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docs/integration-ebpf.mdx

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@@ -24,12 +24,6 @@ eBPF is an emerging Linux kernel technology that allows for user-supplied progra
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|:------------:|:------------:|:-----:|:-----:|:-------:|:------:|
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| ebpfspy | `embedded` || | ||
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### Benefits and Tradeoffs of using eBPF for continuous profiling
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We added a blog post "[The pros and cons of eBPF profiling](/blog/ebpf-profiling-pros-cons)" which more deeply
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explores this topic and provides some examples of eBPF profiles. If you're interested in some of the more
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granular details you can find them there!
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### Getting Started with eBPF Profiling
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For the reasons mentioned above, we recommend an hybrid approach for better results: eBPF to profile the node and specific language instrumentation per application. The following steps will explain how to get started:
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| env var | default | description |
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| -------------------------- | -------------------------------- | ---------------------------------------------- |
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| `PYROSCOPE_KUBERNETES_NODE` | `""` | Used by service discovery. It's automatically set in the Helm Chart. |
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| `PYROSCOPE_ONLY_SERVICES` | `false` | Ignore processes unknown to service discovery. In a Kubernetes cluster it ignores processes like `containerd, runc, kubelet` etc |
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| `PYROSCOPE_ONLY_SERVICES` | `false` | Ignore processes unknown to service discovery. In a Kubernetes cluster it ignores processes like `containerd, runc, kubelet` etc |
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| `PYROSCOPE_SYMBOL_CACHE_SIZE` | `256` | Max size of symbols cache (1 entry per process). Change this value if you’re experiencing memory pressure or have many individual services. |
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### Sending data to Phlare with Pyroscope eBPF integration

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