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move common topics to resources base
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## docker metrics
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### summary
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Enlist nosqlbench to stand up your metrics infrastructure using a local docker runtime:
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--docker-metrics
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When this option is set, nosqlbench will start graphite, prometheus, and grafana automatically
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on your local docker, configure them to work together, and point nosqlbench to send metrics
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the system automatically. It also imports a base dashboard for nosqlbench and configures grafana
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snapshot export to share with a central DataStax grafana instance (grafana can be found on localhost:3000
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with the default credentials admin/admin).
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### details
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If you want to know exactly what nosqlbench is doing, it's the equivalent of running the following by hand:
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#### pull and run the graphite-exporter container
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docker run -d -p 9108:9108 -p 9109:9109 -p 9109:9109/udp prom/graphite-exporter
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#### prometheus config
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place prometheus config in .prometheus:
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prometheus.yml (found in resources/docker/prometheus/prometheus.yml)
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#### pull and run the prometheus container
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docker run -d -p 9090:9090 -v '<USER HOME>/.prometheus:/etc/prometheus' prom/prometheus --config.file=/etc/prometheus/prometheus.yml" --storage.tsdb.path=/prometheus" --storage.tsdb.retention=183d --web.enable-lifecycle
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#### pull and run the grafana container
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docker run -d -p 3000:3000 -v grafana/grafana
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with the following environment variables:
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GF_SECURITY_ADMIN_PASSWORD=admin
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GF_AUTH_ANONYMOUS_ENABLED="true"
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GF_SNAPSHOTS_EXTERNAL_SNAPSHOT_URL=http://54.165.144.56:3001
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GF_SNAPSHOTS_EXTERNAL_SNAPSHOT_NAME="Send to Wei"
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#### configure grafana
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use the grafana api to set up the datasource and dashboard
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POST
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http://localhost:3000/api/dashboards/db
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Payload:
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analysis.json (found in resources/docker/dashboards/analysis.json)
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POST
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http://localhost:3000/api/datasources
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Payload:
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prometheus-datasource.yaml (found in resources/docker/datasources/prometheus-datasource.yaml)
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@@ -1,21 +0,0 @@
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# Setting threads
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Threads may be set in a few different ways depending on the type of
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testing you are doing.
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Sometimes, you need the client runtime to emulate a threading model of
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an application. Other times you may want the client to go as fast as it
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can regardless of the threading model. The difference between these
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varies significantly depending on whether you are using asynchronous
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messaging or not.
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Some valid forms for setting threads include:
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- threads=auto
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- Sets the thread count to 10x the number of CPUs
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- This does not consider hyper-threading
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- threads=2x
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- Sets the thread count to 2x the number of CPUs
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- This does not consider hyper-threading
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- threads=10
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- Simply sets the thread count to 10
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