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69 lines
3.6 KiB
Markdown
69 lines
3.6 KiB
Markdown
---
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slug: /en/operations/monitoring
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sidebar_position: 45
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sidebar_label: Monitoring
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description: You can monitor the utilization of hardware resources and also ClickHouse server metrics.
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keywords: [monitoring, observability, advanced dashboard, dashboard, observability dashboard]
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---
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# Monitoring
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import SelfManaged from '@site/docs/en/_snippets/_self_managed_only_automated.md';
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<SelfManaged />
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You can monitor:
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- Utilization of hardware resources.
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- ClickHouse server metrics.
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## Built-in advanced observability dashboard
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<img width="400" alt="Screenshot 2023-11-12 at 6 08 58 PM" src="https://github.com/ClickHouse/ClickHouse/assets/3936029/2bd10011-4a47-4b94-b836-d44557c7fdc1" />
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ClickHouse comes with a built-in advanced observability dashboard feature which can be accessed by `$HOST:$PORT/dashboard` (requires user and password) that shows the following metrics:
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- Queries/second
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- CPU usage (cores)
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- Queries running
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- Merges running
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- Selected bytes/second
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- IO wait
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- CPU wait
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- OS CPU Usage (userspace)
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- OS CPU Usage (kernel)
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- Read from disk
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- Read from filesystem
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- Memory (tracked)
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- Inserted rows/second
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- Total MergeTree parts
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- Max parts for partition
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## Resource Utilization {#resource-utilization}
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ClickHouse also monitors the state of hardware resources by itself such as:
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- Load and temperature on processors.
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- Utilization of storage system, RAM and network.
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This data is collected in the `system.asynchronous_metric_log` table.
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## ClickHouse Server Metrics {#clickhouse-server-metrics}
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ClickHouse server has embedded instruments for self-state monitoring.
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To track server events use server logs. See the [logger](../operations/server-configuration-parameters/settings.md#server_configuration_parameters-logger) section of the configuration file.
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ClickHouse collects:
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- Different metrics of how the server uses computational resources.
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- Common statistics on query processing.
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You can find metrics in the [system.metrics](../operations/system-tables/metrics.md#system_tables-metrics), [system.events](../operations/system-tables/events.md#system_tables-events), and [system.asynchronous_metrics](../operations/system-tables/asynchronous_metrics.md#system_tables-asynchronous_metrics) tables.
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You can configure ClickHouse to export metrics to [Graphite](https://github.com/graphite-project). See the [Graphite section](../operations/server-configuration-parameters/settings.md#server_configuration_parameters-graphite) in the ClickHouse server configuration file. Before configuring export of metrics, you should set up Graphite by following their official [guide](https://graphite.readthedocs.io/en/latest/install.html).
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You can configure ClickHouse to export metrics to [Prometheus](https://prometheus.io). See the [Prometheus section](../operations/server-configuration-parameters/settings.md#server_configuration_parameters-prometheus) in the ClickHouse server configuration file. Before configuring export of metrics, you should set up Prometheus by following their official [guide](https://prometheus.io/docs/prometheus/latest/installation/).
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Additionally, you can monitor server availability through the HTTP API. Send the `HTTP GET` request to `/ping`. If the server is available, it responds with `200 OK`.
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To monitor servers in a cluster configuration, you should set the [max_replica_delay_for_distributed_queries](../operations/settings/settings.md#max_replica_delay_for_distributed_queries) parameter and use the HTTP resource `/replicas_status`. A request to `/replicas_status` returns `200 OK` if the replica is available and is not delayed behind the other replicas. If a replica is delayed, it returns `503 HTTP_SERVICE_UNAVAILABLE` with information about the gap.
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