fixed CPU benchmarking typos and small formatting
parent
ce01c06fef
commit
2be9109797
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@ -27,7 +27,7 @@ elif [[ ${OS} == "Linux" ]]; then
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fi
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# calc average each non-autopause test target
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calcAvarageNonAutopause() {
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calcAverageNonAutopause() {
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for target in ${TESTS_TARGETS[@]}; do
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nap_count=0;
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nap_total=0;
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@ -50,7 +50,7 @@ calcAvarageNonAutopause() {
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}
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# calc average each autopause test target
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calcAvarageAutopause() {
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calcAverageAutopause() {
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for target in ${TESTS_TARGETS[@]}; do
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if [[ "${target}" == "minikube."* ]]; then
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ap_count=0;
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@ -85,8 +85,8 @@ updateAutopauseSummary() {
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}
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}
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calcAvarageNonAutopause
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calcAverageNonAutopause
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updateNonAutopauseSummary
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calcAvarageAutopause
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calcAverageAutopause
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updateAutopauseSummary
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@ -26,7 +26,7 @@ elif [[ ${OS} == "Linux" ]]; then
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fi
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# calc average each test target
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calcAvarage() {
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calcAverage() {
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for target in ${TESTS_TARGETS[@]}; do
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count=0;
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total=0;
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@ -51,5 +51,5 @@ updateSummary() {
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}
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}
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calcAvarage
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calcAverage
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updateSummary
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@ -1,45 +1,45 @@
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---
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title: "CPU Usage Benchmarks(Linux)"
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linkTitle: "CPU Usage Benchmarks(Linux)"
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title: "CPU Usage Benchmarks (Linux)"
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linkTitle: "CPU Usage Benchmarks (Linux)"
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weight: 1
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---
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## CPU% Busy Overhead - Avarage first 5 minutes only
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## CPU% Busy Overhead - Average first 5 minutes only
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This chart shows each tool's CPU busy overhead percentage.
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After each tool's starting, we measured each tool's idle for 5 minutes.
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This chart was measured only after the start without deploying any pods.
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This chart shows each tool's CPU busy overhead percentage.
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After each tool's starting, we measured each tool's idle for 5 minutes.
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This chart was measured only after the start without deploying any pods.
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1. start each local kubernetes tool
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2. measure its cpu usage with [cstat](https://github.com/tstromberg/cstat)
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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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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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This chart shows each tool's CPU busy overhead percentage with auto-pause addon.
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The auto-pause is mechanism which reduce CPU busy usage by pausing kube-apiserver.
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We compare CPU usage after deploying sample application(nginx deployment) to all tools(including minikube and other tools).
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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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This chart shows each tool's CPU busy overhead percentage with auto-pause addon.
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The auto-pause is mechanism which reduce CPU busy usage by pausing kube-apiserver.
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We compare CPU usage after deploying sample application (nginx deployment) to all tools (including minikube and other tools).
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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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1. start each local kubernetes tool
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2. deploy sample application(nginx deployment) to each tool
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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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4. measure No.3 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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5. if tool is minikube, enable auto-pause addon which pause control plane
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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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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. 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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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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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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@ -1,14 +1,14 @@
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---
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title: "CPU Usage Benchmarks(macOS)"
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linkTitle: "CPU Usage Benchmarks(macOS)"
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title: "CPU Usage Benchmarks (macOS)"
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linkTitle: "CPU Usage Benchmarks (macOS)"
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weight: 1
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---
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## CPU% Busy Overhead - Avarage first 5 minutes only
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## CPU% Busy Overhead - Average first 5 minutes only
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This chart shows each tool's CPU busy overhead percentage.
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After each tool's starting, we measured each tool's idle for 5 minutes.
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This chart was measured only after the start without deploying any pods.
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This chart shows each tool's CPU busy overhead percentage.
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After each tool's starting, we measured each tool's idle for 5 minutes.
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This chart was measured only after the start without deploying any pods.
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1. start each local kubernetes tool
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2. measure its cpu usage with [cstat](https://github.com/tstromberg/cstat)
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@ -17,23 +17,23 @@ This chart was measured only after the start without deploying any pods.
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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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The auto-pause is mechanism which reduce CPU busy usage by pausing kube-apiserver.
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We compare CPU usage after deploying sample application(nginx deployment) to all tools(including minikube and other tools).
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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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This chart shows each tool's CPU busy overhead percentage with auto-pause addon.
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The auto-pause is mechanism which reduce CPU busy usage by pausing kube-apiserver.
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We compare CPU usage after deploying sample application (nginx deployment) to all tools (including minikube and other tools).
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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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1. start each local kubernetes tool
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2. deploy sample application(nginx deployment) to each tool
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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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4. measure No.3 idle CPU usage with [cstat](https://github.com/tstromberg/cstat)
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5. if tool is minikube, enable auto-pause addon which pause control plane
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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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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. 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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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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