litellm/terraform/litellm/aws
Yassin Kortam 4e3c437631
feat(deploy): make coordination redis a first-class chart and terraform surface (#32662)
Render a general_settings.coordination_redis block into the litellm-helm
proxy config when the bundled Redis is enabled, gated on a new
redis.coordination.enabled value and skipped when the user already
supplies their own block. Sentinel deployments render sentinel_nodes and
service_name rather than a host/port pair.

Also fixes litellm.redis.serviceName, which gated its sentinel branch on
standalone architecture. The bundled Redis subchart only serves sentinel
in replication mode, and renders no master Service there, so REDIS_HOST
pointed at a Service that never existed for every sentinel user.

Documents the coordination redis in the componentized chart and in the
terraform modules, whose existing REDIS_* exports now feed it directly.

Adds helm-unittest coverage for both charts' redis wiring, which had none
2026-07-10 16:16:09 -07:00
..
examples/default feat(deploy): make coordination redis a first-class chart and terraform surface (#32662) 2026-07-10 16:16:09 -07:00
.terraform.lock.hcl feat: add Terraform stacks for deploying LiteLLM on AWS and GCP (#27673) 2026-05-16 17:26:20 -07:00
alb.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
autoscaling.tf feat: add Terraform stacks for deploying LiteLLM on AWS and GCP (#27673) 2026-05-16 17:26:20 -07:00
bootstrap.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
ecs.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
iam.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
locals.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
migrations.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
network.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
outputs.tf feat: add Terraform stacks for deploying LiteLLM on AWS and GCP (#27673) 2026-05-16 17:26:20 -07:00
rds.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
README.md refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
redis.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
s3.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
secrets.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
variables.tf refactor: convert AWS and GCP Terraform stacks into reusable modules … (#28103) 2026-06-06 12:57:44 -07:00
versions.tf feat: add Terraform stacks for deploying LiteLLM on AWS and GCP (#27673) 2026-05-16 17:26:20 -07:00

LiteLLM on AWS (ECS Fargate)

Deploys the componentized LiteLLM proxy on AWS:

  • VPC with public + private subnets across the AZs you pass in, one NAT gateway
  • Aurora Postgres cluster — one writer instance + one reader instance, IAM database authentication enabled
  • ElastiCache Redis (private, replication group with multi-AZ failover and at-rest + in-transit encryption) for caching + rate limiting
  • S3 bucket (private, versioned, SSE-S3) — exposed to gateway + backend as S3_BUCKET_NAME / S3_REGION_NAME for cache backend, request log archival, and /v1/files storage
  • Secrets Manager entries for LITELLM_MASTER_KEY (auto-generated, sk-…) and the Aurora master password (bootstrap-only)
  • ECS Fargate cluster running three services — gateway, backend, ui
  • Application Load Balancer (public, HTTP/80) with path-based routing:
    • LLM data-plane prefixes (/v1/chat/*, /v1/embeddings, …) → gateway
    • UI assets (/, /_next/*, /litellm-asset-prefix/*, …) → ui
    • Everything else (management API: /key/*, /user/*, …) → backend
  • One-off migration task (litellm-migrations) that runs prisma migrate deploy from the dedicated ghcr.io/berriai/litellm-migrations image

Aurora + IAM auth

The cluster runs with iam_database_authentication_enabled = true. Enabling that on the cluster doesn't by itself let any Postgres user log in with an IAM token — you also need to CREATE USER ... GRANT rds_iam once. bootstrap.tf does this automatically during terraform apply via a one-shot Fargate task (postgres:16-alpine running the bootstrap SQL with the master password from Secrets Manager). The SQL is idempotent, so re-applies are safe.

The same apply also runs the prisma schema migration via the existing litellm-migrations task definition, and the gateway/backend services depends_on the migration so they don't start until the schema is in place.

At runtime, the proxy assembles DATABASE_URL from DATABASE_HOST/PORT/USER/NAME plus a short-lived IAM token — see litellm/proxy/auth/rds_iam_token.py. The task role has rds-db:connect scoped to the IAM-authed user on the cluster.

Break-glass. If you need to run the bootstrap or migration by hand (e.g., to re-apply against an externally provisioned cluster), db_bootstrap_sql and migration_run_command are still exposed as outputs.

Prerequisite. terraform apply shells out to aws ecs run-task / aws ecs wait in local-exec provisioners, so the machine running terraform needs the aws CLI installed and authenticated.

Configuring the proxy

proxy_config (preferred)

Mirrors the helm chart's gateway.config.proxy_config. The map is YAML-encoded and uploaded to S3 (config/litellm-config.yaml in the stack's bucket); the gateway and backend container entrypoints download it to /tmp/litellm-config.yaml at task start via boto3 and set CONFIG_FILE_PATH to match. The S3 object's etag is wired into the task definition, so editing proxy_config produces a new task-def revision and a rolling redeploy of both services.

proxy_config = {
  model_list = [
    {
      model_name = "gpt-4o"
      litellm_params = {
        model   = "openai/gpt-4o"
        api_key = "os.environ/OPENAI_API_KEY"
      }
    },
  ]
  general_settings = {
    master_key   = "os.environ/LITELLM_MASTER_KEY"
    database_url = "os.environ/DATABASE_URL"
  }
}

LiteLLM resolves os.environ/<NAME> references in the YAML against the container's environment. That means provider API keys belong in *_extra_secrets (next section), and your YAML just references them by name.

