⚡ Best Practices for Production

1. Use this config.yaml

Use this config.yaml in production (with your own LLMs)

model_list:
  - model_name: fake-openai-endpoint
    litellm_params:
      model: openai/fake
      api_key: fake-key
      api_base: https://exampleopenaiendpoint-production.up.railway.app/

general_settings:
  master_key: sk-1234      # enter your own master key, ensure it starts with 'sk-'
  alerting: ["slack"]      # Setup slack alerting - get alerts on LLM exceptions, Budget Alerts, Slow LLM Responses
  proxy_batch_write_at: 60 # Batch write spend updates every 60s
  database_connection_pool_limit: 10 # limit the number of database connections to = MAX Number of DB Connections/Number of instances of litellm proxy (Around 10-20 is good number)

  # OPTIONAL Best Practices
  disable_spend_logs: True # turn off writing each transaction to the db. We recommend doing this is you don't need to see Usage on the LiteLLM UI and are tracking metrics via Prometheus
  disable_error_logs: True # turn off writing LLM Exceptions to DB
  allow_requests_on_db_unavailable: True # Only USE when running LiteLLM on your VPC. Allow requests to still be processed even if the DB is unavailable. We recommend doing this if you're running LiteLLM on VPC that cannot be accessed from the public internet.

litellm_settings:
  request_timeout: 600    # raise Timeout error if call takes longer than 600 seconds. Default value is 6000seconds if not set
  set_verbose: False      # Switch off Debug Logging, ensure your logs do not have any debugging on
  json_logs: true         # Get debug logs in json format

Set slack webhook url in your env

export SLACK_WEBHOOK_URL="https://hooks.slack.com/services/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"

Turn off FASTAPI's default info logs

export LITELLM_LOG="ERROR"

info

Need Help or want dedicated support ? Talk to a founder [here]: (https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat)

2. On Kubernetes - Use 1 Uvicorn worker [Suggested CMD]

Use this Docker CMD. This will start the proxy with 1 Uvicorn Async Worker

(Ensure that you're not setting run_gunicorn or num_workers in the CMD).

CMD ["--port", "4000", "--config", "./proxy_server_config.yaml"]

3. Use Redis 'port','host', 'password'. NOT 'redis_url'

If you decide to use Redis, DO NOT use 'redis_url'. We recommend usig redis port, host, and password params.

redis_urlis 80 RPS slower

This is still something we're investigating. Keep track of it here

Recommended to do this for prod:

router_settings:
  routing_strategy: usage-based-routing-v2 
  # redis_url: "os.environ/REDIS_URL"
  redis_host: os.environ/REDIS_HOST
  redis_port: os.environ/REDIS_PORT
  redis_password: os.environ/REDIS_PASSWORD

litellm_settings:
  cache: True
  cache_params:
    type: redis
    host: os.environ/REDIS_HOST
    port: os.environ/REDIS_PORT
    password: os.environ/REDIS_PASSWORD

4. Disable 'load_dotenv'

Set export LITELLM_MODE="PRODUCTION"

This disables the load_dotenv() functionality, which will automatically load your environment credentials from the local .env.

5. If running LiteLLM on VPC, gracefully handle DB unavailability

This will allow LiteLLM to continue to process requests even if the DB is unavailable. This is better handling for DB unavailability.

WARNING: Only do this if you're running LiteLLM on VPC, that cannot be accessed from the public internet.

general_settings:
  allow_requests_on_db_unavailable: True

6. Disable spend_logs & error_logs if not using the LiteLLM UI

By default, LiteLLM writes several types of logs to the database:

• Every LLM API request to the LiteLLM_SpendLogs table
• LLM Exceptions to the LiteLLM_LogsErrors table

If you're not viewing these logs on the LiteLLM UI (most users use Prometheus for monitoring), you can disable them by setting the following flags to True:

general_settings:
  disable_spend_logs: True    # Disable writing spend logs to DB
  disable_error_logs: True    # Disable writing error logs to DB

More information about what the Database is used for here

7. Use Helm PreSync Hook for Database Migrations [BETA]

To ensure only one service manages database migrations, use our Helm PreSync hook for Database Migrations. This ensures migrations are handled during helm upgrade or helm install, while LiteLLM pods explicitly disable migrations.

