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ClusterCockpit Metric Store

Build & Test

The cc-metric-store provides a simple in-memory time series database for storing metrics of cluster nodes at preconfigured intervals. It is meant to be used as part of the ClusterCockpit suite. As all data is kept in-memory (but written to disk as compressed JSON for long term storage), accessing it is very fast. It also provides topology aware aggregations over time and nodes/sockets/cpus.

There are major limitations: Data only gets written to disk at periodic checkpoints, not as soon as it is received. Also only the fixed configured duration is stored and available.

Go look at the GitHub Issues for a progress overview. The NATS.io based writing endpoint consumes messages in this format of the InfluxDB line protocol.

Building

cc-metric-store can be built using the provided Makefile. It supports the following targets:

  • make: Build the application, copy a example configuration file and generate checkpoint folders if required.
  • make clean: Clean the golang build cache and application binary
  • make distclean: In addition to the clean target also remove the ./var folder
  • make swagger: Regenerate the Swagger files from the source comments.
  • make test: Run test and basic checks.

REST API Endpoints

The REST API is documented in swagger.json. You can explore and try the REST API using the integrated SwaggerUI web interface.

For more information on the cc-metric-store REST API have a look at the ClusterCockpit documentation website

Run tests

Some benchmarks concurrently access the MemoryStore, so enabling the Race Detector might be useful. The benchmarks also work as tests as they do check if the returned values are as expected.

# Tests only
go test -v ./...

# Benchmarks as well
go test -bench=. -race -v ./...

What are these selectors mentioned in the code?

The cc-metric-store works as a time-series database and uses the InfluxDB line protocol as input format. Unlike InfluxDB, the data is indexed by one single strictly hierarchical tree structure. A selector is build out of the tags in the InfluxDB line protocol, and can be used to select a node (not in the sense of a compute node, can also be a socket, cpu, ...) in that tree. The implementation calls those nodes level to avoid confusion. It is impossible to access data only by knowing the socket or cpu tag, all higher up levels have to be specified as well.

This is what the hierarchy currently looks like:

  • cluster1
    • host1
      • socket0
      • socket1
      • ...
      • cpu1
      • cpu2
      • cpu3
      • cpu4
      • ...
      • gpu1
      • gpu2
    • host2
    • ...
  • cluster2
  • ...

Example selectors:

  1. ["cluster1", "host1", "cpu0"]: Select only the cpu0 of host1 in cluster1
  2. ["cluster1", "host1", ["cpu4", "cpu5", "cpu6", "cpu7"]]: Select only CPUs 4-7 of host1 in cluster1
  3. ["cluster1", "host1"]: Select the complete node. If querying for a CPU-specific metric such as floats, all CPUs are implied

Config file

You find the configuration options on the ClusterCockpit website.

Test the complete setup (excluding cc-backend itself)

There are two ways for sending data to the cc-metric-store, both of which are supported by the cc-metric-collector. This example uses NATS, the alternative is to use HTTP.

# Only needed once, downloads the docker image
docker pull nats:latest

# Start the NATS server
docker run -p 4222:4222 -ti nats:latest

Second, build and start the cc-metric-collector using the following as Sink-Config:

{
  "type": "nats",
  "host": "localhost",
  "port": "4222",
  "database": "updates"
}

Third, build and start the metric store. For this example here, the config.json file already in the repository should work just fine.

# Assuming you have a clone of this repo in ./cc-metric-store:
cd cc-metric-store
make
./cc-metric-store

And finally, use the API to fetch some data. The API is protected by JWT based authentication if jwt-public-key is set in config.json. You can use this JWT for testing: eyJ0eXAiOiJKV1QiLCJhbGciOiJFZERTQSJ9.eyJ1c2VyIjoiYWRtaW4iLCJyb2xlcyI6WyJST0xFX0FETUlOIiwiUk9MRV9BTkFMWVNUIiwiUk9MRV9VU0VSIl19.d-3_3FZTsadPjDEdsWrrQ7nS0edMAR4zjl-eK7rJU3HziNBfI9PDHDIpJVHTNN5E5SlLGLFXctWyKAkwhXL-Dw

JWT="eyJ0eXAiOiJKV1QiLCJhbGciOiJFZERTQSJ9.eyJ1c2VyIjoiYWRtaW4iLCJyb2xlcyI6WyJST0xFX0FETUlOIiwiUk9MRV9BTkFMWVNUIiwiUk9MRV9VU0VSIl19.d-3_3FZTsadPjDEdsWrrQ7nS0edMAR4zjl-eK7rJU3HziNBfI9PDHDIpJVHTNN5E5SlLGLFXctWyKAkwhXL-Dw"

# If the collector and store and nats-server have been running for at least 60 seconds on the same host, you may run:
curl -H "Authorization: Bearer $JWT" -D - "http://localhost:8080/api/query" -d "{ \"cluster\": \"testcluster\", \"from\": $(expr $(date +%s) - 60), \"to\": $(date +%s), \"queries\": [{
  \"metric\": \"load_one\",
  \"host\": \"$(hostname)\"
}] }"

# ...

For debugging there is a debug endpoint to dump the current content to stdout:

JWT="eyJ0eXAiOiJKV1QiLCJhbGciOiJFZERTQSJ9.eyJ1c2VyIjoiYWRtaW4iLCJyb2xlcyI6WyJST0xFX0FETUlOIiwiUk9MRV9BTkFMWVNUIiwiUk9MRV9VU0VSIl19.d-3_3FZTsadPjDEdsWrrQ7nS0edMAR4zjl-eK7rJU3HziNBfI9PDHDIpJVHTNN5E5SlLGLFXctWyKAkwhXL-Dw"

# If the collector and store and nats-server have been running for at least 60 seconds on the same host, you may run:
curl -H "Authorization: Bearer $JWT" -D - "http://localhost:8080/api/debug"

# ...