In our November 2024 release we have added an option to enable Java Agent to monitor the dashboard to collect metrics, traces and logs for observability.
You can find info about enabling this feature by checking out our November 2024 release notes - November 2024 - Dashboard Release Notes
Example:Example:
This configuration bellow will do the following:
Launch the Dashboard with Java Agent Enabled: The application is started with the OpenTelemetry Java agent, which uses the OTLP exporter configured. This setup will allow the application to send telemetry data (traces and metrics in this example) to the OpenTelemetry Collector for further processing.
Collect and Process Telemetry Data: The OpenTelemetry Collector will be set up to receive telemetry data from the application via OTLP protocols (HTTP on port
4318and gRPC on port4317).Export Metrics: The processed metrics will then exposed for Prometheus to scrape at the endpoint
0.0.0.0:8889. This integration will allows real-time monitoring and visualisation of the dashboard’s performance.Export Traces: The OpenTelemetry Collector will forward the traces to Zipkin, a distributed tracing system. Zipkin will visualise these traces, helping track the flow of requests across the dashboard and identify any performance bottlenecks or failures.
First we need to define the configuration file for OpenTelemetry Collector. Example:
config.yml
| Code Block |
|---|
receivers:
otlp: # Defines the OTLP receiver to accept telemetry data (traces/metrics)
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
processors:
batch/traces:
timeout: 1s
send_batch_size: 50
batch/metrics:
timeout: 1s
send_batch_size: 50
exporters:
prometheus:
endpoint: 0.0.0.0:8889 # The network address and port where Prometheus can scrape metrics
zipkin:
endpoint: "http://zipkin:9411/api/v2/spans" # Traces are exported to Zipkin at defined url
service:
pipelines:
metrics:
receivers: [otlp]
processors: [batch/metrics]
exporters: [prometheus]
traces:
receivers: [otlp]
processors: [batch/traces]
exporters: [zipkin] |
We then define a configuration file for Prometheus. Example:
prometheus.yml
| Code Block |
|---|
global:
scrape_interval: 15s # Default time interval between scrapes for all jobs unless overridden
evaluation_interval: 15s # Default time interval to evaluate alerting and recording rules
scrape_configs:
- job_name: 'example'
metrics_path: '/metrics' # Endpoint where metrics are exposed for the target
scrape_interval: 5s # Override the global `scrape_interval` to scrape this job every 5 seconds
static_configs:
- targets: ['otel-collector:8889'] # The address of the target to scrape |
We then put everything together in one docker compose file. This will include:
Latest version of the dashboard with environment variables defined that will enable Java Agent and will have endpoint and service name specified
External db
OpenTelemetry Collector
Prometheus for scraping metrics
Zipkin for tracing
docker-compose.yml
| Code Block |
|---|
services:
dashboard:
image: ${LATEST_DASHBOARD_IMAGE}
ports:
- 8226:8226
environment:
PI_DB_HOST: database
PI_DB_PASSWORD: password
PI_DB_USERNAME: root
PI_DB_SCHEMA_NAME: dashboard
PI_DB_PORT: 3306
PI_EXTERNAL_DB: "true"
PI_LICENCE: ${LICENCE_KEY}
PI_TOMCAT_MONITORING_ENABLED: "true"
PI_TOMCAT_MONITORING_OTLP_EXPORTER_ENDPOINT: "http://otel-collector:4318"
PI_TOMCAT_MONITORING_OTLP_EXPORTER_PROTOCOL: "http/protobuf"
PI_TOMCAT_MONITORING_SERVICE_NAME: "pi-dashboard"
PI_TOMCAT_PORT: 8226
healthcheck:
test: [ "CMD", "/bin/bash", "/var/panintelligence/tomcat_healthcheck.sh" ]
interval: 10s
start_period: 60s
retries: 3
database:
image: mariadb:10.9.4
environment:
MARIADB_DATABASE: dashboard
MARIADB_ROOT_PASSWORD: password
LANG: C.UTF-8
command: --lower_case_table_names=1 --character-set-server=utf8mb4 --collation-server=utf8mb4_unicode_ci
restart: always
ports:
- "3306:3306"
otel-collector:
image: otel/opentelemetry-collector
container_name: otel-collector
command: [ "--config=/etc/config.yml" ]
volumes:
- /path_to_config_files/config.yml:/etc/config.yml # Mounts the local collector configuration file into the container at the specified path
ports:
- "4317:4317" # OTLP gRPC protocol for receiving telemetry data
- "4318:4318" # MOTLP HTTP protocol for receiving telemetry data
- "8889:8889" # Maps port 8889 for Prometheus scraping metrics from the collector
prometheus:
image: prom/prometheus:latest
container_name: prometheus
ports:
- "9090:9090" # Maps port 9090 for accessing the Prometheus web interface
volumes:
- /path_to_prometheus_config/prometheus.yml:/etc/prometheus/prometheus.yml # Mounts the local Prometheus configuration file into the container
zipkin:
image: openzipkin/zipkin:2.23
container_name: zipkin
ports:
- "9411:9411"
|
Things to note:
All three files (config.yml, prometheus.yml and docker-compose.yml) should exist for this example to work successfully
Amend volumes for otel-collector and prometheus - make sure to point to the correct path within your local directory
Make sure all ports specified are available
After running docker compose up, navigate to the dashboard and log in - make sure all is working nicely.
Navigate to http://localhost:8889/metrics - you will see some output from prometheus of the metrics that have been scraped. Example:
Navigate to zipkink URL (http://localhost:9411/zipkin/), click on ‘run query’. This is the output as an example:
