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fixed links and commands (#7)
Signed-off-by: qinxiaowen <[email protected]>
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2-lts/step3.md

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@@ -78,7 +78,7 @@ The potential duplication of data between Prometheus+sidecar results and store G
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Another interesting question here is how to ensure if we query the data from bucket only?
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We can check this by visitng the [New UI]({{TRAFFIC_HOST1_9091}}/new/graph?g0.expr=&g0.tab=0&g0.stacked=0&g0.range_input=1h&g0.max_source_resolution=0s&g0.deduplicate=1&g0.partial_response=0&g0.store_matches=[]), inserting `continuous_app_metric0` metrics again with 1 year time range of graph,
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We can check this by visitng the [Query UI]({{TRAFFIC_HOST1_9091}}/graph?g0.expr=&g0.tab=0&g0.stacked=0&g0.range_input=1h&g0.max_source_resolution=0s&g0.deduplicate=1&g0.partial_response=0&g0.store_matches=[]), inserting `continuous_app_metric0` metrics again with 1 year time range of graph,
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and click on `Enable Store Filtering`.
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This allows us to filter stores and helps in debugging from where we are querying the data exactly.

2-lts/step4.md

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## Setup Verification
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To check if compactor works fine, we can look at the [Bucket View]({{TRAFFIC_HOST1_19095}}/new/loaded).
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To check if compactor works fine, we can look at the [Bucket View]({{TRAFFIC_HOST1_19095}}/loaded).
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Now, if we click on the blocks, they will provide us all the metadata (Series, Samples, Resolution, Chunks, and many more things).
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@@ -50,7 +50,7 @@ and no special configuration is required to perform this process.
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The Compactor applies compaction to the bucket data and also completes the downsampling for historical data.
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To expierience this, click on the [Querier]({{TRAFFIC_HOST1_9091}}/new/graph?g0.expr=&g0.tab=0&g0.stacked=0&g0.range_input=1h&g0.max_source_resolution=0s&g0.deduplicate=1&g0.partial_response=0&g0.store_matches=[]) and insert metrics `continuous_app_metric0` with 1 year time range of graph, and also, click on `Enable Store Filtering`.
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To expierience this, click on the [Querier]({{TRAFFIC_HOST1_9091}}/graph?g0.expr=&g0.tab=0&g0.stacked=0&g0.range_input=1h&g0.max_source_resolution=0s&g0.deduplicate=1&g0.partial_response=0&g0.store_matches=[]) and insert metrics `continuous_app_metric0` with 1 year time range of graph, and also, click on `Enable Store Filtering`.
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Let's try querying `Max 5m downsampling` data, it uses 5m resolution and it will be faster than the raw data. Also, Downsampling is built on top of data, and never done on **young** data.
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5-query-caching/step1.md

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for i in $(seq 0 2); do
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docker run -d --net=host --rm \
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-v $(pwd)/prometheus"${i}".yml:/etc/prometheus/prometheus.yml \
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-v $(pwd)/prometheus_data:/prometheus"${i}" \
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-v $(pwd)/prometheus_data/prometheus"${i}":/prometheus"${i}" \
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-u root \
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--name prometheus"${i}" \
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quay.io/prometheus/prometheus:v2.38.0 \
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--config.file=/etc/prometheus/prometheus.yml \
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--storage.tsdb.path=/prometheus \
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--storage.tsdb.path=/prometheus"${i}" \
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--web.listen-address=:909"${i}" \
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--web.external-url={{TRAFFIC_HOST1_909"${i}"}} \
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--web.enable-lifecycle \

x-playground/step2.md

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--http-address 0.0.0.0:19095
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```{{execute}}
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Visit {{TRAFFIC_HOST1_19095}}/new/loaded to see Compactor Web UI.
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Visit {{TRAFFIC_HOST1_19095}}/loaded to see Compactor Web UI.
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### Data should be immediately downsampled as well for smooth experience!
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