What Is DevOps Automation?

Discover the transformative power of DevOps automation through real-world examples. Learn essential best practices like version control and modular design, and find out how Pulumi is reshaping modern Infrastructure as Code solutions.

A Guide to DevOps Automation: Benefits and Best Practices

In DevOps, automation is everything. The principle is straightforward: automate end-to-end, starting from code creation on a developer’s workstation to its deployment and ongoing monitoring of your applications and services in production.

A primary emphasis in DevOps is the automated orchestration of infrastructure and configurations alongside software deployments. This automation enables rapid, consistent delivery across different platforms.

DevOps automation refers to integrating technologies that minimize manual intervention, enhancing feedback loops between operations and development. This facilitates quicker iterative updates to production applications. By encompassing the complete development lifecycle, DevOps automation enhances speed, precision, consistency, and reliability, boosting the frequency of software deliveries.

In this article, we’ll unravel how automation, not only accelerates software delivery but also fosters a culture of collaboration, innovation, and continuous improvement. Whether you’re a novice exploring DevOps for the first time or an expert seeking to refine your automation strategies, this guide provides a holistic overview of the DevOps automation landscape.

What is DevOps Automation?

DevOps, a fusion of “development” and “operations,” is both a cultural movement and a philosophy that emphasizes the collaboration between software developers and IT operations teams. The core idea behind DevOps is to break down silos, enhance communication, and streamline processes to deliver software faster, more reliably, and with improved quality. It represents a shift from traditional software development and infrastructure management processes, encouraging rapid, iterative work cycles and shared responsibility for the end product’s performance and reliability.

At the heart of the DevOps paradigm is automation. DevOps automation aims to reduce the manual overhead in tasks such as code integration, testing, deployment, and infrastructure provisioning. By automating these processes, organizations can achieve more frequent deployments, reduce human error, and ensure consistent environments from development to production. This not only accelerates software delivery but also fosters collaboration by integrating the efforts of different teams through shared tooling and processes. The idea is to allow teams to focus on delivering value rather than getting bogged down with repetitive tasks.

Why is DevOps Automation important?

In today’s fast-paced digital world, agility and responsiveness have become critical for businesses to stay competitive. DevOps automation, in essence, serves as the backbone for this agility. Without automation, organizations would find it challenging to maintain the pace of modern software delivery, respond to market changes, and ensure top-notch service quality. Moreover, as the complexity of IT environments continues to grow – with microservices, cloud-native architectures, and intricate deployment topologies – manual processes become increasingly error-prone and unsustainable. DevOps automation bridges this gap by creating streamlined, repeatable, and scalable processes that drive innovation without compromising reliability.

Benefits of DevOps Automation:

  • Faster Time to Market: Automated pipelines reduce the lead time from development to deployment, allowing companies to release features, fixes, and updates more frequently and stay ahead in the market.
  • Enhanced Collaboration: By integrating tools and processes across teams, automation fosters a culture of shared responsibility and seamless collaboration, breaking down traditional silos between development and operations.
  • Increased Reliability: Consistency is key in ensuring the software functions as intended. Automation guarantees that processes like testing and deployment are carried out uniformly every time, leading to a reduction in errors and system failures.
  • Scalability: Automation allows businesses to adapt to changing loads and demands easily. Whether it’s scaling infrastructure during traffic spikes or managing complex deployment patterns, automation ensures systems remain responsive and resilient.
  • Cost Efficiency: By eliminating manual overhead, reducing errors, and accelerating delivery, organizations can achieve significant cost savings. Moreover, quick feedback loops ensure that defects are detected early, further reducing the costs associated with late-stage error rectification.

What types of DevOps processes can/should be automated?

  • Continuous Integration (CI): This is the practice of frequently merging code changes into a central repository. Automated tests are run to ensure new changes don’t introduce errors. It’s essential for catching issues early and streamlining code integration.
  • Continuous Delivery/Deployment (CD): Once code passes the CI phase, it can be automatically deployed to various environments (staging, production). Continuous Delivery ensures the code is always in a deployable state, while Continuous Deployment automates the deployment to production.
  • Automated Testing: Beyond just unit tests in CI, automated testing encompasses integration tests, performance tests, and end-to-end tests, ensuring the software performs well under various conditions and real-world scenarios.
  • Infrastructure as Code (IaC): This is the process of managing and provisioning infrastructure using code and automation tools. IaC allows for consistent environment setups, reducing discrepancies between development, testing, and production environments.
  • Application Performance Monitoring (APM): Automated monitoring tools continuously watch applications in real-time. They can detect performance anomalies, failures, or bottlenecks, providing insights and alerts to teams for swift action.
  • Automated Remediation: When a monitoring tool detects an issue, automated remediation systems can kick in to resolve the problem automatically, whether it’s restarting a failed service or scaling resources based on demand.
  • Configuration Management: Tools like Ansible, Puppet, and Chef allow for the automated setup, maintenance, and updating of system configurations across multiple servers and environments. This ensures systems are consistently configured as per predefined standards and policies.

By automating these processes, DevOps teams can ensure consistency, reliability, and efficiency throughout the software development lifecycle, while also freeing up time for more value-added tasks and innovations.

What does effective DevOps automation look like?

Effective DevOps automation transcends merely stringing together a series of tools and scripts. At its core, it represents a seamless fusion of culture, process, and technology. Culturally, teams are aligned in their goals, fostering an environment of transparency, continuous learning, and shared responsibility.

