Kubernetes vs Terraform
A side-by-side technical matrix of Kubernetes (DevOps & Cloud) and Terraform (DevOps & Cloud) — summaries, strengths and structural trade-offs, symmetrically laid out.
Kubernetes
Kubernetes orchestrates containers across clusters of machines, handling scheduling, scaling, networking, and self-healing. It is the de facto standard for running containerized workloads at scale.
Pros
- Self-healing. Failed containers are restarted and rescheduled automatically without operator action. 0
- Horizontal autoscaling. Pods scale out on CPU, memory, or custom metrics. 0
- Declarative config. Desired state lives in version-controlled YAML the cluster converges toward. 0
- Cloud portability. The same manifests run on EKS, GKE, AKS, or bare metal. 0
- Rich ecosystem. Helm, operators, and service meshes cover almost every operational need. 0
Cons
- Steep learning curve. Pods, services, ingress, and RBAC overwhelm newcomers quickly. 0
- Operational overhead. Running a cluster well demands dedicated platform expertise. 0
- Overkill for small apps. A handful of services rarely justifies the complexity. 0
- Cost floor. Control plane and node overhead make tiny workloads expensive. 0
Terraform
Terraform provisions cloud infrastructure declaratively from versioned configuration files, tracking real-world state to plan safe changes. It supports every major cloud through a large provider ecosystem.
Pros
- Multi-cloud coverage. One language provisions AWS, GCP, Azure, and hundreds of providers. 0
- Plan before apply. Every change previews exactly what will be created or destroyed. 0
- Versioned infrastructure. Infrastructure changes go through code review like application code. 0
- Module reuse. Shared modules encode team standards once and reuse everywhere. 0
Cons
- State file fragility. Corrupted or conflicting state can block or damage deployments. 0
- Drift headaches. Manual console changes diverge from code until re-imported. 0
- License change. The 2023 BUSL license pushed some teams toward OpenTofu. 0
- Slow feedback. Large plans take minutes, stretching iteration cycles. 0