Update linux auto-pause result with improved method
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@ -5,8 +5,8 @@ These scripts are for the benchmark of cpu usage, minikube vs kind vs k3d.
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* `update_summary.sh`: create one summary csv file of each drivers and products
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* `update_summary.sh`: create one summary csv file of each drivers and products
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* `chart.go`: create bar chart graph as a png file
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* `chart.go`: create bar chart graph as a png file
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In `benchmark_local_k8s.sh`, we compare minikube drivers(hyperkit, virtualbox, docker) and kind, k3d, Docker for Mac Kubernetes in case of macOS.
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In `benchmark_local_k8s.sh`, we compare minikube drivers(hyperkit, virtualbox, docker with auto-pause addon) and kind, k3d, Docker for Mac Kubernetes in case of macOS.
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In `benchmark_local_k8s.sh`, we compare minikube drivers(kvm2, virtualbox, docker) and kind, k3d in case of Linux.
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In `benchmark_local_k8s.sh`, we compare minikube drivers(kvm2, virtualbox, docker with auto-pause addon) and kind, k3d in case of Linux.
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`benchmark_local_k8s.sh` take these steps to measure `auto-pause` vs. `non auto-pause`.
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`benchmark_local_k8s.sh` take these steps to measure `auto-pause` vs. `non auto-pause`.
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1. start each local kubernetes tool
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1. start each local kubernetes tool
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@ -12,6 +12,9 @@ This chart was measured only after the start without deploying any pods.
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NOTE: the benchmark environment uses GCE with nested virtualization. This may affect virtual machine's overhead.
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https://cloud.google.com/compute/docs/instances/enable-nested-virtualization-vm-instances
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## CPU% Busy Overhead - With Auto Pause vs. Non Auto Pause
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## CPU% Busy Overhead - With Auto Pause vs. Non Auto Pause
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This chart shows each tool's CPU busy overhead percentage with auto-pause addon.
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This chart shows each tool's CPU busy overhead percentage with auto-pause addon.
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@ -20,11 +23,19 @@ This chart was measured with the following steps.
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By these steps, we compare CPU usage with auto-pause vs. non-auto-pause.
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By these steps, we compare CPU usage with auto-pause vs. non-auto-pause.
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1. start each local kubernetes tool
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1. start each local kubernetes tool
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2. deploy sample application(nginx deployment)
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2. deploy sample application(nginx deployment) to each tool
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3. wait 1 minute without anything
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3. wait 1 minute without anything
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4. measure No.3 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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4. measure No.3 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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5. enable auto-pause addons(only if tool is minikube)
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5. if tool is minikube, enable auto-pause addon which pause control plane
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6. wait 3 minute without anything
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6. if tool is minikube, wait 1 minute so that control plane will become Paused status(It takes 1 minute to become Pause status from Stopped status)
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7. measure No.6 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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7. if tool is minikube, verify if minikube control plane is paused
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8. if tool is minikube, wait 3 minute without anything
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9. if tool is minikube, measure No.8 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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No.1-4: Initial start CPU usage with sample(nginx) deployment
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No.5-9: Auto Paused CPU usage with sample(nginx) deployment
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NOTE: the benchmark environment uses GCE with nested virtualization. This may affect virtual machine's overhead.
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https://cloud.google.com/compute/docs/instances/enable-nested-virtualization-vm-instances
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