Extra env vars

Non-sensitive plaintext (feature flags, observability hosts, etc.):

gateway_extra_env = {
  LANGFUSE_HOST = "https://us.cloud.langfuse.com"
}
backend_extra_env = {
  STORE_MODEL_IN_DB = "True"
}

Extra secrets (API keys)

Sensitive values — provider API keys, third-party tokens — live in existing Secrets Manager secrets. Reference them by ARN:

gateway_extra_secrets = {
  OPENAI_API_KEY    = "arn:aws:secretsmanager:us-west-2:111122223333:secret:openai-api-key-AbCdEf"
  ANTHROPIC_API_KEY = "arn:aws:secretsmanager:us-west-2:111122223333:secret:anthropic-api-key-GhIjKl"
}

What happens under the hood:

  • The execution role auto-gains secretsmanager:GetSecretValue on every ARN listed here.
  • ECS resolves each secret at task launch and injects its value into the container as the env var named on the left.
  • The proxy_config YAML references the resulting env var via os.environ/OPENAI_API_KEY.

To pluck a single field out of a JSON secret, use ECS's :fieldName:: suffix:

gateway_extra_secrets = {
  OPENAI_API_KEY = "arn:…:secret:provider-keys-AbCdEf:openai_api_key::"
}

To create the secret beforehand:

aws secretsmanager create-secret \
  --name openai-api-key \
  --secret-string "sk-proj-..."

Observability (OpenTelemetry v2)

OTel v2 (https://docs.litellm.ai/docs/observability/opentelemetry_v2) is opt-in and gated entirely on otel_endpoint. Empty (default) and nothing OTel-related is added to the container env. Set it and both gateway and backend gain LITELLM_OTEL_V2=true plus the OTEL_* block, with OTEL_SERVICE_NAME stamped per component (${tenant}-litellm-${env}-gateway and -backend) so spans land tagged with the right hop. Any OTEL_* key set in gateway_extra_env / backend_extra_env overrides the default for that service.

otel_endpoint         = "http://otel-collector.internal:4318"
otel_exporter         = "otlp_http"   # otlp_grpc, console
otel_environment_name = "prod"        # defaults to var.env

For collectors that require an auth header, store the comma-separated key=value string in Secrets Manager and reference it via otel_headers_secret_arn. The execution role auto-gains secretsmanager:GetSecretValue on that ARN.

otel_headers_secret_arn = "arn:aws:secretsmanager:us-west-2:111122223333:secret:honeycomb-otel-headers-AbCdEf"

OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT defaults to no_content; flip otel_capture_message_content = "prompt_and_completion" only after auditing what lands in the backend, since prompts and completions are typically sensitive.

Vendor presets (Arize, Phoenix, Langfuse OTel, Weave, Langtrace, Levo, AgentOps) live under proxy_config.litellm_settings.callbacks and are orthogonal to the OTLP variables above; their credentials still go in *_extra_secrets.

Tenant deployment

Every resource the stack creates is named ${tenant}-litellm-${env} (or that plus a per-resource suffix), so multiple tenants and multiple environments coexist in the same account as long as the (tenant, env) pair differs:

tenant env Example resource name
acme stage acme-litellm-stage-gateway
acme prod acme-litellm-prod-master-key
globex dev globex-litellm-dev-license

For a per-tenant instance via the example root, the only inputs that change are the tenant slug, env, and the two pre-issued secrets:

cd terraform/litellm/aws/examples/default
export TF_VAR_litellm_master_key="sk-..."   # the tenant's master key
export TF_VAR_litellm_license="lic-..."     # their LITELLM_LICENSE

terraform apply \
  -var "region=us-west-2" \
  -var 'azs=["us-west-2a","us-west-2b"]' \
  -var "tenant=acme" \
  -var "env=stage"

To run many tenants from a single config, call the module with for_each instead of one root per tenant (see "Using as a module"):

module "litellm" {
  for_each = toset(["acme", "globex"])
  source   = "github.com/BerriAI/litellm//terraform/litellm/aws?ref=<tag>"
  tenant   = each.key
  env      = "prod"
  region   = "us-west-2"
  azs      = ["us-west-2a", "us-west-2b"]
}

(This for_each form is only possible because the module declares no provider block — the original root-with-provider layout forbade it.)

Both litellm_master_key and litellm_license are optional:

  • Omit litellm_master_key → the stack auto-generates a random sk-… value (trial/dev path).
  • Omit litellm_license → no license secret is created and gateway/ backend run without LITELLM_LICENSE (OSS-only).

