Chapter 1
Foundations of OpenShift Pipelines and Tekton
In this chapter, we deconstruct the pivotal evolution from traditional CI/CD approaches to the deep integration of pipelines within modern Kubernetes environments. By dissecting the architectural underpinnings and motivation behind Tekton and OpenShift Pipelines, we reveal why these technologies have become central to the software delivery lifecycle in cloud-native enterprises. This chapter lays the intellectual groundwork for understanding, customizing, and mastering advanced pipeline operations.
1.1 History and Evolution of CI/CD in Kubernetes
The trajectory of Continuous Integration and Continuous Delivery (CI/CD) in the context of Kubernetes is tightly interwoven with broader transformations in software architecture and infrastructure automation. Initially, traditional CI/CD systems revolved around monolithic tools-most notably Jenkins-which, while revolutionary in their time, began to reveal critical limitations as software delivery processes evolved and infrastructure paradigms shifted.
Jenkins, established in the early 2000s, became the de facto standard for orchestrating CI/CD pipelines. It excelled at automating build, test, and deployment tasks on virtual machines or bare metal servers. However, with the rise of containerization and microservices, the classical Jenkins installation increasingly appeared monolithic and brittle. Since it tightly coupled pipeline logic with the underlying infrastructure, it encountered fundamental challenges related to scaling and portability. The management overhead of Jenkins masters and agents intensified in multi-tenant, cloud-native environments. Furthermore, the static, predefined nature of Jenkins pipelines impeded dynamic adaptation to ephemeral, distributed Kubernetes clusters.
The emergence of Kubernetes, representing a shift toward container orchestration at cloud scale, catalyzed a re-imagination of CI/CD workflows. Kubernetes' declarative API and dynamic scheduling capabilities suggested a fundamentally new model for pipeline execution-one where CI/CD processes are treated as native Kubernetes resources rather than external orchestration tasks. This philosophy facilitates elasticity, fault isolation, and seamless scaling, aligning with microservices' granularity and operational demands.
Early attempts to integrate Jenkins tightly with Kubernetes manifested as the Jenkins Kubernetes Plugin, enabling Jenkins agents to run as pods within clusters. Despite simplifying infrastructure management, this approach inherited Jenkins' overall architectural constraints. Pipelines remained rooted in Jenkins server logic, limiting portability across Kubernetes distributions and complicating pipeline-as-code paradigms. Customizing pipelines to leverage Kubernetes-specific primitives such as Jobs, CronJobs, and custom controllers involved complex scripting and external tooling.
The rise of microservices architectures amplified the demand for modular, composable, and scalable CI/CD pipelines. Microservices decomposed applications into independently deployable units, each requiring frequent, isolated validation and deployment cycles. Traditional monolithic pipelines struggled to support the concurrency and independence required, resulting in longer build queues and reduced developer velocity. Additionally, organizations adopting hybrid and multi-cloud strategies underscored the necessity for pipeline portability across diverse Kubernetes environments.
In response, the cloud-native landscape witnessed the advent of purpose-built CI/CD frameworks designed explicitly for Kubernetes. Notably, Tekton emerged as a seminal innovation, built on Kubernetes Custom Resource Definitions (CRDs) and leveraging the native control loop model. Tekton pipelines are defined as Kubernetes-native resources, which the system reconciles dynamically, enabling declarative, version-controlled workflows that integrate seamlessly with existing Kubernetes tooling.
Tekton addressed key limitations of traditional models by providing a standard API for pipeline components and execution, enabling reusability, composition, and parameterization at granular levels. Its design supports sidecar containers, multiple steps with independent lifecycles, and tight integration with Kubernetes RBAC and secrets management. By executing pipeline tasks as ephemeral pods, Tekton leverages Kubernetes scheduling and scaling capabilities, thereby enhancing fault tolerance and horizontally scaling the CI/CD pipeline across distributed clusters.
Simultaneously, the ecosystem around Tekton matured, encompassing Triggers to initiate pipelines based on events (e.g., GitHub webhooks) and Dashboard components providing observability. This modularity allows organizations to assemble bespoke CI/CD systems tailored to their workflows without being tied to heavyweight, single-vendor solutions. Moreover, Tekton's specifications have laid the groundwork for a portable, vendor-neutral standard, endorsed by the Continuous Delivery Foundation, thereby fostering widespread adoption and interoperability.
In parallel, complementary projects such as Argo Workflows and Flux have enriched the Kubernetes-native CI/CD landscape, emphasizing declarative GitOps methodologies and asynchronous workflow management. These projects illustrate a general paradigm shift from imperative, script-driven pipelines to declarative automation fully integrated within Kubernetes' API machinery.
The adoption of cloud providers' managed CI/CD offerings (e.g., Google Cloud Build, AWS CodePipeline) also reflects this evolution, as their underlying architectures increasingly incorporate Kubernetes-native constructs inspired by Tekton and similar frameworks. The shift in CI/CD tooling thus mirrors the broader migration from monolithic DevOps toolchains towards lightweight, composable, and cloud-agile practices optimized for microservices and Kubernetes orchestration.
The history of CI/CD in Kubernetes encapsulates a progression from traditional, monolithic automation servers to Kubernetes-native, declarative pipeline frameworks capable of addressing modern demands for scalability, portability, and seamless cloud integration. Tekton and its ecosystem epitomize this evolution, enabling continuous delivery workflows that are intrinsically suited to the distributed, dynamic nature of cloud-native software development.
1.2 Tekton Project Architecture
At the core of Tekton's architecture lies a consciously modular and extensible design that fully leverages Kubernetes-native primitives. This design enables Tekton to orchestrate complex continuous integration and continuous delivery (CI/CD) workflows dynamically and declaratively, while maintaining a lightweight footprint within a Kubernetes cluster. The architecture embodies the principles of cloud-native computing by designedly utilizing Kubernetes custom resources and controllers, which affords both flexibility and scalability.
Tekton is implemented as a collection of Kubernetes Custom Resource Definitions (CRDs) along with their corresponding controllers. These CRDs define the key abstractions around pipelines, tasks, and execution state, while the controllers implement the business logic that reconciles the desired state represented by these resources with their actual state in the cluster. This declarative reconciliation ensures that any changes applied via the Kubernetes API are continuously monitored and enacted upon, adhering to Kubernetes best practices.
The primary Tekton custom resources are Pipeline, Task, and PipelineRun (along with TaskRun), which together define and execute CI/CD processes:
- Task: A Task encapsulates a sequence of steps typically realized as containers executing commands. Tasks define reusable units of work with parameters, input/output resources, and results that can be composed into larger workflows.
- Pipeline: Composed of an ordered set of Tasks, a Pipeline defines the flow of tasks and their dependencies. Pipelines can specify conditional execution and parallelism using Kubernetes-native concepts such as resource references and explicit task sequencing.
- TaskRun and PipelineRun: These resources trigger the instantiation of a Task or Pipeline. They carry concrete parameter values, workspace bindings, and resource specifications, serving as execution instances. Their status fields continuously reflect runtime state and logs, updating asynchronously as the workflow progresses.
The Tekton controllers are designed as Kubernetes operators that watch for changes in these custom resources. For example, the PipelineRun controller observes new PipelineRun objects and orchestrates corresponding TaskRun executions according to the defined pipeline graph. Each controller interacts with the Kubernetes API server to create, update, or delete pods that run the individual task steps, relying on native Kubernetes scheduling, networking, and security mechanisms.
A schematic overview can be summarized as follows: user-submitted Pipeline and...
