Automation’s place in DevOps

Automation is one of the core levers for accelerating DevOps adoption. It drives consistency, reliability, and efficiency across the organization, which in turn helps teams spot and resolve issues faster. But knowing that automation matters is not the same as knowing where to start. Teams often struggle to identify which processes are worth automating and how to approach the work.

A few guiding principles can help you decide what and how to automate:

  • Choose open standards. Your team and contributors will change, but your toolchain does not have to. Following community-driven standards for packaging, runtime, configuration, networking, and storage (as found in Kubernetes) simplifies onboarding, reduces specialized training, and becomes increasingly important as deployments move to the cloud.
  • Use dynamic variables. Reusable code means less rework and duplication now and later. By securely defining variables outside your scripts or tools, you can apply the same automation across different environments without rewriting the logic.
  • Use flexible, portable tooling. No single tool fits every situation, but choosing one that integrates with a broad ecosystem and works across clouds allows you to change direction or swap technologies without redoing your automation. This keeps your toolchain from limiting your path to your own best practices.

Four automation focus areas

1. CI/CD and continuous deployment

DevOps is often equated with CI/CD, though in practice it covers far more—from enabling contributors to build and run code to improving developer productivity. Still, CI/CD is a foundational piece of DevOps automation.

  • Continuous integration (CI) runs automated tests on every change so contributors can see immediately whether their work breaks anything.
  • Continuous delivery (CD) is the practice of keeping software in a state where any successful release candidate can be deployed to production at any time.
  • Continuous deployment goes further: every successful change is automatically deployed to production. Whether you adopt this depends on your product and industry—hardware and manufacturing, for instance, often cannot push new changes to customers instantly.

Together, CI and CD create a collaborative model where teams share ownership of projects, maintain quality control through automation, and—when full continuous deployment is in play—get new features to users without manual release steps.

2. Change management

Change management is central to business processes, and the right version control and configuration practices give dev and ops teams consistency.

  • Version control. From RCS and SVN through CVS, Perforce, ClearCase, and Git, version control has long enabled collaboration by giving teams a shared workflow and code base, while making it easy to revert changes and learn from past decisions.
  • Change control. Beyond the history itself, coordinating and facilitating changes keeps the product moving in the intended direction, reduces the risk of harmful modifications, and encourages collaboration.
  • Configuration management. Templates and controlled approvals make complex deployments manageable at scale, providing proper oversight as changes are applied.

3. “X” as code

Infrastructure as code, configuration as code, policy as code, and other “as code” models give you a declarative framework for managing your operating environments. You define the variables you provide to a tool, and it consistently produces the same output, letting you recreate resources reliably. Adopting these models brings a few key benefits: an auditable change trail for compliance, collaborative change processes through version control, consistent and testable deployment of resources, and a lower learning curve for new team members.

  • Infrastructure as code (IaC) builds immutable infrastructure declaratively, using the same versioning and workflow as source code. When requirements change, new infrastructure is defined, tested, and deployed through automated pipelines.
  • Platform as code (PaC) applies the same idea to services, using high-level abstractions to deploy them rapidly onto existing infrastructure.
  • Configuration as code (CaC) extends declarative pipelines to application configuration, treating it as versioned resources.
  • Policy as code brings versioning and the DevOps workflow to security and policy management.

4. Continuous monitoring

You cannot understand how software behaves in production without operational insight. Continuous monitoring tracks the performance and stability of applications and infrastructure throughout the lifecycle, giving operations teams the data to troubleshoot and development teams the information to debug and patch. Good monitoring can mean the difference between a minor blip and a major outage, and it feeds directly into the security-focused principles of DevSecOps. Key components include:

  • Logging. Application, infrastructure, and audit logs create a continuous stream of data about the components critical to your business, supporting ongoing learning and improvement.
  • Monitoring. Monitoring adds interpretation to raw logs and metrics, and advanced tools can deliver correlated insights that raw data cannot show on its own.
  • Alerting. Proactive notifications keep teams ahead of major issues and, when well implemented, provide critical debugging context to speed up resolution.
  • Tracing. A deeper level of application performance insight that goes beyond logging, tracing significantly impacts the stability and scalability of software in production.

Getting started with automation

Automation is a crucial mechanism for efficient teamwork in DevOps, but it is not the whole story. If you are new to DevOps or migrating from another set of tools, start small. Testing new tooling on a limited project or process lays the groundwork for scaling and standardizing across the organization, and gives you a way to measure effectiveness and track progress toward goals. Whichever toolset you pick, evaluating your current workflows and the information your teams actually need will guide your platform decisions and set you up for success.

Useful references for tooling decisions can be found in the Periodic Table of DevOps Tools, a DevOps tools glossary, and a top DevOps tools list. For a look at automation in practice, see how engineers at Wiley build with GitHub Actions.