Use TF_VAR_* env vars rather than tfvars files for these — values written to a tfvars file end up in terraform.tfstate and any committed example files.

Quick start

cd terraform/litellm/aws/examples/default
cp terraform.tfvars.example terraform.tfvars
# Edit: region, tenant, env, azs, proxy_config, gateway_extra_secrets.

terraform init
terraform apply

examples/default/ is a thin root that configures the aws provider and calls the module (../../). It exposes a curated variable surface; for advanced knobs (per-component CPU/memory/workers, autoscaling, RDS/Redis sizing, per-component image pins) set them on the module "litellm" block in examples/default/main.tf, or call the module from your own config — see "Using as a module" below.

That single apply provisions everything, runs the DB user bootstrap, runs the schema migration, and only then starts the gateway/backend services. When it returns, the stack is serving traffic.

terraform output alb_url
# UI login: admin / <master key>
aws secretsmanager get-secret-value \
  --secret-id "$(terraform output -raw master_key_secret_arn)" \
  --query SecretString --output text

Using as a module

The directory itself is a module with no provider block — the caller owns provider config. That means you can call it directly with for_each (many tenants from one config), count (conditional stacks), depends_on, an assume-role / aliased provider, etc.:

provider "aws" {
  region = "us-west-2"
  assume_role { role_arn = "arn:aws:iam::111122223333:role/deployer" }
}

module "litellm" {
  source = "github.com/BerriAI/litellm//terraform/litellm/aws?ref=<tag>"

  region = "us-west-2"
  tenant = "acme"
  env    = "prod"
  azs    = ["us-west-2a", "us-west-2b"]
  # ...any of the inputs in variables.tf...
}

Tags: the module threads its own litellm:stack / managed-by / var.tags onto every taggable resource. Any default_tags on your provider merge on top — set org-wide tags there, per-deployment tags via the tags input.

Image pulls

The defaults pull from ghcr.io/berriai/litellm-<component>:v1.86.0-dev, which is anonymous-readable. There are four images: litellm-gateway, litellm-backend, litellm-ui, and litellm-migrations (slim image used only by the one-off migration task — runs prisma migrate deploy against the writer DB and exits). Bump them together when bumping LiteLLM. To pull from a private registry:

  • ECR (same account): the execution role already has AmazonECSTaskExecutionRolePolicy, which grants ECR pull for repos in the same account. No extra config needed.
  • ECR (cross-account): attach a policy to the execution role allowing ecr:GetAuthorizationToken + ecr:BatchGetImage on the foreign repo ARNs.
  • Other private registries (GHCR with a PAT, Docker Hub, …): create a secret holding {"auths":{"<registry>":{"auth":"<base64-user:token>"}}} in Secrets Manager and set repositoryCredentials.credentialsParameter on the task def container — extend ecs.tf accordingly.

TLS

terraform plan refuses to provision an HTTP-only ALB by default — TLS is the supported posture. Two paths:

Production / staging — provide an ACM certificate:

  1. Create or import an ACM cert in var.region covering the DNS name you plan to point at the ALB.
  2. Set acm_certificate_arn = "arn:aws:acm:..." in tfvars and apply.

Result: a 443 listener carries the path-routing rules; the 80 listener serves a permanent 301 redirect to HTTPS, so HTTP clients are automatically upgraded.

Trial / dev — explicitly opt into HTTP-only:

Set allow_plaintext_alb = true in tfvars. Without this flag, plan fails with a clear error pointing at the precondition. Intended for short-lived trial / dev stacks only.

Storage and database retention

Three opt-in tripwires guard against accidental data loss on terraform destroy:

  • skip_final_snapshot (Aurora; default false) — destroying the cluster takes a <cluster>-final-<short-sha> snapshot first.
  • s3_force_destroy (S3 bucket holding request log archives, /v1/files content, and the S3 cache backend; default false) — terraform destroy against a non-empty bucket fails.

Flip either to true only for ephemeral / CI stacks where you accept losing the contents.

Files

File What's in it
versions.tf Terraform + required_providers constraints (module declares no provider config)
examples/default/ Thin root: aws provider (with an optional default_tags slot for org-wide tags) + a call to the module. The one-command deploy path.
variables.tf All input variables
locals.tf Path-prefix lists for ALB routing (mirror of helm/.../ingress.yaml)
network.tf VPC, subnets, IGW, NAT, route tables, security groups
secrets.tf Secrets Manager entries + random passwords
rds.tf Aurora Postgres cluster + writer / reader instances
redis.tf ElastiCache Redis
s3.tf S3 bucket + task-role policy scoped to it
iam.tf Task execution + task roles, including rds-db:connect
ecs.tf ECS cluster, task definitions, services for the three components
alb.tf ALB, listener, target groups, path-routing rules
migrations.tf One-off migration task definition
outputs.tf DNS name, secret ARN, bootstrap SQL, migration run-task command