DevOps Resume Keywords

What You Need to Know

DevOps job descriptions are packed with specific tool names because teams use standardized stacks. Mentioning "Kubernetes" signals you understand container orchestration, not just basic Docker. "Terraform" shows infrastructure as code experience, which is non-negotiable at scale. Cloud platform keywords like "AWS" or "Azure" matter because companies standardize on one provider. CI/CD tool names appear frequently—Jenkins, GitLab CI, GitHub Actions—so including the ones you've used helps match. Monitoring tools like Prometheus and Grafana are common requirements. Linux skills are assumed, but mentioning specific distributions can help. DevOps has become a distinct discipline with its own tooling ecosystem, and ATS systems reflect this specialization. Generic terms like "system administration" aren't enough—recruiters search for specific tools and platforms that teams actually use. Understanding which keywords matter requires understanding modern infrastructure practices and how DevOps teams actually work. Containerization keywords are essential because containers have become the standard deployment unit. Docker is the foundation, but mentioning it alone isn't enough—showing you understand Dockerfiles, multi-stage builds, and image optimization demonstrates deeper knowledge. Container registries like Docker Hub, AWS ECR, or Google Container Registry appear in job descriptions. Understanding container security scanning and best practices shows awareness of production concerns. Kubernetes has become the standard for container orchestration, so mentioning it is almost mandatory for many roles. But Kubernetes is complex, so showing you understand specific concepts helps—pods, services, deployments, ingress controllers, operators. Mentioning specific Kubernetes distributions or managed services—EKS, GKE, AKS—shows you understand cloud provider offerings. Helm charts for package management and kubectl for cluster management are common requirements. Infrastructure as code (IaC) is non-negotiable at scale, so Terraform and CloudFormation appear frequently. But mentioning them isn't enough—showing you understand state management, modules, and provider ecosystems demonstrates real experience. Ansible, Puppet, and Chef are less common but still appear, especially in organizations with existing investments. Understanding configuration management versus infrastructure provisioning shows deeper knowledge. Cloud platform keywords are critical because most companies use cloud infrastructure. AWS is most common, but Azure and GCP are also popular. Mentioning specific services helps—EC2, S3, Lambda, RDS for AWS; Virtual Machines, Blob Storage, Functions, SQL Database for Azure. Understanding cloud architecture patterns—regions, availability zones, VPCs—demonstrates real experience. Cloud certifications can help but aren't required. Multi-cloud experience is becoming more valuable as companies try to avoid vendor lock-in. CI/CD pipeline keywords are essential because automation is core to DevOps. Jenkins is still common but legacy; GitLab CI, GitHub Actions, and CircleCI are more modern. Understanding pipeline as code, parallel execution, and artifact management shows deeper knowledge. Build tools like Maven, Gradle, or npm appear in job descriptions. Understanding different pipeline patterns—branching strategies, deployment strategies—demonstrates experience with real-world scenarios. Version control is assumed knowledge, but mentioning Git workflows like GitFlow or trunk-based development shows understanding of team practices. GitLab and GitHub are common platforms, each with their own features. Monitoring and observability keywords are increasingly important. Prometheus for metrics and Grafana for visualization are standard. But understanding the broader observability stack helps—distributed tracing with Jaeger or Zipkin, log aggregation with ELK stack or Loki, APM tools like New Relic or Datadog. Understanding SLIs, SLOs, and error budgets demonstrates site reliability engineering (SRE) knowledge. Alerting systems like PagerDuty or Opsgenie appear frequently. Linux skills are fundamental, but mentioning specific distributions can help—Ubuntu, CentOS, RHEL, or Alpine (for containers). Understanding shell scripting, systemd, and package management shows deeper knowledge. Windows Server experience appears less frequently but can be valuable in mixed environments. Networking knowledge is important because DevOps engineers need to understand how systems communicate. Understanding TCP/IP, DNS, load balancing, and firewalls demonstrates foundational knowledge. Service mesh technologies like Istio or Linkerd are becoming more common. Security keywords are increasingly important as security becomes integrated into DevOps (DevSecOps). Understanding secrets management with tools like Vault or AWS Secrets Manager shows security awareness. Security scanning tools, compliance frameworks, and secure coding practices appear in job descriptions. Scripting and programming keywords show you can automate tasks. Python and Bash are most common, but Go is becoming popular for infrastructure tools. Understanding APIs and how to integrate different systems demonstrates practical skills. Database keywords appear because DevOps engineers often manage database infrastructure. Understanding different database types—relational, NoSQL, time-series—and their operational characteristics helps. Database migration tools and backup strategies are common requirements. The DevOps field is constantly evolving, so showing you stay current matters. Mentioning newer trends like GitOps, serverless, or edge computing can help. But balance newer trends with proven fundamentals—showing you understand both demonstrates well-rounded knowledge. Certifications can help, especially for specific platforms like AWS, Azure, or Kubernetes (CKA, CKAD). But practical experience matters more than certifications. The key is showing you understand not just what tools exist, but how to use them together to build reliable, scalable systems.