What slows software teams down more than anything? Misalignment, manual processes, and fragile deployments that break under pressure. Many companies still rely on traditional development workflows that isolate teams and delay releases. These outdated models fall short when systems grow, users scale, and expectations rise.

The DevOps software development life cycle changes this dynamic. It brings development and operations together through a continuous loop of planning, integration, deployment, and feedback. Teams that follow this model move faster, respond to real-time needs, and ship updates with fewer failures. In this guide, we explain how the DevOps cycle works in practice, what each phase involves, and how to build a system that supports speed, collaboration, and consistent delivery.

What is DevOps lifecycle (SDLC)?

The DevOps software development life cycle (SDLC) functions as a continuous loop that unifies development and operations within a shared workflow. It removes traditional silos because teams pursue one objective: they build, release, and improve software quickly without loss of stability or quality. Rather than follow a linear sequence, the DevOps cycle forms a closed loop. Teams plan features, write and integrate code, run tests, deploy builds, monitor performance, and collect feedback—all within one streamlined system. Each phase informs the next and fosters a culture of constant improvement. This model also supports complex engineering tasks such as custom backend development by maintaining consistency and automation across environments.

Source: bigohtech.com

This lifecycle supports rapid iterations by embedding automation at every stage. Developers push code more frequently, QA identifies issues earlier, and operations teams respond faster to incidents. Collaboration and observability stay at the center of the process, which makes the software more reliable and scalable. Unlike legacy development models, the DevOps SDLC adapts to real-world complexity. It helps teams keep up with user demands, production changes, and business goals without creating friction between roles. Key advantages of the DevOps SDLC include:

• Faster release cycles with fewer delays or rollbacks
• Better communication between development, QA, and operations
• Fewer errors due to automation and early testing
• Real-time monitoring and faster incident response
• Higher deployment frequency and system stability
• Stronger alignment between business goals and technical execution

DevOps adoption is widespread, with 86% of businesses utilizing DevOps methodologies to accelerate software releases, according to the report. The global DevOps market is experiencing significant growth, projected to expand from $10.56 billion in 2023 to $25.5 billion by 2028, reflecting a compound annual growth rate (CAGR) of 19.7%. These advantages make the DevOps SDLC a core model for modern teams building scalable and resilient software products.

The 7 phases of the DevOps lifecycle

The DevOps stages form a continuous loop that keeps software projects moving forward with speed and clarity. Each phase supports the next, which can reduce delays and improve the quality of every release. Instead of working in isolation, development and operations teams collaborate through automation, shared responsibility, and rapid iteration. This approach aligns especially well with modern delivery models like saas application development solutions, where frequent updates and operational stability are both important.

Source: napkin.ai

1. Continuous Development

Teams define project requirements, prioritize tasks, and write code based on a shared product vision. This phase starts with stakeholder discussions and backlog refinement, followed by sprint planning and task breakdown. Developers organize features into smaller, manageable units that align with business objectives. Throughout the process, version control tools like Git help track changes, support collaboration, and prevent conflicts. Frequent commits and branching strategies keep the development workflow transparent and adaptive, setting the stage for seamless integration in the next phase.

2. Continuous Integration

After developers write code, they merge their updates into a central repository several times a day. Each integration triggers an automated pipeline that builds the application and runs unit or integration tests. The pipeline helps teams detect bugs early, validate code functionality, and keep a stable baseline. Continuous integration cuts the time teams spend on manual reviews and reveals code conflicts before they reach the wider system. Rapid feedback on every commit preserves code quality and increases the development pace.

3. Continuous Testing

QA teams validate each build and run automated as well as manual tests across varied environments and conditions. They verify functional correctness, performance bottlenecks, usability issues, and security vulnerabilities. Tools such as Selenium, JUnit, and TestNG automate tests, while containerized environments preserve consistency across runs. When issues arise, the build returns to the integration phase for fixes, and the loop closes tightly. Early and repeated tests boost software stability and reduce the risk of flawed code reaching production. These practices are especially important when developing financial applications, where accuracy, auditability, and team alignment are important.

