Open Source DevOps and Container Tools
In This Guide
What DevOps Means in Practice
DevOps is a set of practices that combines software development and IT operations to shorten the development lifecycle while delivering features, fixes, and updates frequently and reliably. The term was coined around 2008 and 2009, emerging from conversations between software developers and system administrators who recognized that traditional handoffs between teams created bottlenecks, miscommunication, and slow release cycles.
In practice, DevOps is not a single tool or product. It is a culture built on automation, measurement, and collaboration. Development teams write code, commit it to version control, and expect automated systems to test, build, package, and deploy that code with minimal manual intervention. Operations teams, in turn, manage infrastructure through code rather than manual configuration, making environments reproducible and auditable.
The core feedback loop in DevOps starts with planning, moves through coding, building, testing, releasing, deploying, operating, and monitoring, then feeds observations back into the next planning cycle. Each stage benefits from automation, and open source tools exist for every step. A working DevOps pipeline might use Git for version control, Jenkins or GitLab CI for continuous integration, Docker for containerization, Kubernetes for orchestration, Terraform for infrastructure provisioning, and Prometheus for monitoring. None of these tools require a paid license.
What separates DevOps from earlier approaches like Agile or ITIL is the emphasis on breaking down organizational walls. Developers own their code through deployment. Operations engineers write code to manage infrastructure. Both groups share responsibility for uptime, performance, and user experience. The tools described in this guide exist to make that shared responsibility practical, repeatable, and scalable.
Why Open Source Dominates DevOps
Open source software holds an outsized position in the DevOps ecosystem compared to other technology categories. The reasons are structural, not accidental. DevOps workflows require interoperability between dozens of tools, and open source projects with public APIs and documented protocols make integration straightforward. A proprietary CI/CD system can lock you into a specific vendor's container registry, artifact store, and deployment target. An open source CI/CD system works with whatever you point it at.
Cost matters as well. DevOps tooling runs at every layer of the stack, from developer workstations to build servers to production clusters. Licensing costs at that scale can be substantial. Open source tools eliminate license fees entirely, shifting costs to infrastructure and the engineering time needed to operate the tools. For many organizations, especially startups and mid-size companies, that trade-off is favorable.
Community velocity is another factor. The pace of change in infrastructure technology is relentless. Container runtimes, orchestration platforms, and deployment strategies evolve faster than any single vendor can track. Open source projects with large contributor bases, like Kubernetes with its thousands of contributors, absorb and respond to changes faster than proprietary alternatives. When a new cloud provider launches or a new security standard emerges, the open source ecosystem adapts in weeks rather than quarters.
Transparency and auditability also play a role. DevOps tools handle sensitive operations: deploying production code, managing secrets, provisioning cloud resources. Organizations with compliance requirements often prefer tools where they can inspect every line of source code. Open source tools offer that transparency by definition.
Finally, open source DevOps tools serve as a shared language across the industry. Engineers who know Docker, Kubernetes, Terraform, and Jenkins can move between companies and hit the ground running. This portability of skills creates a self-reinforcing cycle: companies adopt open source tools because engineers know them, and engineers learn them because companies use them.
Containers: Docker, Podman, and the OCI Ecosystem
Containers changed how software is packaged and deployed. A container bundles an application with its dependencies, libraries, and configuration into a single artifact that runs consistently across development laptops, CI servers, and production clusters. Unlike virtual machines, containers share the host operating system's kernel, making them lightweight and fast to start.
Docker popularized containers starting in 2013. It introduced a simple command-line interface for building container images from Dockerfiles, running containers from those images, and sharing images through registries like Docker Hub. Docker made containers accessible to developers who had no background in Linux namespace isolation or cgroup resource controls. The Dockerfile format became a de facto standard for defining container builds.