1. Helm PreSync Hook:

   • The Helm PreSync hook is configured in the chart to run database migrations during deployments.
   • The hook always sets DISABLE_SCHEMA_UPDATE=false, ensuring migrations are executed reliably.

   Reference Settings to set on ArgoCD for values.yaml

   db:
     useExisting: true # use existing Postgres DB
     url: postgresql://ishaanjaffer0324:3rnwpOBau6hT@ep-withered-mud-a5dkdpke.us-east-2.aws.neon.tech/test-argo-cd?sslmode=require # url of existing Postgres DB

2. LiteLLM Pods:

   • Set DISABLE_SCHEMA_UPDATE=true in LiteLLM pod configurations to prevent them from running migrations.

   Example configuration for LiteLLM pod:

   env:
     - name: DISABLE_SCHEMA_UPDATE
       value: "true"

8. Set LiteLLM Salt Key

If you plan on using the DB, set a salt key for encrypting/decrypting variables in the DB.

Do not change this after adding a model. It is used to encrypt / decrypt your LLM API Key credentials

We recommned - https://1password.com/password-generator/ password generator to get a random hash for litellm salt key.

export LITELLM_SALT_KEY="sk-1234"

See Code

Extras

Expected Performance in Production

1 LiteLLM Uvicorn Worker on Kubernetes

Description	Value
Avg latency	50ms
Median latency	51ms
/chat/completions Requests/second	100
/chat/completions Requests/minute	6000
/chat/completions Requests/hour	360K

Verifying Debugging logs are off

You should only see the following level of details in logs on the proxy server

# INFO:     192.168.2.205:11774 - "POST /chat/completions HTTP/1.1" 200 OK
# INFO:     192.168.2.205:34717 - "POST /chat/completions HTTP/1.1" 200 OK
# INFO:     192.168.2.205:29734 - "POST /chat/completions HTTP/1.1" 200 OK

Machine Specifications to Deploy LiteLLM

Service	Spec	CPUs	Memory	Architecture	Version
Server	t2.small.	1vCPUs	8GB	x86
Redis Cache	-	-	-	-	7.0+ Redis Engine

Reference Kubernetes Deployment YAML

Reference Kubernetes deployment.yaml that was load tested by us

apiVersion: apps/v1
kind: Deployment
metadata:
  name: litellm-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: litellm
  template:
    metadata:
      labels:
        app: litellm
    spec:
      containers:
        - name: litellm-container
          image: ghcr.io/berriai/litellm:main-latest
          imagePullPolicy: Always
          env:
            - name: AZURE_API_KEY
              value: "d6******"
            - name: AZURE_API_BASE
              value: "https://ope******"
            - name: LITELLM_MASTER_KEY
              value: "sk-1234"
            - name: DATABASE_URL
              value: "po**********"
          args:
            - "--config"
            - "/app/proxy_config.yaml"  # Update the path to mount the config file
          volumeMounts:                 # Define volume mount for proxy_config.yaml
            - name: config-volume
              mountPath: /app
              readOnly: true
          livenessProbe:
            httpGet:
              path: /health/liveliness
              port: 4000
            initialDelaySeconds: 120
            periodSeconds: 15
            successThreshold: 1
            failureThreshold: 3
            timeoutSeconds: 10
          readinessProbe:
            httpGet:
              path: /health/readiness
              port: 4000
            initialDelaySeconds: 120
            periodSeconds: 15
            successThreshold: 1
            failureThreshold: 3
            timeoutSeconds: 10
      volumes:  # Define volume to mount proxy_config.yaml
        - name: config-volume
          configMap:
            name: litellm-config  

Reference Kubernetes service.yaml that was load tested by us

apiVersion: v1
kind: Service
metadata:
  name: litellm-service
spec:
  selector:
    app: litellm
  ports:
    - protocol: TCP
      port: 4000
      targetPort: 4000
  type: LoadBalancer