• Start all services - docker compose up --build
• Generate load on the api - k6 run load/load-test.js
• View some metrics - http://localhost:6788
• Make a coffee - Let the load test run for at least 5 minutes
• Check the alerts - http://localhost:6788/explorer#/alerts

If you don't want to install k6 locally, you can run it via Docker as well:

docker run --rm -i grafana/k6 run --vus 10 --duration 30s - <load/load-test.js

You need a few tools installed on your system to run this demo:

• Docker and Docker Compose
• k6 CLI tool (brew install k6)

This is a setup for a demo service that generates embeddings from some input text.

The service has three components:

• A node.js web server that serves a simple HTML form, and accepts POST requests to /generate-embeddings with a text parameter in the body. It calls a python service (described below) to generate the embeddings, and returns a JSON response with the embeddings.

• A python service that accepts POST requests to the route /embeddings with a text parameter in the body. It returns a JSON response with BERT embeddings of the provided text.

• A postgres database that can store the embeddings (not yet integrated)

The python and node services are instrumented with the autometrics library. Their metrics data can be visualized with the Autometrics Explorer UI, which is available at http://localhost:6788.

Optionally, the k6 CLI tool can be used to generate load on the services, which will make the autometrics explorer UI far more fun to look at.

The node.js api has two SLOs:

• The API should have a 99.9% success rate
• 99% of API requests should return in under 100ms

After running the load test, which takes around 6 minutes, there should be alerts in the am explorer UI (at http://localhost:6789/explorer#/alerts) for the latency SLO.

The Docker Compose file also starts a few other services for monitoring. Most of these are started on nonstandard ports to avoid conflicts with other services you may have running on your system.

Access Prometheus via http://localhost:9099.

Access the Autometrics Explorer via http://localhost:6789/explorer.

Access Grafana via http://localhost:9011.

There you'll find a dashboard with some basic metrics about containers on your system (thanks to cAdvisor). Look for the autometrics-demo-embeddings-embeddings-1 container.

Access cAdvistor via http://localhost:8088.

Container metrics are made available via cAdvisor. However, the configuration to get these metrics is specific to running on an M1/M2 macbook.