4. Continuous Deployment

Once a build passes all testing stages, it advances to production through fully automated deployment pipelines. Teams use containerization tools like Docker and orchestration platforms such as Kubernetes to deliver updates across staging and live environments with consistent configurations. Infrastructure-as-Code practices help manage environment setup and rollback strategies. Automation reduces human intervention, minimizes downtime, and keeps each deployment under the same tested conditions. This phase lets teams release features faster and more reliably and supports a continuous delivery model without delays or disruptions.

5. Continuous monitoring

After deployment, operations teams monitor application performance, infrastructure stability, and end-user behavior in real time. They use observability tools like Prometheus, Grafana, Datadog, or New Relic to collect metrics, logs, and traces across environments. Monitoring reveals patterns in resource consumption, latency, error rates, and usage trends. When anomalies or failures appear, alerts help teams respond quickly before users experience disruption. This visibility enables incident management and supplies valuable data to inform priorities in the next development cycle.

6. Continuous feedback

Product teams gather input from real user interactions, support tickets, in‑app behavior analytics, and external review channels, and then assess how well the software meets expectations. This feedback highlights usability issues, feature gaps, and unexpected friction points that may not surface during internal tests. Structured surveys and unstructured channels, such as social media, both add insights. Teams analyze these data points, refine the user experience, reprioritize the roadmap, and shape future iterations. Continuous feedback maintains alignment between user needs and product direction and keeps development grounded in real‑world performance.

7. Continuous Operations

This phase focuses on maintaining system reliability, optimizing runtime performance, and minimizing planned or unplanned disruptions. Teams automate infrastructure provisioning, configuration management, and service updates using tools like Kubernetes, Terraform, and Ansible. These practices support consistency across environments and reduce the risk of human error. Continuous operations also involve implementing self-healing mechanisms, load balancing, and fault tolerance to sustain high availability. By managing deployments, updates, and recoveries without downtime, teams deliver stable services while keeping the system ready for future iterations.

Together, these DevOps lifecycle phases build a workflow that scales with complexity and adapts to change. Each stage reinforces the others, allowing teams to release faster, respond sooner, and evolve their products with confidence.

Security within the DevOps lifecycle

Security plays a key role in every phase of the DevOps lifecycle. Instead of treating security as a separate stage at the end of development, teams embed protective measures directly into planning, coding, testing, deployment, and monitoring activities.This approach—often called DevSecOps—keeps software secure and still preserves delivery speed and agility.

During the plan phase, the team sets security requirements alongside functional goals. During development, the team uses static code analysis and secret scans and detects vulnerabilities early. Integration and test stages include automated security checks, container scans, and compliance validation. Deployment pipelines run configuration audits and enforce policy controls across cloud environments. Tools track threats in real time, flag suspicious activity, and assist incident response

DevSecOps helps teams address common risks such as misconfigurations, outdated dependencies, and privilege misuse. Tools like SonarQube, Snyk, OWASP ZAP, and Falco support continuous security validation throughout the software lifecycle. By adopting this model, teams reduce the attack surface, avoid late-stage fixes, and stay compliant with security standards—all without slowing down their DevOps cycle.

