https://github.com/ricoberger/parca-operator
Deploy and Operator Parca
https://github.com/ricoberger/parca-operator
continuous-profiling kubernetes observability parca
Last synced: 5 months ago
JSON representation
Deploy and Operator Parca
- Host: GitHub
- URL: https://github.com/ricoberger/parca-operator
- Owner: ricoberger
- License: mit
- Created: 2023-07-10T20:34:51.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-09-16T16:27:00.000Z (6 months ago)
- Last Synced: 2025-09-16T19:02:03.341Z (6 months ago)
- Topics: continuous-profiling, kubernetes, observability, parca
- Language: Go
- Homepage:
- Size: 353 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Codeowners: .github/CODEOWNERS
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README
# Parca Operator
The Parca Operator can be used to deploy and operator
[Parca](https://www.parca.dev). It can be used to deploy the
[Parca Server](https://www.parca.dev/docs/parca) and
[Parca Agent](https://www.parca.dev/docs/parca-agent). Besides that the Parca
Operator can also be used to configure the
[pull-based ingestion](https://www.parca.dev/docs/ingestion#pull-based) via
Custom Resource Definitions.
> [!NOTE]
> The Parca Operator is work in progress. While I plan to add support for the
> deployment of the Parca Server and Parca Agent, these features are not
> implemented yet.
>
> This means, that the Parca Operator can currently only be used to configure
> the pull-based ingestion via the ParcaScrapeConfig Custom Resource Definition.
## Installation
The Parca Operator can be installed via Helm:
```sh
helm upgrade --install parca-operator oci://ghcr.io/ricoberger/charts/parca-operator --version
```
Make sure that you set the following environment variables for the Parca
Operator:
- `PARCA_CONFIG_SOURCE`: The path to the configration file for Parca. This file
is used as source for the generated Parca configration and should contain the
`object_storage` configuration.
- `PARCA_CONFIG_TARGET_NAME` and `PARCA_CONFIG_TARGET_NAMESPACE`: The name and
namespace of secret which should be generated. The secret contains a
`parca.yaml` key with the generated configuration for Parca. The generated
configuration file contains the content of the source configuration and the
configuration for all scrape configuration created via a `ParcaScrapeConfig`
resource.
## API Reference
### ParcaScrapeConfig
```yaml
apiVersion: parca.ricoberger.de/v1alpha1
kind: ParcaScrapeConfig
metadata:
name:
namespace:
spec:
# Selector is the selector for the Pods which should be scraped by Parca.
selector:
matchLabels:
matchExpressions:
# ScrapeConfig is the scrape configuration as it can be set in the Parca
# configuration.
scrapeConfig:
# Job is the job name of the section in the configurtion. If no job name is
# provided, it will be automatically generated based on the name and
# namespace of the CR: "namespace/name"
job:
# Port is the name of the port of the Pods which is used to expose the
# profiling endpoints.
port:
# PortNumber is the number of the port which is used to expose the
# profiling endpoints. This can be used instead of the port field. If the
# port is not named.
portNumber:
# Params is a set of query parameters with which the target is scraped.
params:
# Interval defines how frequently to scrape the targets of this scrape
# config.
interval:
# Timeout defines the timeout for scraping targets of this config.
timeout:
# Schema sets the URL scheme with which to fetch metrics from targets.
scheme:
# ProfilingConfig defines the profiling config for the targets, see
# https://www.parca.dev/docs/ingestion#pull-based for more information.
profiling_config:
# RelabelConfigs allows dynamic rewriting of the label set for the targets,
# see https://prometheus.io/docs/prometheus/latest/configuration/configuration/#relabel_config
# for more information.
relabel_configs:
```
Example
```yaml
apiVersion: parca.ricoberger.de/v1alpha1
kind: ParcaScrapeConfig
metadata:
name: parca-server
namespace: parca
spec:
selector:
matchLabels:
app: parca-server
scrapeConfig:
port: grpc
interval: 45s
timeout: 60s
profilingConfig:
pprofConfig:
fgprof:
enabled: true
path: /debug/pprof/fgprof
```
## Development
After modifying the `*_types.go` file always run the following command to update
the generated code for that resource type:
```sh
make generate
```
The above Makefile target will invoke the
[controller-gen](https://sigs.k8s.io/controller-tools) utility to update the
`api/v1alpha1/zz_generated.deepcopy.go` file to ensure our API's Go type
definitons implement the `runtime.Object` interface that all Kind types must
implement.
Once the API is defined with spec/status fields and CRD validation markers, the
CRD manifests can be generated and updated with the following command:
```sh
make manifests
```
This Makefile target will invoke controller-gen to generate the CRD manifests at
`charts/parca-operator/crds/parca.ricoberger.de_.yaml`.
Deploy the CRD and run the operator locally with the default Kubernetes config
file present at `$HOME/.kube/config`:
```sh
export PARCA_CONFIG_SOURCE=parca.yaml
export PARCA_CONFIG_TARGET_NAME=parca-generated
export PARCA_CONFIG_TARGET_NAMESPACE=parca
make run
```