The container ecosystem has matured significantly since Docker's early days. The Open Container Initiative (OCI), founded in 2015 by Docker, CoreOS, Google, and others, established open standards for container image formats and runtimes. These standards mean that a container image built with Docker can run on any OCI-compliant runtime, and vice versa. The three key OCI specifications are the Image Spec (how images are structured), the Runtime Spec (how containers are executed), and the Distribution Spec (how images are pushed and pulled from registries).
Podman is the most prominent Docker alternative. Developed by Red Hat, Podman provides a Docker-compatible CLI that runs containers without a central daemon process. Docker requires a long-running background daemon with root privileges, which has been a security concern for some organizations. Podman runs each container as a child process of the user who started it, enabling rootless container execution by default. Podman also supports pods, groups of containers that share network and storage namespaces, mirroring the Kubernetes pod concept.
Beneath both Docker and Podman sit lower-level container runtimes. containerd, originally developed by Docker and donated to the Cloud Native Computing Foundation (CNCF), is the industry-standard container runtime used by Docker Engine, Kubernetes, and many cloud providers. It handles image pulling, container execution, and storage management. runc, also a CNCF project, is the reference implementation of the OCI Runtime Spec that actually creates and runs containers using Linux kernel features. Most users never interact with containerd or runc directly, but they are the foundation that higher-level tools build on.
Buildah and Skopeo round out the Red Hat container toolchain. Buildah builds OCI container images without requiring a running daemon, and it can create images from scratch without a base image. Skopeo copies container images between registries without pulling them to the local machine first, which is useful for CI/CD pipelines that need to promote images between staging and production registries.
Choosing between Docker and Podman often comes down to your environment. Docker has the largest ecosystem of documentation, tutorials, and third-party integrations. Podman offers stronger security defaults and better alignment with Kubernetes concepts. Both produce OCI-compliant images, so the containers themselves are interchangeable.
Container Orchestration with Kubernetes
Running a single container on a single server is straightforward. Running hundreds or thousands of containers across a cluster of servers, keeping them healthy, scaling them based on demand, routing network traffic between them, and rolling out updates without downtime, that requires an orchestration platform. Kubernetes is the dominant solution.
Google released Kubernetes as an open source project in 2014, drawing on fifteen years of internal experience running containerized workloads with its Borg and Omega systems. The Cloud Native Computing Foundation (CNCF) became its home in 2015, and it has grown into one of the largest open source projects in history with over 88,000 GitHub stars and contributions from thousands of engineers at hundreds of companies.
Kubernetes organizes containers into pods, the smallest deployable units, which share network and storage resources. Deployments manage groups of identical pods, handling rolling updates and rollbacks. Services provide stable network endpoints that route traffic to the correct pods even as they are created and destroyed. Ingress resources manage external HTTP traffic, and ConfigMaps and Secrets store configuration data and sensitive credentials separately from container images.
The learning curve for Kubernetes is steep. A minimal production cluster requires understanding at least a dozen resource types, YAML manifests, RBAC (role-based access control), networking plugins (CNI), storage classes, and the kubectl command-line tool. This complexity is justified for organizations running many services at scale, but it can be excessive for smaller deployments.
Lightweight Kubernetes distributions address this problem. k3s, created by Rancher Labs (now part of SUSE), packages Kubernetes into a single binary under 100 MB that runs on everything from Raspberry Pi devices to edge servers. It replaces etcd with SQLite by default, bundles a container runtime and load balancer, and starts in seconds. k0s from Mirantis takes a similar approach, providing a zero-friction Kubernetes distribution with minimal dependencies. MicroK8s from Canonical offers a snap-based Kubernetes for development and IoT use cases.
For teams not ready for full Kubernetes, Docker Swarm provides simpler container orchestration built into the Docker Engine. HashiCorp's Nomad is another alternative that orchestrates not just containers but also virtual machines, Java applications, and raw binaries. Nomad has a smaller feature set than Kubernetes but is significantly simpler to operate.
