DevOps embraces the following foundational practices that, when applied in unison, drive reliable, repeatable workflows throughout the development lifecycle:
Continuous integration/continuous delivery (CI/CD)
Continuous integration automatically merges code changes into shared repositories, triggering automated builds and tests. Continuous delivery extends this by automatically deploying validated code to staging and production environments. This practice reduces deployment risks while enabling multiple daily releases.
Automation
Streamlining repetitive tasks such as testing, deployment, and monitoring through workflow automation increases productivity, reduces errors, and gives DevOps team more time to focus on strategic activities. Also, automation of security-focused processes helps teams efficiently protect software against vulnerabilities.
Cross-team collaboration
DevOps fundamentally changes how teams across disciplines approach software development and operations. Rather than viewing them as separate entities with conflicting priorities, DevOps fosters a culture around shared objectives and mutual accountability for customer success. By valuing teamwork and open communication, DevOps allows teams to more quickly respond to changes and issues.
Version control
Centralized version control systems automatically track every code change, configuration update, and infrastructure modification. Teams maintain complete visibility into who changed what, when, and why—essential for debugging, compliance, and collaborative development.
Situational awareness
Teams continuously observe, comprehend, and anticipate what’s happening in the DevOps pipeline. This practice goes beyond simple monitoring to allow teams to identify issues in real time and proactively resolve them.
Infrastructure as code (IaC)
IaC treats infrastructure provisioning like software development, using code to define servers, networks, and cloud resources. This practice supports CI/CD pipelines and enables consistent, repeatable infrastructure deployments across development, staging, and production environments. It also enables rapid scaling and disaster recovery.
Microservices
A microservice architecture supports the efficient development, deployment, and scaling of innovative, cloud-based services. Teams can work independently on small, specific services before connecting them through APIs into a larger solution. Increasingly packaged using
containers, microservices allow for greater flexibility, innovation, and resilience in DevOps workflows.
DevSecOps
DevSecOps—short for development, security, and operations—has become a standard DevOps practice. Automated security tools identify vulnerabilities embedded throughout the development lifecycle. Also, Zero Trust architectures and continuous compliance monitoring help organizations maintain a strong security posture while preserving development velocity.
Configuration management
Automated configuration management maintains consistent system states across all environments. Rather than manual server setup, teams use code-driven tools to deploy, configure, and maintain infrastructure components reliably.
Continuous monitoring
Real-time monitoring and observability provide insights into application performance, user experience, and system health. Proactive monitoring enables teams to identify and resolve issues before they impact customers, supporting the high-velocity deployment cycles that define successful DevOps implementation.
AI in DevOps
DevOps uses machine learning, generative AI, and other AI technologies to empower teams at every phase of the lifecycle. For example,
AI in DevOps streamlines planning through more informed decision-making, speeds code development with AI-powered suggestions, and boosts CI/CD through predictive analytics. Agentic DevOps, where autonomous agents work alongside or on behalf of humans to perform a string of tasks, represents a new chapter in the evolution of DevOps.