a first-class engineering input. Monitoring data is the raw material for the next plan phase, not an afterthought. That is a fundamentally different philosophy from delivering a project and handing it over.

The Role of Continuous Feedback in the DevOps Lifecycle Phases

Continuous feedback means every phase produces signals that improve the next iteration. A failed build in phase 3 feeds back to the code phase. A spike in error rates in phase 8 feeds back to phase 1. The speed of that feedback loop is what separates high-performing teams from slow ones. The shorter the loop, the cheaper the mistake and the faster the learning.

For practical DevOps case studies and tool comparisons from working engineering teams, the 3.0 University blog is worth bookmarking as a regular reference.

How Agile, Scrum and DevOps Work Together

Students often ask whether agile DevOps is one thing or two. They are complementary, not the same. Agile is a philosophy for how a team organises its work: short sprints, iterative delivery, working software over documentation. Scrum is the most popular Agile framework, giving that philosophy a concrete structure with sprints, standups, retrospectives and a product backlog.

Where DevOps Picks Up from Agile

Agile answers the question: how does the team decide what to build and in what order? DevOps answers the question: how does what the team built get from a developer’s laptop into the hands of a user in Bengaluru, reliably and quickly? They operate on different parts of the value chain, which is why most mature engineering organisations use both.

A Scrum team might run two-week sprints, which is Agile. But whether those sprint deliverables hit production in two weeks or two months depends on the DevOps practices in place: CI/CD pipelines, automated testing, infrastructure automation and monitoring. Without DevOps, an Agile team can build quickly but still release slowly.

Agile vs DevOps vs Waterfall: A Comparison

Dimension	Agile	DevOps
Primary focus	How the team builds software	How software is delivered and operated
Key framework	Scrum, Kanban, SAFe	CI/CD, SRE, infrastructure-as-code
Team boundary	Primarily development team	Development plus operations, often security
Feedback loop	Sprint retrospectives, stakeholder reviews	Production monitoring, incident data, user telemetry
Delivery cadence	Sprint-based (1-4 weeks)	Continuous, multiple times per day in elite teams
Waterfall contrast	Iterative vs sequential phases	Continuous deployment vs big-bang releases

According to the LinkedIn 2024 Jobs on the Rise report for India, DevOps Engineer and Site Reliability Engineer roles grew by over 40% year-on-year, reflecting how deeply this combined agile-plus-DevOps model has embedded itself in Indian tech hiring, particularly in Bengaluru, Pune and Hyderabad. Understanding both sides of that equation is what employers are actually testing for in interviews.

If you are mapping this to your own career trajectory, it is worth reading about how to future-proof your career in the age of AI, because DevOps skills are increasingly intersecting with AI-driven operations and AIOps tooling.

The AI job market and skills data from 3.0 University’s research team also shows that candidates who combine DevOps knowledge with cloud and automation skills consistently command higher starting salaries in India’s IT sector.

Ready to go deeper? 3.0 University’s bootcamp training programs run cohort-based, project-driven sessions that take you from theory to a working CI/CD pipeline in weeks, not months. The REACH learner community connects you with thousands of students and working professionals navigating the same transition.

The practical next steps for this week: draw the eight-phase loop from memory, identify which phases your current or target employer handles manually, and pick one phase to research in depth. Explore the full catalogue of online certification courses at 3.0 University to find a structured path that fits your schedule and career goals.

Frequently Asked Questions

What are the phases of the DevOps lifecycle?

The DevOps lifecycle has eight phases: plan, code, build, test, release, deploy, operate and monitor. Each phase feeds into the next, and the monitor phase feeds data back into plan, creating a continuous loop. Development and operations teams share responsibility across all eight stages rather than handing work over at a fixed boundary.

What does the DevOps infinity loop mean?

The infinity loop, or figure-eight diagram, represents the fact that DevOps is a continuous cycle with no defined end point. The left side of the loop covers development phases (plan, code, build, test) and the right side covers delivery and operations phases (release, deploy, operate, monitor). Continuous feedback connects both sides in real time.

What is the difference between Agile and DevOps?

Agile is a philosophy for organising how a team builds software, using short sprints and iterative delivery. DevOps covers how that software is delivered to users and kept running in production. Agile without DevOps can still mean slow, manual releases. DevOps without Agile can mean fast delivery of poorly prioritised features. Most successful teams use both together.

Where does testing fit in the DevOps lifecycle?

Testing has a dedicated phase (phase 4) but it actually starts in the code phase through static analysis and unit tests, a practice called shift-left testing. Automated test suites run on every commit, and monitoring in production acts as a final, ongoing quality check. Testing is distributed across the whole lifecycle, not concentrated at one gate.

How does the waterfall model compare with DevOps?

Waterfall runs phases sequentially with formal sign-offs between each stage. A requirement error found late means walking back through multiple phases, which is expensive and slow. DevOps runs phases continuously with automated feedback at every step. The Standish Group CHAOS Report 2020 found waterfall projects succeeded on time and budget only 31% of the time, partly because of this rigidity.

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Last updated: June 2025. Reviewed by the 3University editorial team.