MpegFlow with Terraform: infrastructure as code

Terraform manages MpegFlow's infrastructure dependencies — K8s clusters, managed databases, storage, IAM, networking. The Helm chart deploys MpegFlow itself; Terraform deploys everything underneath. We provide example Terraform modules for common deployment shapes; this page covers the integration patterns that make Terraform-driven deployments operationally clean.

How the integration works

Terraform manages: VPC + subnets, K8s cluster (EKS/GKE/AKS), managed Postgres, managed Redis, S3 / GCS / R2 buckets, IAM roles, KMS keys, CloudFront distributions, ACM certs. The Helm chart deploys MpegFlow into the cluster Terraform created. Two layers, clean separation: infrastructure changes via Terraform PRs, application changes via Helm + GitOps.

Common patterns

• Module-per-environment

  Wrap each MpegFlow deployment as a Terraform module: "production-us-east-1", "staging-eu-west-1", etc. Each module instantiates the same resources with different sizing. Variables drive environment differences (instance sizes, Postgres tier, retention).

• Remote state with S3 + DynamoDB

  Terraform state lives in S3 with DynamoDB locking — the standard AWS pattern. For multi-cloud or sovereign-cloud, GCS state with Cloud Storage object versioning, or HashiCorp Cloud Platform (Terraform Cloud) for managed state.

• GitOps for infrastructure

  Terraform configs live in a git repo. PR-based review for any infrastructure change. CI runs terraform plan on PR, terraform apply on merge to main. Atlantis or Spacelift automates this loop.

• Terraform + Helm via terraform-helm-release

  For tightly-coupled deployments where infra + app should be applied together, the Terraform helm_release resource installs the MpegFlow Helm chart. Useful for ephemeral environments (preview deploys); GitOps via Argo/Flux is better for production.

Pitfalls

1. Terraform state can drift if anyone makes manual changes via the cloud console. Enforce all-changes-via-Terraform; audit with drift detection in CI.
2. Module versioning matters at scale: pin module versions to specific tags, never use "main". Upgrades are explicit version-bump PRs.
3. Terraform plan output for large state files can take minutes. Plan against changed-only resources via -target where possible.
4. KMS key destruction is irreversible: Terraform destroying a KMS key encrypting your data is a hard incident. Use prevent_destroy lifecycle blocks for stateful KMS keys.
5. Multi-region deployments need careful provider configuration — easy to accidentally deploy resources in the wrong region. Use per-region Terraform workspaces or modules.

At production scale

Terraform at MpegFlow scale typically lands at ~100-500 resources per environment. Plan times below 30 seconds are achievable with proper module structure. For multi-cluster federation deployments, Terraform manages each cluster as a separate state — federation is at the application layer (MpegFlow control plane), not the infra layer.

• terraform
• infrastructure
• iac
• tooling
• integration