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翻訳待ち
eBPF distributed networking observability tool for Kubernetes
翻訳待ち
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Read the full README ↗Retina is a cloud-agnostic, open-source Kubernetes network observability platform that provides a centralized hub for monitoring application health, network health, and security. It provides actionable insights to cluster network administrators, cluster security administrators, and DevOps engineers navigating DevOps, SecOps, and compliance use cases.
Retina collects customizable telemetry, which can be exported to multiple storage options (such as Prometheus, Azure Monitor, and other vendors) and visualized in a variety of ways (like Grafana, Azure Log Analytics, and other vendors).
Retina lets you investigate network issues on-demand and continuously monitor your clusters. For scenarios where Retina shines, see the intro docs here
See retina.sh for documentation and examples.
⚠️ Performance on High-Core-Count Systems: Community users have reported performance considerations when using Advanced metrics (with packetparser plugin) on nodes with 32+ CPU cores under high network load. Consider starting with Basic metrics mode on large node types. See Known Limitations for details.
⚠️ Windows Server 2019: Retina no longer supports Windows Server 2019 nodes. Use Windows Server 2022 for Windows workloads.
Retina has two major features:
Retina can be installed using the Helm chart from GHCR:
# Set the version to a specific version here or get latest version from GitHub API.
VERSION=$( curl -sL https://api.github.com/repos/microsoft/retina/releases/latest | jq -r .name)
helm upgrade --install retina oci://ghcr.io/microsoft/retina/charts/retina \
--version $VERSION \
--set image.tag=$VERSION \
--set operator.tag=$VERSION \
--set logLevel=info \
--set enabledPlugin_linux="\[dropreason\,packetforward\,linuxutil\,dns\]"
Set the version and image tag arguments to the desired version, if different.
After Helm install, follow the steps for setting up Prometheus and Grafana to configure metrics collection and visualization.
The preferred way to install the Retina CLI using Krew.
kubectl krew install retina
Other installation options are documented in CLI Installation.
Verify installation:
$ kubectl retina
Retina is an eBPF distributed networking observability tool for Kubernetes.
Usage:
kubectl-retina [command]
Available Commands:
capture Capture network traffic
completion Generate the autocompletion script for the specified shell
config Configure retina CLI
help Help about any command
shell [EXPERIMENTAL] Interactively debug a node or pod
trace Retrieve status or results from Retina
version Show version
Flags:
-h, --help help for kubectl-retina
Use "kubectl-retina [command] --help" for more information about a command.
To quickly start creating a capture:
kubectl retina capture create --pod-selectors <app=my-app>
For further CLI documentation, see Capture with Retina CLI.
Install Retina using Helm:
VERSION=$( curl -sL https://api.github.com/repos/microsoft/retina/releases/latest | jq -r .name)
helm upgrade --install retina oci://ghcr.io/microsoft/retina/charts/retina \
--version $VERSION \
--set image.tag=$VERSION \
--set operator.tag=$VERSION \
--set image.pullPolicy=Always \
--set logLevel=info \
--set os.windows=true \
--set operator.enabled=true \
--set operator.enableRetinaEndpoint=true \
--skip-crds \
--set enabledPlugin_linux="\[dropreason\,packetforward\,linuxutil\,dns\,packetparser\]"
Then follow steps in Capture CRD for documentation of the CRD and examples for setting up Captures.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
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