Continuous integration and continuous delivery (CI/CD): The impact on DevOps and Unpacking the purpose and importance of an IT cultural revolution

The increase in demand for digital services since 2020 represents a lasting trend that is anticipated to intensify further. In order to remain competitive, organizations must ensure both speed and reliability in the introduction of new products and services to the market. To address this demand, many organizations are implementing DevOps methodologies, including continuous integration and continuous delivery, along with the associated practice of continuous deployment, collectively known as CI/CD. CI/CD encompasses a series of interrelated processes that enable developers to create high-quality software through streamlined and automated development, testing, delivery, and deployment. These practices foster improved collaboration and enhanced efficiency for DevOps teams throughout the software development lifecycle. It is essential to understand these software development methodologies, their interconnections, and the advantages they provide to DevOps teams as they seek to optimize and automate various processes, ultimately achieving a quicker time to value for their customers.

Continuous integration streamlines development

According to survey findings, continuous integration (CI) is a software development methodology that enhances the internal processes involved in software creation. Through CI, multiple developers can collaborate on various features or modules of the same application, committing their updates to a shared code repository upon completion, often multiple times within a single day. When developers check in their code, the build management system automatically generates a build and conducts tests. Should any tests fail, the system alerts the team to rectify the code. This methodology enables software teams to swiftly identify and address any bugs that may arise during the development phase.

Moreover, continuous integration mitigates the risk of "merge hell," a situation that can occur when multiple developers unintentionally introduce conflicting changes that disrupt the build upon merging back into the master branch. It also prevents teams from having to reconcile large volumes of conflicting or redundant code, which could necessitate code freezes or a separate integration phase in the development pipeline.

By continuously integrating incremental changes, developers can make modifications without the concern of disrupting others' work or having their own contributions overwritten. This seamless and regular merging process allows software development teams to complete projects more swiftly and effectively. Additionally, it guarantees the availability of a testable, up-to-date build that compiles correctly, which is essential for frequent and thorough application testing.

This strategy conserves time and resources that would otherwise be allocated to resolving issues later in the software development life cycle, or, even more critically, after release, when addressing such issues becomes significantly more challenging.

Continuous delivery ensures code is always ready to deploy

Continuous delivery (CD) is a methodology employed by DevOps teams to develop and transfer complete segments of software to a repository, such as GitHub or a container registry, in brief, regulated cycles. The primary objective of continuous delivery is to establish regular and predictable release schedules for DevOps personnel while ensuring a smooth experience for end-users.

Additionally, continuous delivery aims to maintain the code in a deployable condition at all times, allowing for immediate updates with minimal or no complications. DevOps teams can streamline CI/CD pipelines to facilitate the movement of code through the designated environments without human intervention, thereby expediting the build, testing, and deployment phases of software development, as well as any other stages they may have implemented based on their specific processes.

For instance, when a feature is prepared for client presentation, the DevOps team can utilize a CD tool to automatically deploy it to a test server, enabling the client to evaluate its functionality and provide feedback prior to its deployment on the production server.

Continuous deployment guarantees that customers consistently receive the most up-to-date version.

Continuous deployment, commonly referred to as CD, represents an advancement of continuous delivery. In this model, builds that successfully pass testing are automatically deployed to production environments on a daily or even hourly schedule.

This approach accelerates the feedback loop with customers and alleviates the workload on operations teams by automating the subsequent phase in the deployment pipeline.

Once an organization has established stable and mature continuous delivery practices, it frequently transitions to automated continuous deployment and testing through a tiered "blue-green" strategy. In this method, the new build (green) is deployed alongside the current build (blue) to verify its functionality before the blue build is decommissioned. Additionally, teams may implement a phased "canary" deployment strategy, wherein the new build is incrementally introduced to replace the existing build.

Continuous Delivery versus Continuous Deployment: What is the distinction in CI/CD?

Continuous delivery (CD) is frequently mistaken for continuous deployment (CD). When individuals discuss CI/CD practices, it is essential to clarify whether they are referring to continuous delivery, continuous deployment, or both.

In essence, the term can denote either continuous delivery or the combination of continuous delivery and continuous deployment. While these concepts are interconnected, they pertain to automated processes that occur at distinct stages within the delivery workflow.

One can conceptualize the adoption of these practices as a three-step progression in the realm of DevOps automation:

1. Continuous integration, which enhances development efficiency by automating the building and testing processes. This approach allows multiple developers to collaborate on the same codebase simultaneously.

2. Continuous delivery, which automates the transition of completed code segments into the main branch, making them ready for deployment to a production environment by the operations team. This step enables the development segment of a DevOps team to streamline the testing and committing of code.

3. Continuous deployment, which automates the actual deployment of completed and tested code into a production environment. This process allows the operations segment of a DevOps team to facilitate the delivery of new code to customers seamlessly.

When organizations initially embrace agile DevOps methodologies, they typically begin with continuous integration and quickly evolve into continuous delivery, thereby achieving CI/CD. However, many organizations choose to halt their progress at this stage, opting for manual production code releases. Others advance to continuous deployment to fully automate the software development, delivery, and deployment pipeline.

