Comments (2)
It is a design choice to be more scalable. The native k8s Pod API is to access the API server, while the kubelet call through HTTP(s) is initiated and ended on each node. The former will stress the API server when there are many nodes, while the latter doesn't have this issue.
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Since Kepler is running on each node, it can directly access the kubelet instance without having to go through the API server. It is well known that the API server can become a bottleneck and avoiding unnecessary calls makes our system more scalable and high performing.
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Related Issues (20)
- Can we add kwok support for integration test?
- Remove BCC Code
- Evaluate using tracepoint/sched_switch over kprobe/finish_task_switch
- No value reported by Kepler latest on OpenShift HOT 7
- Audit usage of build tags
- CPU Ref Cycles in unused HOT 1
- Using bpf_perf_event_read_value causes verifier error
- Add eBPF Testing HOT 1
- "Other" metrics are out of proportion on local Kind cluster
- Kepler rpm not installable HOT 4
- Replace libbpfgo with cilium/ebpf
- Add workflow to build and push Kepler builder image
- Keep ginkgo versions in sync
- Expose Kepler version in exported metric HOT 3
- Segfault from commit e0ec4fddc3fdcc7e8de18e9e494806fb9a8659b2 HOT 2
- Transparency of Kepler information especially the power models that it is using
- Mounting volume "proc" fails for helm chart installation on containerd runtime
- kepler crashes if local regression model cannot be found
- Platform power reports value much lower than package power
- Consistent Log Levelling
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