CI/CD: Continuous Integration and Delivery
Continuous Integration (CI) is the practice of merging developer code changes into a shared repository frequently, at least once a day, and validating each merge with automated builds and tests. Continuous Delivery (CD) extends this by automating the release process so that code can be deployed to production at any time with confidence. Together, CI/CD forms the backbone of modern software delivery.
Jenkins is the oldest and most widely used open source CI/CD server. Originally released as Hudson in 2004, it was forked and renamed Jenkins in 2011. Jenkins runs on Java and supports an enormous plugin ecosystem with over 1,800 plugins covering everything from source control integration to cloud deployment. Its Pipeline feature, defined in Jenkinsfiles using a Groovy-based DSL, allows complex multi-stage build and deployment workflows to be stored as code alongside the application. Jenkins can run on a single server or scale across a cluster of build agents.
GitLab CI/CD is tightly integrated into the GitLab source code management platform. CI/CD pipelines are defined in a .gitlab-ci.yml file at the root of each repository, and GitLab handles everything from triggering builds on commits to deploying artifacts to production environments. The self-hosted GitLab Community Edition includes CI/CD at no cost, making it a popular choice for organizations that want source control and CI/CD in a single platform.
Several newer tools have gained traction. Tekton is a Kubernetes-native CI/CD framework that defines pipeline components as Kubernetes custom resources. This means pipelines are managed, scheduled, and scaled by Kubernetes itself. Argo CD focuses specifically on the continuous delivery side, implementing GitOps principles where the desired state of a Kubernetes cluster is declared in a Git repository and Argo CD continuously reconciles the cluster to match. Drone (now Harness Open Source) provides a container-native CI platform where every step in a pipeline runs in its own container, ensuring clean and reproducible builds.
Woodpecker CI, a community fork of Drone, offers a lightweight CI/CD engine with a simple YAML-based configuration, support for multiple version control platforms, and a clean web interface. It runs entirely in containers and is straightforward to self-host.
Choosing a CI/CD tool depends on your existing infrastructure. If you already run GitLab, its built-in CI/CD is the natural choice. If you run Kubernetes and want native integration, Tekton or Argo CD fit well. If you need maximum flexibility with deep plugin support, Jenkins remains the most configurable option despite its age.
Infrastructure as Code
Infrastructure as Code (IaC) is the practice of managing and provisioning computing infrastructure through machine-readable configuration files rather than manual processes or interactive tools. IaC makes infrastructure reproducible, version-controlled, and testable, bringing the same discipline to operations that source control brought to software development.
Terraform, originally created by HashiCorp, is the most widely adopted IaC tool. It uses a declarative configuration language called HCL (HashiCorp Configuration Language) to define cloud resources across AWS, Azure, Google Cloud, and dozens of other providers. You write .tf files describing the infrastructure you want, run terraform plan to preview changes, and run terraform apply to create or modify resources. Terraform tracks the current state of your infrastructure in a state file, comparing it against your configuration to determine what needs to change.
OpenTofu is an open source fork of Terraform, created in 2023 after HashiCorp changed Terraform's license from the Mozilla Public License to the Business Source License. OpenTofu is maintained by the Linux Foundation and aims to remain a fully open, community-driven alternative to Terraform. It is compatible with existing Terraform configurations and providers, making migration straightforward. For organizations concerned about licensing restrictions, OpenTofu provides the same capabilities under a permissive open source license.
Ansible, developed by Red Hat, takes a procedural approach to infrastructure management. Instead of declaring the desired state, Ansible playbooks define a sequence of tasks to execute on remote servers over SSH. No agent software needs to run on the target machines, which simplifies deployment. Ansible uses YAML for its playbook syntax and has a large collection of modules for managing everything from package installation and file templates to cloud resources and network devices. Ansible excels at configuration management, application deployment, and ad-hoc task execution.
Pulumi offers a different approach entirely, letting you define infrastructure using general-purpose programming languages like Python, TypeScript, Go, and C# instead of domain-specific configuration languages. This means you can use loops, conditionals, functions, and unit tests in your infrastructure code, leveraging skills your developers already have. Pulumi supports the same cloud providers as Terraform and can import existing Terraform state.