The benefits of CI/CD

The primary advantage of continuous integration and continuous delivery lies in its ability to significantly shorten the development time for applications and features. This efficiency provides organizations with a competitive edge over those that continue to rely on traditional, manual software development methods.

In addition to this competitive edge, CI/CD empowers agile development teams to consistently iterate and introduce new features. These methodologies ensure that all team members are collaborating on the same version of the code while they develop and enhance features and functionalities. With the processes of integration and testing automated, engineers can concentrate on their core competency: coding.

For teams that have adopted continuous deployment, code experiences reduced delays in testing and deployment, allowing it to spend more time in production. This shift accelerates user feedback and ultimately leads to improved business results.

The benefits of enhanced efficiency, shorter time to market, and faster innovation render CI/CD an appealing strategy for organizations across various sectors.

Augment?the?DevOps?pipeline with AI

Each phase of the DevOps pipeline necessitates a certain level of analysis to inform decisions, responses, and automation processes.

For instance, accurate AI-driven analysis can influence decisions regarding the deployment of software, and once the software is operational, it can assess whether the release is functioning as intended. Additionally, in the event of unsuccessful test executions, AI can pinpoint the exact root cause, down to the specifics of the underlying code, enabling developers to swiftly resolve and correct issues.

The capacity to analyze data with precision and dependability, and to deliver conclusive answers, empowers teams to automate various processes throughout the software delivery lifecycle. Trustworthy, AI-generated insights are essential for prompt incident response and automated remediation, allowing teams to grasp the context surrounding a failure or error.

This application of artificial intelligence in IT operations (AIOps) is increasingly becoming a common practice, particularly as organizations embrace cloud-native infrastructures.

Adopt a platform-driven approach with self-service processes

Achieving extensive success in DevOps necessitates a platform-centric approach that facilitates structural transformations within organizations, thereby enhancing team collaboration. A primary objective is to create self-service mechanisms for the management of various testing, monitoring, alerting, CI/CD workflows, internal infrastructure, development environments, and public cloud resources. When teams are equipped with dependable data and analytical tools, and when individuals are empowered to utilize their expertise, organizations can amplify the benefits of DevOps across the entire enterprise.

By providing self-service access to APIs, tools, services, and support through a unified platform that incorporates AI and automation, teams gain a consistent and trustworthy source of information and coordination. This capability allows teams to integrate and optimize their DevOps toolchains and processes, enabling them to allocate more time to innovation rather than infrastructure maintenance.

DevOps has the potential to significantly transform enterprises by fostering a culture that embraces experimentation, risk-taking, and trust among team members. This environment encourages continuous feedback, which is essential for success. However, cultural change alone is insufficient; organizations must also adopt appropriate technologies and DevOps software to facilitate their objectives.

As the landscape of tools and technologies expands, a vital capability emerges: observability. This refers to the ability to instrument and monitor telemetry data throughout the cloud-native ecosystem. It encompasses metrics, logs, distributed traces, and user experience data, as well as the latest open-source standards, all aimed at assessing the health of applications and their underlying infrastructure at every development stage.

A recent report from Gartner emphasizes that leaders should explore solutions during the pre-production phase to enhance insights into application performance, service availability, and overall environmental health.

Additionally, there is a growing trend to incorporate various disciplines into the DevOps framework. For instance, "DevSecOps" teams focus on integrating security testing within delivery and deployment pipelines, while "BizDevOps" initiatives aim to evaluate application performance from the perspective of user experience.

While the benefits of DevOps are evident, the cultural and technological shifts it necessitates can render the implementation of DevOps solutions a gradual and iterative process.

The motivation to enhance and automate additional continuous integration and continuous deployment processes.

To meet competitive demands, organizations know they must release new products and services more quickly than ever without compromising quality or reliability. They know basic CI/CD practices are fundamental to DevOps and DevSecOps initiatives that look to develop applications with more effective collaboration and greater precision.

Teams that implement CI/CD practices successfully rely on many tools and methods to manage features, versions, testing, and builds. Automation happens at every stage of the pipeline, from building, packaging, and testing to pushing applications to different production environments.

To accelerate the development pipeline for ever-faster releases with less risk, teams need continuous automation and advanced AI-driven observability across all the tools in their DevOps toolchain so they can automate manual steps and identify quality issues earlier in the software lifecycle.

If your organization uses or is considering adopting CI/CD DevOps processes, a best practice is to implement a full-stack observability platform that can provide code-level visibility of all software builds, apps, and services in your environment, whether they’re in development or deployed to end-users.

The Dynatrace Software Intelligence Platform continuously and automatically monitors the performance of DevOps tools, and seamlessly integrates with CI/CD workflows. With improved collaboration on a single platform and a shared data model, you can ensure your entire team has continuous situational awareness across the lifecycle.

Jasmeet Singh

Project Manager Senior- Technology

FIS