.github/workflows | ||
.gitignore | ||
api.go | ||
archive.go | ||
config.json | ||
debug.go | ||
float.go | ||
go.mod | ||
go.sum | ||
LICENSE | ||
lineprotocol_test.go | ||
lineprotocol.go | ||
memoryStore_test.go.orig | ||
memstore_test.go | ||
memstore.go | ||
metric-store.go | ||
openapi.yaml | ||
README.md | ||
selector.go | ||
stats.go | ||
TODO.md |
ClusterCockpit Metric Store
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 aggregations over time and nodes/sockets/cpus.
Go look at the TODO.md
file and the GitHub Issues for a progress overview. Things work, but are not properly tested.
The NATS.io based writing endpoint consumes messages in this format of the InfluxDB line protocol.
REST API Endpoints
The REST API is documented in openapi.yaml in the OpenAPI 3.0 format.
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?
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.
This is what the hierarchy currently looks like:
- cluster1
- host1
- socket0
- socket1
- ...
- cpu1
- cpu2
- cpu3
- cpu4
- ...
- host2
- ...
- host1
- cluster2
- ...
Example selectors:
["cluster1", "host1", "cpu0"]
: Select only the cpu0 of host1 in cluster1["cluster1", "host1", ["cpu4", "cpu5", "cpu6", "cpu7"]]
: Select only CPUs 4-7 of host1 in cluster1["cluster1", "host1"]
: Select the complete node. If querying for a CPU-specific metric such as floats, all CPUs are implied
Config file
All durations are specified in seconds.
metrics
: Map of metric-name to objects with the following propertiesfrequency
: Timestep/Interval/Resolution of this metric (In seconds)aggregation
: Can be"sum"
,"avg"
ornull
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 (Theupdates
channel will be subscribed for metrics), example: "nats://localhost:4222"http-api-address
: Where to listen via HTTP, example: ":8080"jwt-public-key
: Base64 encoded string, use this to verify requests to the HTTP APIretention-on-memory
: Keep all values in memory for at least that amount of seconds
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. 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\": $(date +%s), \"queries\": [{
\"metric\": \"load_one\",
\"hostname\": \"$(hostname)\"
}] }"
# ...