This cluster operator gathers anonymized system configuration and reports it to Red Hat Insights. It is a part of the standard OpenShift distribution. The data collected allows for debugging in the event of cluster failures or unanticipated errors.

• Building
• Testing
• Documentation
• Getting metrics from Prometheus
  • Generate the certificate and key
  • Prometheus metrics provided by Insights Operator
  • Getting the data directly from Prometheus
  • Debugging Prometheus metrics without valid CA
• Debugging
  • Using the profiler
• Changelog
  • Updating the changelog
• Reported data
• Contributing
• Support
• License

To build the operator, install Go 1.11 or above and run:

$ make build

To test the operator against a remote cluster, run:

$ bin/insights-operator start --config=config/local.yaml --kubeconfig=$KUBECONFIG

where $KUBECONFIG has sufficiently high permissions against the target cluster.

Unit tests can be started by the following command:

$ make test

It is also possible to specify CLI options for Go test. For example, if you need to disable test results caching, use the following command:

$ VERBOSE=-count=1 make test

Integration (e2e) tests are not part of this repository, you can find it here.

The document docs/gathered-data contains the list of collected data and the API that is used to collect it. This documentation is generated by the command bellow, by collecting the comment tags located above each Gather method.

To start generating the document run:

$ make docs

Certificate and key are required to access Prometheus metrics (instead 404 Forbidden is returned). It is possible to generate these two files from Kubernetes config file. Certificate is stored in users/admin/client-cerfificate-data and key in users/admin/client-key-data. Please note that these values are encoded by using Base64 encoding, so it is needed to decode them, for example by base64 -d.

There's a tool named gen_cert_key.py that can be used to automatically generate both files. It is stored in tools subdirectory.

$ gen_cert_file.py kubeconfig.yaml

It is possible to read Prometheus metrics provided by Insights Operator. Example of metrics exposed by Insights Operator can be found at metrics.txt

Depending on how or where the IO is running you may have different ways to retrieve the metrics. Here is a list of some options, so you can find the one that fits you:

If the IO runs locally, the following command migth be used:

$ curl --cert k8s.crt --key k8s.key -k https://localhost:8443/metrics

Get the token

$ oc whoami -t

Read metrics from Pod

$ oc exec \
    -it deployment/insights-operator \
    -n openshift-insights -- \
    curl -k -H "Authorization: Bearer YOUR-TOKEN-HERE" 'https://localhost:8443/metrics'

$ sudo kubefwd svc -n openshift-monitoring -d openshift-monitoring.svc -l prometheus=k8s
$ curl --cert k8s.crt --key k8s.key  -k 'https://prometheus-k8s.openshift-monitoring.svc:9091/metrics'

Get the token

$ oc sa get-token prometheus-k8s -n openshift-monitoring

Change in pkg/controller/operator.go after creating metricsGatherKubeConfig (about line #86)

metricsGatherKubeConfig.Insecure = true
metricsGatherKubeConfig.BearerToken = "YOUR-TOKEN-HERE"
# by default CAFile is /var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt
metricsGatherKubeConfig.CAFile = "" 
metricsGatherKubeConfig.CAData = []byte{}

IO starts a profiler if given the correct environment. Set the OPENSHIFT_PROFILE env variable to "web".

$ export OPENSHIFT_PROFILE=web

After IO starts the profiling can be accessed at http://localhost:6060, you can use the pprof tool to connect to it.

Some profiling examples:

# CPU profiling for 30 seconds
$ go tool pprof http://localhost:6060/debug/pprof/profile?seconds=30

# heap profiling
$ go tool pprof http://localhost:6060/debug/pprof/heap

These commands will create a compressed file that can be visualized using a variety of tools, one of them is the pprof tool.

Starting a web ui at localhost:8080 to visualize/analyze the profiling data:

$ go tool pprof -http=:8080 /path/to/profiling.out

For extra info: check this link

You can find the project changelog by clicking here.

At ./cmd/changelog/main.go there is a script that can update the changelog for you.

It uses both the local git and GitHub`s API to update the file so:

• To get info from GitHub you will need to set the GITHUB_TOKEN envvar to a GitHub access-token.
• Make sure that you have a local, up-to-date copy of each release-branch that might be in the changelog.

It can be used 2 ways:

1. Providing no command line arguments the script will update the current CHANGELOG.md with the latest changes according to the local git state.

🚨 IMPORTANT: It will only work with changelogs created with this script

$ go run cmd/changelog/main.go

2. Providing 2 command line arguments, AFTER and UNTIL dates the script will generate a new CHANGELOG.md within the provided time frame.

$ go run cmd/changelog/main.go 2021-01-10 2021-01-20

• ClusterVersion
• ClusterOperator objects
• All non-secret global config (hostnames and URLs anonymized)

The list of all collected data with description, location in produced archive and link to Api and some examples is at docs/gathered-data.md

The resulting data is packed in .tar.gz archive with folder structure indicated in the document. Example of such archive is at docs/insights-archive-sample.

There is a sample IO archive maintained in this repo to use as a quick reference. (can be found at docs/insights-archive-sample)

To keep it up-to-date it is required to update this manually when developing a new data enhancement.

Make sure the .json files are in a humanly readable format in the sample archive. By doing this its easier to review a data enhancement PR, and rule developers can easily check what data it collects.

Run the insights-operator on a test cluster (from cluster-bot or Quicklab or etc).

This formats .json files from folder with extracted archive.

$ find . -type f -name '*.json' -print | while read line; do cat "$line" | jq > "$line.tmp" && mv "$line.tmp" "$line"; done

See CONTRIBUTING for workflow & convention details.

See STYLEGUIDE for file format and coding style guide.

Insights Operator is part of Red Hat OpenShift Container Platform. For product-related issues, please file a ticket in Red Hat Bugzilla for "Insights Operator" component.

This project is licensed by the Apache License 2.0. For more information check the LICENSE file.