DevOps Lifecycle: Definition, Key Components, Best Practices
The DevOps lifecycle is a set of continuous and collaborative practices that bridge the gap between software development and IT operations, promoting seamless integration, automation, and faster delivery of software. The DevOps lifecycle phases include:
What Is DevOps?
DevOps is the merging of cultural beliefs, methods, and technology that enhances an organization's capacity to provide applications and services quickly. This enables the continual enhancement of products at a faster rate compared to organizations employing conventional software development and infrastructure management procedures.
Previously, without DevOps, developers had to build the code, ship, and integrate it, and only then would the IT Ops team start to package and deploy the code. This requires a lot of back-and-forth communication between the teams when something goes wrong. DevOps removes the boundaries between the two teams (distinct roles, responsibilities, work silos) and brings them closer together in a collaborative and integrated manner.
What Is the DevOps Lifecycle?
The DevOps lifecycle is the continuous and iterative set of practices and processes that facilitate the integration and collaboration between software development (Dev) and IT operations (Ops) teams. It aims to streamline the development and delivery process, ensuring faster and more reliable releases while still maintaining a high level of quality.
Below is the DevOps Lifecycle diagram — a closed and continuous infinity cycle, representing the iterative flow of stages involved. The first round includes plan, code, build, and test, which are the four major activities of the Dev team, while the second round includes deploy, operate, feedback, and monitor, the four major activities of the Ops team. DevOps tools are usually utilized across the lifecycle to simplify the process.
Stages of the DevOps Lifecycle Explained
Exactly as its name suggests, this stage involves planning the entire project lifecycle. During this stage, the three essential stakeholders hold meetings to discuss the project requirements (collected from customers, internal/external experts/managers) and perform necessary analysis to come up with a strategic approach to building the application.
During this stage, details on resource allocation, project timeline, team structures, tech stack, tools, and risk mitigation approaches are also decided.
Before the coding stage, there can be a preliminary Design stage where software engineers analyze and identify the best solutions to create the software. For example, they can decide on an appropriate architectural pattern that best fits the project's needs, then break down the system architecture into smaller, more manageable components.
At this point developers start to work on the code. Version control systems, like Git, are used to manage code changes and enable collaboration among team members.
With the new code ready, it is now time for developers to integrate code changes into a shared repository, ideally multiple times a day. Continuous integration (CI) plays a crucial role here, which ensures that any integration issues are detected and resolved early on, so that the codebase is always in a consistent and working state.
Once the developers commit code and the lead developer approves, the CI process is triggered, initiating the build process. The CI server will compile the source code into low-level machine code that can be executed. CI tools also identify the dependencies, such as external libraries, frameworks, and modules required for the code to run properly. The output of this build process is a “build artifact,” an executable and deployable form ready for testing and distribution to end users.
This is a critical phase to ensure the software’s quality and reliability. A wide variety of tests are performed to validate all aspects of the build, including functionality, performance, aesthetics, security, and more. The approach to testing should be carefully defined in the test strategy document while specific test scenarios and details on test operations are noted in the test plan.
Automated testing is key to DevOps as it enables faster and more reliable verification of code changes, reduces manual effort, and facilitates continuous integration (CI) and continuous delivery (CD). Testers need to perform automated testing at all levels, including unit, integration, and system testing.
- Unit testing: to verify the functionality of individual units of code
- Integration testing: to verify the flow of data between different code units or components, ensuring that they communicate effectively with each other
- System testing: to test user interaction in an environment as closely related to the production environment as possible
To automate those tests, QA teams usually have to choose between two options: either creating automated test scripts on their own using test automation frameworks like Selenium and Appium, which requires a certain level of technical expertise or investing in an automation testing tool that offers low-code test-script creation. The decision to choose between build vs. buy is up to the capabilities of each team.
After test execution, there should be detailed reports over the test results, providing in-depth insights into which tests passed, failed, and if any defects were discovered. The results from these test sessions should help QA teams address issues promptly.
During this phase, the code that has been thoroughly tested is released and deployed to different environments, including staging, UAT, and production. The software/application is now available for users to access and interact with, but the level of access differs for each:
- The staging environment (also known as a preproduction environment) is a near exact replica of a production environment for software testing. These environments bridge the development environment with the production environment, providing a preview of how the software works and ensuring it aligns with stakeholders’ expectations.
- The UAT environment is where the code is deployed after software testing is completed on staging. It is also a near exact replica of the production environment, but customers or product owners perform testing here instead of the QA team.
- The production environment is where the final deployment is done. Also called the “live” environment, all customers can interact with it in real time. During this stage, bugs are not expected to be found. If a bug is found, the QA will immediately be alerted.
