ClusterCockpit Metric Store

Barely unusable yet. Go look at the GitHub Issues for a progress overview.

REST API Endpoints

TODO... (For now, look at the examples below)

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 and API?

Tags in InfluxDB are used to build indexes over the stored data. InfluxDB-Tags have no relation to each other, they do not depend on each other and have no hierarchy. Different tags build up different indexes (I am no expert at all, but this is how i think they work).

This project also works as a time-series database and uses the InfluxDB line protocol. 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.

Metrics have to be specified in advance! Those are taken from the fields of a line-protocol message. New levels will be created on the fly at any depth, meaning that the clusters, hosts, sockets, number of cpus, and so on do not have to be known at startup. Every level can hold all kinds of metrics. If a level is asked for metrics it does not have itself, all child-levels will be asked for their values for that metric and the data will be aggregated on a per-timestep basis.

A.t.m., the cc-metric-collector does not provide a socket tag for cpu metrics, so currently, the tree structure looks like this (example selector: ["cluster1", "host1", "cpu", "0"]):

cluster1
- host1
  - socket
    - 0
    - 1
  - cpu
    - 0
    - 1
    - 2
    - ...
- host2
- ...
cluster2
...

The plan is later to have the structure look like this (for this, the socket of every cpu must be kown in advance or provided as tag, example selector: ["cluster1", "host1", "socket0", "cpu0"]):

cluster1
- host1
  - socket0
    - cpu0
    - cpu1
    - cpu2
    - ...
  - socket1
    - cpu8
    - cpu9
    - cpu10
    - ...
  - ...
- host2
- ...
cluster2
...

Config file

metrics: Map of metric-name to objects with the following properties
- frequency: Timestep/Interval/Resolution of this metric (In seconds)
- aggregation: Can be "sum", "avg" or null
  - null means aggregation across nodes is forbidden for this metric
  - "sum" means that values from the child levels are summed up for the parent level
  - "avg" means that values from the child levels are averaged for the parent level
- scope: Unused at the moment, should be something like "node", "socket" or "cpu"
nats: Url of NATS.io server (The updates channel will be subscribed for metrics)
archive-root: Directory to be used as archive
restore-last-hours: After restart, load data from the past X hours back to memory
checkpoint-interval-hours: Every X hours, write currently held data to disk

Test the complete setup (excluding ClusterCockpit itself)

First, get a NATS server running:

# 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 config.json:

{
    "sink": {
        "type": "nats",
        "host": "localhost",
        "port": "4222",
        "database": "updates"
    },
    "interval" : 3,
    "duration" : 1,
    "collectors": [ "likwid", "loadavg" ],
    "default_tags": { "cluster": "testcluster" },
    "receiver": { "type": "none" }
}

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
go get
go build
./cc-metric-store

And finally, use the API to fetch some data:

# If the collector and store and nats-server have been running for at least 60 seconds on the same host, you may run:
curl -D - "http://localhost:8080/api/$(expr $(date +%s) - 60)/$(date +%s)/timeseries" -d "{ \"selectors\": [[\"testcluster\", \"$(hostname)\"]], \"metrics\": [\"load_one\"] }"

# Get flops_any for all CPUs:
curl -D - "http://localhost:8080/api/$(expr $(date +%s) - 60)/$(date +%s)/timeseries" -d "{ \"selectors\": [[\"testcluster\", \"$(hostname)\", \"cpu\"]], \"metrics\": [\"flops_any\"] }"

# Get flops_any for CPU 0:
curl -D - "http://localhost:8080/api/$(expr $(date +%s) - 60)/$(date +%s)/timeseries" -d "{ \"selectors\": [[\"testcluster\", \"$(hostname)\", \"cpu\", \"0\"]], \"metrics\": [\"flops_any\"] }"

# Stats for load_one and proc_run:
curl -D - "http://localhost:8080/api/$(expr $(date +%s) - 60)/$(date +%s)/stats" -d "{ \"selectors\": [[\"testcluster\", \"$(hostname)\"]], \"metrics\": [\"load_one\", \"proc_run\"] }"

# Stats for *all* CPUs aggregated both from CPU to node and over time:
curl -D - "http://localhost:8080/api/$(expr $(date +%s) - 60)/$(date +%s)/stats" -d "{ \"selectors\": [[\"testcluster\", \"$(hostname)\", \"cpu\"]], \"metrics\": [\"flops_sp\", \"flops_dp\"] }"


# ...

5.9 KiB Raw Blame History