Modern platforms usually treat observability as three core signals:

• Metrics
• Logs
• Traces

OpenTelemetry (OTel) is the standard way to produce and ship all three signals. This article explains a practical setup for InterSystems IRIS running in Docker Compose, with a full local observability stack:

• Prometheus (metrics)
• Loki (logs)
• Tempo (traces, for Grafana Traces Drilldown)
• Jaeger (optional, alternate trace viewer)
• Grafana (unified UI)
• OpenTelemetry Collector

What you’ll build

• IRIS emits OTLP/HTTP telemetry to the OpenTelemetry Collector
• Collector routes:
  • traces -> Tempo (for Grafana)/Jaeger (alternate trace UI)
  • metrics -> Prometheus
  • logs -> Loki
• Grafana reads from Prometheus + Tempo + Jaeger + Loki and shows everything in one place

You can download the full working Docker Compose example here: https://github.com/isc-jyin/iris-otel-example

Prerequisites

• Docker

Step-by-Step Guide

1. Create a folder structure

otel-minimal-config/
  iris/
    cpf-merge.cpf
  configs/
    otel-collector-config.yaml
    prometheus.yaml
    tempo.yaml
    grafana/
      provisioning/
        datasources/
          datasources.yaml
  docker-compose.yaml
  README.md
  README.pdf

2. Configure the OpenTelemetry Collector

The Collector is the router that receives OTLP from IRIS, then exports to each backend in the correct format. 

Create otel-collector-config.yaml:

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318
exporters:
  # export Metrics to Prometheus for viewing
  prometheus:
    endpoint: "0.0.0.0:8889"
  # export traces to Jaeger for viewing
  otlp/jaeger:
    endpoint: jaeger:4317
    tls:
      insecure: true
  otlphttp/loki:
    endpoint: "http://loki:3100/otlp"
    tls:
      insecure: true
  otlp/tempo:
    endpoint: tempo:4317
    tls:
      insecure: true
  debug:
    verbosity: detailed
processors:
  batch:
service:
  pipelines:
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [prometheus]
    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlphttp/loki, debug]
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp/jaeger, otlp/tempo, debug]

3. Configure Prometheus scraping

Prometheus scrapes metrics from an HTTP endpoint exposed by the Collector. It also stores metrics generated by Tempo.

Create prometheus.yaml:

scrape_configs:
  - job_name: 'otel-collector'
    scrape_interval: 10s
    static_configs:
      - targets: ['otel-collector:8889']
      - targets: ['otel-collector:8888']

4. Configure Tempo

Tempo is the trace backend that Grafana's Traces Drilldown needs. We also enable Tempo's metrics generator so Grafana can build metrics (rate/errors/duration) from traces. 

Create tempo.yaml:

server:
  http_listen_port: 3200
distributor:
  receivers:
    otlp:
      protocols:
        grpc:
          endpoint: "tempo:4317"
storage:
  trace:
    backend: local
    local:
      path: /tmp/tempo/traces
    wal:
      path: /tmp/tempo/wal
metrics_generator:
  registry:
    external_labels:
      source: tempo
      cluster: docker-compose
  storage:
    path: /var/tempo/generator/wal
    remote_write:
      - url: http://prometheus:9090/api/v1/write
        send_exemplars: true
  traces_storage:
    path: /var/tempo/generator/traces
overrides:
  defaults:
    metrics_generator:
      processors: [service-graphs, span-metrics, local-blocks] # enables metrics generator
      generate_native_histograms: both

5. Configure Grafana datasources

Grafana reads from Prometheus + Tempo + Jaeger + Loki and shows everything in one place

Create datasources.yaml:

apiVersion: 1
datasources:
- name: Loki
  type: loki
  access: proxy
  url: http://loki:3100
- name: Prometheus
  type: prometheus
  access: proxy
  url: http://prometheus:9090
  isDefault: true
- name: Jaeger
  type: jaeger
  access: proxy
  url: http://jaeger:16686
- name: Tempo
  type: tempo
  access: proxy
  url: http://tempo:3200

6. Enable OTel metrics and logs in IRIS

Create iris.cpf

[Monitor]
OTELMetrics=1
OTELLogs=1
OTELLogLevel=INFO

7. Create docker-compose.yaml

Compose starts everything consistently under the same network, so DNS names like tempo, loki, otel-collector work.

services:
  iris:
    image: containers.intersystems.com/intersystems/iris-community:2025.3
    environment:
    - ISC_CPF_MERGE_FILE=/iris/cpf-merge.cpf
    - OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4318
    - OTEL_EXPORTER_OTLP_TIMEOUT=500
    - OTEL_SERVICE_NAME=iris
    depends_on:
    - otel-collector
    volumes:
      - ./iris:/iris
  otel-collector:
    image: otel/opentelemetry-collector-contrib:0.143.0
    command: ["--config=/etc/otel-collector-config.yaml"]
    volumes:
      - ./configs/otel-collector-config.yaml:/etc/otel-collector-config.yaml:ro
  tempo:
    image: grafana/tempo:latest
    command: ["-config.file=/etc/tempo.yaml"]
    volumes:
      - ./configs/tempo.yaml:/etc/tempo.yaml:ro
    ports:
      - 3200
      - 4317
  loki:
    image: grafana/loki:latest
    ports:
      - 3100
  prometheus:
    image: prom/prometheus:v3.9.1
    volumes:
     - ./configs/prometheus.yaml:/etc/prometheus/prometheus.yml:ro
    ports:
      - "9090:9090"
  # Jaeger
  jaeger:
    image: jaegertracing/all-in-one:1.76.0
    ports:
      - "16686:16686"
      - 4317
    environment:
      - LOG_LEVEL=debug
  grafana:
    image: grafana/grafana:12.3.1
    environment:
      - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin
      - GF_AUTH_ANONYMOUS_ENABLED=true
      - GF_AUTH_BASIC_ENABLED=false
      - GF_FEATURE_TOGGLES_ENABLE=traceqlEditor
    volumes:
      - ./configs/grafana/provisioning:/etc/grafana/provisioning:ro
    ports:
      - 3000:3000/tcp
    depends_on:
      - prometheus
      - loki
      - jaeger
  

8. Start the stack

Start the environment

docker compose up -d

Open a terminal session in the IRIS container:

docker compose exec iris iris session IRIS

Then run the built-in trace demo:

Do ##class(%Trace.Tracer).Test()

9. Viewing Results

Grafana - Traces + Metrics + Logs

Open http://localhost:3000/drilldown

Metrics:

Logs:

Traces:

Jaeger - Traces

Open http://localhost:16686

Prometheus - Metrics

Open http://localhost:9090