Some minor syntax enhancements
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1 changed files with 12 additions and 13 deletions
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@ -24,7 +24,6 @@ akka.extensions = [ "akka.cluster.metrics.ClusterMetricsExtension" ]
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## Introduction
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The member nodes of the cluster can collect system health metrics and publish that to other cluster nodes
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and to the registered subscribers on the system event bus with the help of Cluster Metrics Extension.
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@ -44,16 +43,16 @@ Certain message routing and let-it-crash functions may not work when Sigar is no
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Cluster metrics extension comes with two built-in collector implementations:
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1. `akka.cluster.metrics.SigarMetricsCollector`, which requires Sigar provisioning, and is more rich/precise
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2. `akka.cluster.metrics.JmxMetricsCollector`, which is used as fall back, and is less rich/precise
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1. `akka.cluster.metrics.SigarMetricsCollector`, which requires Sigar provisioning, and is more rich/precise
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2. `akka.cluster.metrics.JmxMetricsCollector`, which is used as fall back, and is less rich/precise
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You can also plug-in your own metrics collector implementation.
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By default, metrics extension will use collector provider fall back and will try to load them in this order:
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1. configured user-provided collector
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2. built-in `akka.cluster.metrics.SigarMetricsCollector`
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3. and finally `akka.cluster.metrics.JmxMetricsCollector`
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1. configured user-provided collector
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2. built-in `akka.cluster.metrics.SigarMetricsCollector`
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3. and finally `akka.cluster.metrics.JmxMetricsCollector`
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## Metrics Events
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@ -69,14 +68,14 @@ You can subscribe your metrics listener actors to these events in order to imple
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Scala
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: @@@ vars
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```
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```scala
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ClusterMetricsExtension(system).subscribe(metricsListenerActor)
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```
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@@@
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Java
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: @@@ vars
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```
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```java
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ClusterMetricsExtension.get(system).subscribe(metricsListenerActor);
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```
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@@@
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@ -123,11 +122,11 @@ The `AdaptiveLoadBalancingPool` / `AdaptiveLoadBalancingGroup` performs load bal
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It uses random selection of routees with probabilities derived from the remaining capacity of the corresponding node.
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It can be configured to use a specific MetricsSelector to produce the probabilities, a.k.a. weights:
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* `heap` / `HeapMetricsSelector` - Used and max JVM heap memory. Weights based on remaining heap capacity; (max - used) / max
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* `load` / `SystemLoadAverageMetricsSelector` - System load average for the past 1 minute, corresponding value can be found in `top` of Linux systems. The system is possibly nearing a bottleneck if the system load average is nearing number of cpus/cores. Weights based on remaining load capacity; 1 - (load / processors)
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* `cpu` / `CpuMetricsSelector` - CPU utilization in percentage, sum of User + Sys + Nice + Wait. Weights based on remaining cpu capacity; 1 - utilization
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* `mix` / `MixMetricsSelector` - Combines heap, cpu and load. Weights based on mean of remaining capacity of the combined selectors.
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* Any custom implementation of `akka.cluster.metrics.MetricsSelector`
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* `heap` / `HeapMetricsSelector` - Used and max JVM heap memory. Weights based on remaining heap capacity; (max - used) / max
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* `load` / `SystemLoadAverageMetricsSelector` - System load average for the past 1 minute, corresponding value can be found in `top` of Linux systems. The system is possibly nearing a bottleneck if the system load average is nearing number of cpus/cores. Weights based on remaining load capacity; 1 - (load / processors)
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* `cpu` / `CpuMetricsSelector` - CPU utilization in percentage, sum of User + Sys + Nice + Wait. Weights based on remaining cpu capacity; 1 - utilization
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* `mix` / `MixMetricsSelector` - Combines heap, cpu and load. Weights based on mean of remaining capacity of the combined selectors.
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* Any custom implementation of `akka.cluster.metrics.MetricsSelector`
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The collected metrics values are smoothed with [exponential weighted moving average](https://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average). In the @ref:[Cluster configuration](cluster-usage.md#cluster-configuration) you can adjust how quickly past data is decayed compared to new data.
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