Other IaC tools serve specific niches. Chef and Puppet are configuration management tools that preceded Ansible, using Ruby-based DSLs to define system configurations. SaltStack (now part of VMware) handles both configuration management and event-driven automation. CloudFormation is AWS's native IaC service, and while not open source, it is free to use and deeply integrated with AWS services.
The IaC landscape is large, but most teams settle on one provisioning tool (Terraform, OpenTofu, or Pulumi for cloud resources) and one configuration management tool (Ansible for server setup and application deployment). Combining both covers the full spectrum from creating a virtual machine to configuring the software running on it.
GitOps and Version Control Platforms
GitOps is a set of practices that uses Git repositories as the single source of truth for both application code and infrastructure configuration. In a GitOps workflow, every change to the system, whether it is a new feature deployment, a configuration update, or a scaling adjustment, is made through a Git commit. Automated agents watch the repository and continuously reconcile the live system to match the declared state.
The GitOps model offers several advantages. Every change is auditable through the Git commit history. Rollbacks are as simple as reverting a commit. Pull requests serve as change approval workflows. And the entire state of a system can be reconstructed from the repository at any point in time.
Argo CD is the most popular GitOps tool for Kubernetes. It runs inside a Kubernetes cluster, watches one or more Git repositories, and automatically deploys changes when new commits appear. Argo CD provides a web dashboard that visualizes the sync status of every application, showing whether the live state matches the desired state in Git. Flux is another CNCF GitOps project with similar capabilities but a different architecture, using a set of Kubernetes controllers rather than a centralized server.
Self-hosted Git platforms are essential infrastructure for organizations that cannot or prefer not to use GitHub or GitLab's cloud services. GitLab Community Edition is the most feature-rich self-hosted option, combining source control, CI/CD, container registry, issue tracking, and wiki functionality in a single application. Gitea is a lightweight, self-hosted Git service written in Go, designed for simplicity and low resource usage. Forgejo, a community fork of Gitea created in 2022 over governance concerns, offers the same lightweight design with a commitment to remaining a community-governed project.
Version control is the foundation of every DevOps workflow. Whether you host your own GitLab instance or use a managed service, the repository is where code, configuration, pipeline definitions, and infrastructure declarations live. The choice of platform influences how CI/CD, code review, and deployment automation work, since many tools integrate more deeply with specific Git providers.
Building Your DevOps Toolchain
A DevOps toolchain is the collection of tools that a team uses across the entire software delivery lifecycle. There is no single correct combination, but certain pairings are proven and well-documented. The key is to select tools that integrate cleanly, avoid unnecessary overlap, and match your team's scale and expertise.
For a small team deploying a few services, a practical starting stack might be: Gitea for source control, Drone or Woodpecker for CI/CD, Docker for containerization, and Ansible for server provisioning and deployment. This combination is lightweight, easy to self-host, and requires minimal infrastructure.
For a mid-size organization running microservices, a more complete stack might include: GitLab CE for source control and CI/CD, Docker for building images, Kubernetes (via k3s) for orchestration, Terraform or OpenTofu for cloud infrastructure provisioning, Ansible for configuration management, and Argo CD for GitOps-based deployments.
For large enterprises operating across multiple clouds and regions, the stack typically expands to include: a full Kubernetes deployment with multiple clusters, a service mesh like Istio or Linkerd for inter-service communication, Vault for secrets management, a comprehensive monitoring stack (covered in our Open Source Monitoring guide), and policy engines like Open Policy Agent (OPA) for governance and compliance.
Several principles apply regardless of scale. Prefer tools that store configuration as code in Git. Choose tools with active communities and regular releases. Avoid tools that create vendor lock-in through proprietary formats or protocols. And invest in understanding each tool deeply rather than adopting many tools superficially. A simple pipeline that your team fully understands is more valuable than a sophisticated one that only one person can maintain.