On the process front, automation should be all-encompassing, touching every aspect of the software delivery lifecycle—from code integration to deployment, monitoring, and feedback loops. The tools chosen must not only facilitate these processes but also integrate harmoniously with one another, creating a cohesive ecosystem that provides end-to-end visibility and traceability. Furthermore, effective DevOps automation is iterative and adaptable, with teams continually assessing and refining their automation strategies in response to changing needs, technologies, and feedback. This proactive approach ensures that the automation remains resilient, scalable, and attuned to the organization’s overarching objectives.

Measuring the effectiveness of DevOps automation requires a set of KPIs (Key Performance Indicators) that encapsulate both the technical and cultural shifts intended by the DevOps movement. Here are some critical KPIs to consider:

  • Deployment Frequency: This measures how often code deployments occur. An increase in deployment frequency often indicates a more agile and responsive development process.
  • Lead Time for Changes: This KPI gauges the time taken from code commitment to code successfully running in production. Shorter lead times suggest a more efficient delivery pipeline.
  • Change Failure Rate: This is the percentage of changes that fail. A lower change failure rate indicates a more stable and reliable deployment process, whereas a higher rate may suggest issues with testing or integration processes.
  • Mean Time to Recovery (MTTR): When failures occur, how long does it take to restore service? A shorter MTTR implies a more resilient system and effective incident response.
  • Automated Test Pass Rate: The percentage of automated tests that pass during the CI/CD process. A high pass rate may indicate good code health, while a low rate can be a red flag for potential quality issues.
  • Infrastructure Automation Rate: Measures the percentage of infrastructure provisioning and management tasks that are automated. Higher automation rates indicate a mature Infrastructure as Code (IaC) approach.
  • Feedback Loop Time: The time it takes for developers to receive feedback on their changes, whether through automated tests, code reviews, or production monitoring. Quicker feedback loops enhance the development process and reduce latent defects.
  • Percent of Defects Found in Automation: A higher percentage indicates that your automation processes, especially testing, are effective in catching issues before they reach production.
  • Operational Overhead: The time spent on operational tasks as opposed to value-added activities. Effective automation should reduce this overhead, allowing teams to focus more on innovation and less on maintenance.
  • Toolchain Integration Efficiency: How well integrated are the various tools in the DevOps pipeline? Seamless integration often results in fewer manual handoffs and a more streamlined delivery process.

These KPIs offer a comprehensive view of DevOps automation’s performance, but it’s crucial to tailor them to an organization’s specific context and objectives. Regularly reviewing and adjusting these metrics ensures that they remain relevant and drive continuous improvement.

Companies that have successfully automated their DevOps processes

How have existing companies successfully leveraged devops automation to improve real world business challenges? In the examples below, learn how automation was leveraged by these recognizable companies:


Atlassian’s Bitbucket DevSpeed team is responsible for improving developer productivity through better workflows and tooling. The DevSpeed team built a self-service dashboard using Pulumi and the existing CI/CD process that enables any Bitbucket developer to quickly and easily provision a cloud-based development environment through automation. Now any developer can deploy and configure AWS instances for feature development, increasing developer productivity and leading to a 50% reduction in the time developers spend maintaining their instances.


Mercedes-Benz Research & Development North America (MBRDNA) enabled its distributed innovation teams to move hundreds of microservices to the cloud leveraging automation. Infrastructure teams used Pulumi’s Automation API to build self-service tools for building, deploying, and managing infrastructure and offer the right levels of complexity and customization for the tool’s target audience.

SANS Institute

The DevOps team at SANS Institute, which provides cybersecurity training and certification, needed to provide each student with a virtual training environment. Instructors needed a way to spin up ephemeral AWS EC2 instances and related resources, but the process required manual steps that involved gluing together multiple provisioning and scripting tools. To solve this challenge, they built a self-service platform that can automatically deploy, configure and destroy approved infrastructure with best practices baked-in from SANS security and operations teams, eliminating the need for a manual ticketing process.

In each of these examples, devops teams improved scalability and reliability of their infrastructure by introducing automation.

Best practices for DevOps automation

DevOps automation, especially when dealing with Infrastructure as Code (IaC), requires a strategic approach to ensure consistency, maintainability, and security. Here are some best practices for DevOps automation:

  • Version Control Everything: Just like application code, your infrastructure code should be stored in a version control system. This provides a history of changes, allows for rollbacks, and enables collaboration among teams.
  • Automate Testing: Test your infrastructure code to ensure it does what’s expected. Tools like Test Kitchen, inspec, and ServerSpec can help test infrastructure changes before they’re applied.
  • Modularize and Reuse: Design your infrastructure code to be modular, enabling reuse across different parts of the environment or even across different projects. This reduces redundancy and streamlines management.
  • Use a Consistent Naming Convention: A consistent naming schema for resources, modules, and variables improves clarity and eases maintenance.
  • Manage Secrets Securely: Tools like Pulumi Cloud keep secrets secure by default. Never embed secrets directly in your code.

By adhering to these best practices, teams can maximize the benefits of DevOps automation and Infrastructure as Code, resulting in faster, more consistent, and more reliable infrastructure provisioning and management.

How to get started with DevOps automation

Embarking on the journey of DevOps automation can seem daunting given its expansive nature, but it’s pivotal to start with a clear understanding of your organization’s needs and pain points. Begin by identifying repetitive tasks, bottlenecks, and areas prone to human error, then prioritize them for automation. As you work through this, consider embracing tools like Pulumi, which stands out for its unique approach to Infrastructure as Code. Pulumi allows you to define and manage infrastructure using popular programming languages you’re already familiar with, thereby seamlessly integrating into existing development workflows. By leveraging such tools, and fostering a culture of collaboration and continuous improvement, organizations can unlock the full potential of DevOps automation, driving efficiency, reliability, and innovation in their software delivery processes.

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