Elasticsearch Logging with LiteLLM

Send your LLM requests, responses, costs, and performance data to Elasticsearch for analytics and monitoring using OpenTelemetry.

Quick Start

1. Start Elasticsearch

# Using Docker (simplest)
docker run -d \\
  --name elasticsearch \\
  -p 9200:9200 \\
  -e "discovery.type=single-node" \\
  -e "xpack.security.enabled=false" \\
  docker.elastic.co/elasticsearch/elasticsearch:8.18.2

2. Set up OpenTelemetry Collector

Create an OTEL collector configuration file otel_config.yaml:

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

processors:
  batch:
    timeout: 1s
    send_batch_size: 1024

exporters:
  debug:
    verbosity: detailed
  otlphttp/elastic:
    endpoint: "http://localhost:9200"
    headers: 
      "Content-Type": "application/json"

service:
  pipelines:
    metrics:
      receivers: [otlp]
      exporters: [debug, otlphttp/elastic]
    traces:
      receivers: [otlp]
      exporters: [debug, otlphttp/elastic]
    logs: 
      receivers: [otlp]
      exporters: [debug, otlphttp/elastic]

Start the OpenTelemetry collector:

docker run -p 4317:4317 -p 4318:4318 \\
    -v $(pwd)/otel_config.yaml:/etc/otel-collector-config.yaml \\
    otel/opentelemetry-collector:latest \\
    --config=/etc/otel-collector-config.yaml

3. Install OpenTelemetry Dependencies

uv add opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp

4. Configure LiteLLM

Create a config.yaml file:

model_list:
  - model_name: gpt-4.1
    litellm_params:
      model: openai/gpt-4.1
      api_key: os.environ/OPENAI_API_KEY

litellm_settings:
  callbacks: ["otel"]

general_settings:
  otel: true

Set environment variables and start the proxy:

litellm --config config.yaml

Configure OpenTelemetry in your Python code:

# Configure OpenTelemetry
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "http://localhost:4317"

# Enable OTEL logging
litellm.callbacks = ["otel"]

# Make your LLM calls
response = litellm.completion(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "Hello, world!"}]
)

5. Test the Integration

Make a test request to verify logging is working:

curl -X POST "http://localhost:4000/v1/chat/completions" \\
  -H "Content-Type: application/json" \\
  -H "Authorization: Bearer sk-1234" \\
  -d '{
    "model": "gpt-4.1",
    "messages": [{"role": "user", "content": "Hello from LiteLLM!"}]
  }'

response = litellm.completion(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "Hello from LiteLLM!"}],
    user="test-user"
)
print("Response:", response.choices[0].message.content)

6. Verify It's Working

# Check if traces are being created in Elasticsearch
curl "localhost:9200/_search?pretty&size=1"

You should see OpenTelemetry trace data with structured fields for your LLM requests.

7. Visualize in Kibana

Start Kibana to visualize your LLM telemetry data:

docker run -d --name kibana --link elasticsearch:elasticsearch -p 5601:5601 docker.elastic.co/kibana/kibana:8.18.2

Open Kibana at http://localhost:5601 and create an index pattern for your LiteLLM traces:

Production Setup

With Elasticsearch Cloud:

Update your otel_config.yaml:

exporters:
  otlphttp/elastic:
    endpoint: "https://your-deployment.es.region.cloud.es.io"
    headers: 
      "Authorization": "Bearer your-api-key"
      "Content-Type": "application/json"

Docker Compose (Full Stack):

# docker-compose.yml
version: '3.8'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.18.2
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=false
    ports:
      - "9200:9200"
      
  otel-collector:
    image: otel/opentelemetry-collector:latest
    command: ["--config=/etc/otel-collector-config.yaml"]
    volumes:
      - ./otel_config.yaml:/etc/otel-collector-config.yaml
    ports:
      - "4317:4317"
      - "4318:4318"
    depends_on:
      - elasticsearch
      
  litellm:
    image: docker.litellm.ai/berriai/litellm:main-latest
    ports:
      - "4000:4000"
    environment:
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4317
    command: ["--config", "/app/config.yaml"]
    volumes:
      - ./config.yaml:/app/config.yaml
    depends_on:
      - otel-collector

config.yaml:

model_list:
  - model_name: gpt-4.1
    litellm_params:
      model: openai/gpt-4.1
      api_key: os.environ/OPENAI_API_KEY

litellm_settings:
  callbacks: ["otel"]

general_settings:
  master_key: sk-1234
  otel: true