How to implement the DevOps cycle in your organization

DevOps cycle requires a structural and cultural transformation across engineering, operations, and product management. It’s not enough to automate isolated steps or install new tools—the organization must shift toward shared ownership of delivery, reliability, and user outcomes. A well-executed DevOps implementation produces long-term benefits: faster time to market, better system resilience, lower failure rates, and stronger collaboration. These steps show how to roll out DevOps at scale while managing complexity and risk:

Source: napkin.ai

• Align teams around shared goals. Start by establishing cross-functional goals that connect development velocity with operational stability and customer satisfaction. Traditional roles often focus on isolated metrics—developers on code delivery, ops on uptime. The DevOps model removes these divisions. Teams collaborate around unified KPIs such as deployment frequency, change failure rate, and mean time to recovery (MTTR). 
• Audit current processes and identify friction. Map how your software flows from idea to release. Highlight repeated delays, manual interventions, duplicated efforts, or unclear ownership. Common signs of inefficiency include environment drift between dev and prod, fragile handoffs between teams, and long lead times for testing or approvals.
• Establish a CI/CD pipeline. Build an integration and delivery pipeline that automatically compiles, tests, and deploys code with minimal manual involvement. A well-built pipeline replaces slow, error-prone handoffs with fast, reliable automation. Use Jenkins, GitHub Actions, GitLab CI/CD, or equivalent tools to run builds on every commit, trigger automated tests, and deploy to staging or production when code passes validation.
• Implement Infrastructure as Code and consistent environments. Infrastructure as Code (IaC) allows teams to manage server configurations, cloud infrastructure, and deployment environments in version-controlled code. Tools like Terraform, Pulumi, and AWS CDK help maintain consistency across development, staging, and production.
• Integrate security early and continuously. DevSecOps practices add security scans and compliance checks at every stage of the SDLC. Teams integrate static and dynamic analysis tools directly into the pipeline, rather than audit only before a release. Open‑source dependency scanners, container vulnerability detectors, and policy‑as‑code frameworks flag risks before they reach production. This shift‑left approach cuts costly late‑stage fixes and promotes a culture of secure development while the DevOps cycle retains full speed.
• Start with one team, then scale. Do not introduce DevOps across every team at once. Select one product or service team to pilot the full DevOps cycle—from a continuous plan and deployment to integrated metrics oversight and feedback loops. Use that team’s experience to refine tools, elevate documentation, and build reusable templates. As confidence rises, roll out DevOps to additional teams and customize workflows when necessary, while you preserve core principles.

When organizations follow the DevOps cycle through these structured steps, they do more than modernize their development process—they build a system that learns, adapts, and scales. Teams deliver software faster, recover from failures more quickly, and answer user needs with confidence. The outcome is a high‑performance environment where engineering efforts align directly with business goals.

Conclusion

Organizations that adopt the DevOps cycle gain faster delivery times, fewer deployment failures, and greater agility under changing conditions. When combined with Infrastructure as Code, real-time observability, and built-in security, the DevOps model scales with complexity while keeping software aligned with user needs. To make the most of this approach, teams must commit to shared ownership, automation, and continuous feedback. DevOps is not a one-time change—it’s a cycle that improves with every release.

FAQ

What is the purpose of the DevOps lifecycle?

The DevOps lifecycle promotes constant collaboration between development and operations teams, which delivers software faster and with greater reliability. Each phase—from plan to monitoring—links through automated workflows that cut delays and manual errors. The objective is faster releases, higher quality, and stable, scalable systems under real‑world conditions. When teams view delivery as a continuous loop rather than a single event, they respond more quickly to user needs and system feedback.

Is DevOps a part of SDLC or separate?

DevOps extends the traditional software development life cycle (SDLC) by integrating operations into every stage of the process. It is not a separate methodology but an evolved model that overlays automation, feedback, and shared ownership onto the core phases of SDLC. Unlike linear approaches, the DevOps cycle operates continuously to support rapid and repeatable software delivery.

What does DevSecOps add to the DevOps lifecycle?

DevSecOps integrates security into every phase of the DevOps lifecycle rather than placing it at a final checkpoint. It adds automated security tests, compliance checks, and real‑time threat detection across development, integration, deployment, and monitor stages. This approach reduces the risk of late‑stage vulnerabilities and helps teams maintain security without release delays. In a DevSecOps model, secure code practices, dependency scans, and policy enforcement operate in parallel with development and delivery.