Automated deployments are extremely valuable to create a seamless flow, simplifying the deployment process and reducing human errors. It is also the key to achieve continuous deployment, where software changes are automatically pushed to production environments as soon as they pass automated tests.
Read More: Best 14 CI/CD Tools You Should Know
Once the software is deployed, it enters the operational phase, where it is fully available for use by end users. A dedicated operations team will take over the management of the software in the production environment, performing many tasks to keep it running smoothly, ensure its availability, and make optimization decisions to bring better experience to the users.
Ideally this team utilizes monitoring tools to collect and analyze real-time data from all components of the software stack, including servers, databases, networks, or application metrics to be constantly updated on its health. If any deviant behavior is detected based on a preconfigured threshold, these tools can send alerts to the team so that they can be proactive in resolution.
This stage also involves capacity management, ensuring that high volumes of users can access the software while not eating up too much of the available resources. Based on historical usage data, the Operations team can predict future resource requirements to handle unexpected demand.
Finally, the Ops team creates a feedback loop by sending the operational data collected to the Dev team, helping them identify areas for improvement, track the KPIs, and assess if any changes to the software are needed. The DevOps lifecycle begins again, and each of these iterations leads to an enhanced version of the software.
7Cs of the DevOps Lifecycle
You can also view the DevOps lifecycle as a holistic “7C” phase approach:
- Continuous development
- Continuous integration
- Continuous testing
- Continuous deployment/Continuous delivery
- Continuous feedback
- Continuous monitoring
- Continuous operations
1. Continuous Development
Continuous development fosters a culture of collaboration among developers, testers, and other stakeholders. Instead of incorporating changes in one large batch, developers make small, piece-by-piece changes to the software, such as bug fixes, new features, code improvements, and code refactoring. Development becomes a series of small iterations that gradually add value to the software.
The idea behind continuous development is to make the effort more manageable, minimizing the risks of large-scale failures and allowing organizations to be more responsive to user needs and constantly changing market demands.
For continuous development, dev teams usually leverage Git — the most popular version control system for collaborative code development and easy code branching and merging — while GitHub, GitLab, and Bitbucket are popular web-based platforms for hosting and managing Git repositories.
2. Continuous Integration
After the code has been written, it is committed to the shared repository, where a series of events to seamlessly integrate the code is put into motion. This is also known as the CI pipeline:
- Detect changes in the source code repository (new commits appear)
- Source code quality analysis
- Execute all unit tests
- Execute all integration tests
- Generate deployable artifacts
- Report status
If one of the steps above unfortunately fails:
- Integration may stop or continue depending on defect severity and configuration
- Results are notified to the team via email or chat system
- The team fixes defects and commits again
- Tasks are performed again
For CI, Jenkins is a widely used open-source CI/CD automation server. It allows developers to automate various aspects of the software development process, including building, testing, and deploying code changes.
3. Continuous Testing
Continuous testing involves the automation of testing activities to ensure that software changes are validated at each step of the pipeline, providing fast and reliable feedback to the development team, without the need for human intervention. The time saved thanks to continuous testing can be better spent on more strategic and planning tasks.
Read More: Top 15 Automation Testing Tools
For example, you can leverage Katalon Platform for continuous testing. With Katalon, you can create, manage, execute, and analyze tests for web, API, desktop, and even mobile applications across a wide variety of environments, all in one place, with minimal engineering and programming skill requirements.
You can create tests without any code thanks to Built-in Keywords, which are essentially code snippets that can be dragged and dropped together to construct a full test script, or the Record-and-Playback feature, which can record the sequence of activities conducted on screen and turn it into a test script. Katalon even comes with advanced AI testing features that enable autonomous test generation.
Going beyond test creation, Katalon also comes with many features that facilitate the entire Software Testing Life Cycle (STLC):
- Manage all test cases, objects, artifacts in an Object Repository
- Execute tests locally, remotely, or on-cloud for a wide variety of environments
- Integrate seamlessly with your CI/CD pipeline and the latest collaboration tools
- Smart reporting for better decision making
4. Continuous Deployment/Continuous Delivery
Continuous deployment and continuous delivery are two closely related practices in the DevOps world, although they still have distinct differences.
Continuous delivery ensures that software changes are automatically and consistently delivered to production or staging environments after passing through an automated build, test, and validation process. The final decision to deploy the software to production lies with human operators or stakeholders. They can choose when to trigger the deployment.
Continuous deployment takes continuous delivery one step further by fully automating the deployment process to production without any human intervention.
5. Continuous Feedback
In this stage, user feedback is continuously collected to provide insights into how to optimize the codebase. You can set up automated mechanisms to collect feedback, such as automated user feedback surveys, automated error reporting, and automated monitoring systems that collect performance and usage metrics.
