156 lines
8.4 KiB
Plaintext
156 lines
8.4 KiB
Plaintext
[role="xpack"]
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[testenv="basic"]
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[[es-monitoring-collectors]]
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== Collectors
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[IMPORTANT]
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=========================
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{metricbeat} is the recommended method for collecting and shipping monitoring
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data to a monitoring cluster.
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If you have previously configured legacy collection methods, you should migrate
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to using {metricbeat} collection methods. Use either {metricbeat} collection or
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legacy collection methods; do not use both.
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Learn more about <<configuring-metricbeat>>.
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=========================
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Collectors, as their name implies, collect things. Each collector runs once for
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each collection interval to obtain data from the public APIs in {es} and {xpack}
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that it chooses to monitor. When the data collection is finished, the data is
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handed in bulk to the <<es-monitoring-exporters,exporters>> to be sent to the
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monitoring clusters. Regardless of the number of exporters, each collector only
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runs once per collection interval.
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There is only one collector per data type gathered. In other words, for any
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monitoring document that is created, it comes from a single collector rather
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than being merged from multiple collectors. The {es} {monitor-features}
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currently have a few collectors because the goal is to minimize overlap between
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them for optimal performance.
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Each collector can create zero or more monitoring documents. For example,
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the `index_stats` collector collects all index statistics at the same time to
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avoid many unnecessary calls.
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[options="header"]
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|=======================
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| Collector | Data Types | Description
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| Cluster Stats | `cluster_stats`
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| Gathers details about the cluster state, including parts of the actual cluster
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state (for example `GET /_cluster/state`) and statistics about it (for example,
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`GET /_cluster/stats`). This produces a single document type. In versions prior
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to X-Pack 5.5, this was actually three separate collectors that resulted in
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three separate types: `cluster_stats`, `cluster_state`, and `cluster_info`. In
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5.5 and later, all three are combined into `cluster_stats`. This only runs on
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the _elected_ master node and the data collected (`cluster_stats`) largely
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controls the UI. When this data is not present, it indicates either a
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misconfiguration on the elected master node, timeouts related to the collection
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of the data, or issues with storing the data. Only a single document is produced
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per collection.
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| Index Stats | `indices_stats`, `index_stats`
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| Gathers details about the indices in the cluster, both in summary and
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individually. This creates many documents that represent parts of the index
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statistics output (for example, `GET /_stats`). This information only needs to
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be collected once, so it is collected on the _elected_ master node. The most
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common failure for this collector relates to an extreme number of indices -- and
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therefore time to gather them -- resulting in timeouts. One summary
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`indices_stats` document is produced per collection and one `index_stats`
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document is produced per index, per collection.
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| Index Recovery | `index_recovery`
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| Gathers details about index recovery in the cluster. Index recovery represents
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the assignment of _shards_ at the cluster level. If an index is not recovered,
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it is not usable. This also corresponds to shard restoration via snapshots. This
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information only needs to be collected once, so it is collected on the _elected_
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master node. The most common failure for this collector relates to an extreme
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number of shards -- and therefore time to gather them -- resulting in timeouts.
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This creates a single document that contains all recoveries by default, which
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can be quite large, but it gives the most accurate picture of recovery in the
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production cluster.
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| Shards | `shards`
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| Gathers details about all _allocated_ shards for all indices, particularly
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including what node the shard is allocated to. This information only needs to be
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collected once, so it is collected on the _elected_ master node. The collector
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uses the local cluster state to get the routing table without any network
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timeout issues unlike most other collectors. Each shard is represented by a
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separate monitoring document.
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| Jobs | `job_stats`
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| Gathers details about all machine learning job statistics (for example, `GET
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/_ml/anomaly_detectors/_stats`). This information only needs to be collected
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once, so it is collected on the _elected_ master node. However, for the master
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node to be able to perform the collection, the master node must have
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`xpack.ml.enabled` set to true (default) and a license level that supports {ml}.
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| Node Stats | `node_stats`
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| Gathers details about the running node, such as memory utilization and CPU
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usage (for example, `GET /_nodes/_local/stats`). This runs on _every_ node with
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{monitor-features} enabled. One common failure results in the timeout of the node
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stats request due to too many segment files. As a result, the collector spends
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too much time waiting for the file system stats to be calculated until it
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finally times out. A single `node_stats` document is created per collection.
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This is collected per node to help to discover issues with nodes communicating
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with each other, but not with the monitoring cluster (for example, intermittent
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network issues or memory pressure).
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|=======================
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The {es} {monitor-features} use a single threaded scheduler to run the
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collection of {es} monitoring data by all of the appropriate collectors on each
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node. This scheduler is managed locally by each node and its interval is
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controlled by specifying the `xpack.monitoring.collection.interval`, which
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defaults to 10 seconds (`10s`), at either the node or cluster level.
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Fundamentally, each collector works on the same principle. Per collection
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interval, each collector is checked to see whether it should run and then the
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appropriate collectors run. The failure of an individual collector does not
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impact any other collector.
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Once collection has completed, all of the monitoring data is passed to the
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exporters to route the monitoring data to the monitoring clusters.
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If gaps exist in the monitoring charts in {kib}, it is typically because either
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a collector failed or the monitoring cluster did not receive the data (for
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example, it was being restarted). In the event that a collector fails, a logged
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error should exist on the node that attempted to perform the collection.
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NOTE: Collection is currently done serially, rather than in parallel, to avoid
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extra overhead on the elected master node. The downside to this approach
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is that collectors might observe a different version of the cluster state
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within the same collection period. In practice, this does not make a
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significant difference and running the collectors in parallel would not
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prevent such a possibility.
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For more information about the configuration options for the collectors, see
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<<monitoring-collection-settings>>.
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[discrete]
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[[es-monitoring-stack]]
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==== Collecting data from across the Elastic Stack
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{es} {monitor-features} also receive monitoring data from other parts of the
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Elastic Stack. In this way, it serves as an unscheduled monitoring data
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collector for the stack.
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By default, data collection is disabled. {es} monitoring data is not
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collected and all monitoring data from other sources such as {kib}, Beats, and
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Logstash is ignored. You must set `xpack.monitoring.collection.enabled` to `true`
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to enable the collection of monitoring data. See <<monitoring-settings>>.
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Once data is received, it is forwarded to the exporters
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to be routed to the monitoring cluster like all monitoring data.
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WARNING: Because this stack-level "collector" lives outside of the collection
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interval of {es} {monitor-features}, it is not impacted by the
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`xpack.monitoring.collection.interval` setting. Therefore, data is passed to the
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exporters whenever it is received. This behavior can result in indices for {kib},
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Logstash, or Beats being created somewhat unexpectedly.
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While the monitoring data is collected and processed, some production cluster
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metadata is added to incoming documents. This metadata enables {kib} to link the
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monitoring data to the appropriate cluster. If this linkage is unimportant to
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the infrastructure that you're monitoring, it might be simpler to configure
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Logstash and Beats to report monitoring data directly to the monitoring cluster.
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This scenario also prevents the production cluster from adding extra overhead
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related to monitoring data, which can be very useful when there are a large
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number of Logstash nodes or Beats.
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For more information about typical monitoring architectures, see
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<<how-monitoring-works>>.
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