Several channels to provide feedback include:
- Feedback forms that pop up in the application when a certain series of events happen
- Support tickets
- Community forums
6. Continuous Monitoring
It should be noted that monitoring activities have always been fairly continuous. Monitoring is all about gaining real-time visibility into the performance and behavior of a system, providing continuous and up-to-date insights into various metrics. Continuous monitoring takes this one step further by placing emphasis on three key factors:
- Real-time data collection and analysis
- Proactively and constantly respond to risks
- Ongoing data analysis
In many ways, the idea and goals of continuous monitoring are similar to continuous delivery, which is to help organizations move faster with accuracy and efficiency.
7. Continuous Operations
Continuous operations focuses on the ongoing management and maintenance of software systems in production environments, ensuring that the system remains stable, secure, performant, and available to users throughout its lifecycle. Continuous operations include the following key aspects:
- Indirect response and management: detecting and responding to incidents and outages in the production environment. When issues occur, the operations team works to identify the root cause and takes corrective actions to restore normal operations.
- Change management: any updates or changes to the software or infrastructure are carefully planned, tested, and rolled out to minimize disruption and risk.
- Monitoring and alerting: monitoring tools collect real-time data and metrics to provide insights into the system's behavior. Alerting mechanisms notify the operations team when predefined thresholds or conditions are breached.
- Backup and recovery: regular backups are taken to protect data, and disaster recovery plans are prepared to minimize downtime in case of major failures.
DevOps vs. DevSecOps
DevSecOps incorporates security practices into DevOps, achieving rapid delivery while making no compromises to security. In DevSecOps, every stakeholder has their own responsibility in making the codebase more secure.
Here is a comparison table between DevOps and DevSecOps:
Collaboration between development and operations teams to improve software development and delivery processes.
Integration of security practices into the DevOps culture to ensure security throughout the software development lifecycle.
Continuous integration, continuous delivery, automation, collaboration, feedback loop.
Shift-left security, automation of security testing, collaboration between Dev, Ops, and Security teams, continuous Security, secure access management.
Streamline development and operations, accelerate software delivery, and improve collaboration.
Enhance security posture, minimize vulnerabilities, and deliver secure software efficiently.
Emphasizes speed, efficiency, and quality in software development and delivery.
Focuses on security considerations from the early stages of development to production deployment.
Security may be considered in later stages or as an additional process.
Security is integrated into every stage of the software development lifecycle.
Security practices may be ad hoc or separate from the main development process.
Security practices are automated, continuous, and integrated throughout the CI/CD pipeline.
Promotes collaboration between development and operations teams.
Fosters a culture of shared responsibility for security among Dev, Ops, and Security teams.
Automation is primarily focused on the development and delivery process.
Automation includes security testing, vulnerability scanning, and security controls as code.
Faster software delivery, increased collaboration, and improved quality.
Reduced security risks, enhanced software security, and increased customer trust.
Security vulnerabilities may be discovered late in the development process.
Integrating security practices may require cultural and organizational changes.
Continuous integration, continuous deployment, infrastructure as code, automated testing.
Threat modeling, automated security testing, secure configuration management, container security.
4 Best Practices for DevOps in 2023
- Shift left with CI/CD: With CI/CD, developers continuously integrate code changes into a shared repository, and automated tests are run to validate the changes. By shifting testing and validation left in the development process, issues are detected and resolved earlier, reducing the cost and effort required to fix problems later in the development lifecycle.
- Set up automated testing: Automated testing is the core of DevOps. More than just testing, QA teams need a comprehensive quality management platform that helps them plan, organize, create, execute, and analyze their tests. Selecting a testing tool that integrates seamlessly with CI/CD pipeline is crucial to establishing a true DevOps culture.
- Embrace infrastructure as code (IaC): Infrastructure as code is a practice where infrastructure resources, such as servers, networks, and storage, are defined and managed through code. IaC allows for rapid and repeatable deployments, and DevOps teams can spin up or tear down infrastructure resources quickly to meet changing requirements, scale applications, or respond to spikes in demand.
- Switch to microservices: These services can be deployed and operated independently and communicate with each other through a web interface. In a microservices architecture pattern, different languages or frameworks can be used for writing these services, and they can be deployed individually or as a group. This decoupling aligns with the principles of DevOps, where development and operations teams work on small, focused components, allowing for faster development cycles and parallel workstreams.
Validates system behavior in real-world scenarios
Validates integration between components
Broader in scope and cover the entire technology stack of the application
Interaction between different components/modules
More expensive as it often requires more resources, including personnel, equipment, and testing environments.
Less expensive than end-to-end testing
Performed at the end of the software development lifecycle before releases
After unit testing and before end-to-end testing
Black-box testing, often uses User Acceptance Testing (UAT)
White-box testing, often uses API testing