194 lines
7.5 KiB
Markdown
194 lines
7.5 KiB
Markdown
---
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title: Monitor states
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seotitle: Monitor states and state changes in your events and metrics with Flux.
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description: Flux provides several functions to help monitor states and state changes in your data.
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v2.0/tags: [states, monitor, flux]
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menu:
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v2_0:
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name: Monitor states
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parent: How-to guides
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weight: 209
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---
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Flux helps you monitor states in your metrics and events:
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- [Find how long a state persists](#find-how-long-a-state-persists)
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- [Count the number of consecutive states](#count-the-number-of-consecutive-states)
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- [Detect state changes](#detect-state-changes)
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If you're just getting started with Flux queries, check out the following:
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- [Get started with Flux](/v2.0/query-data/get-started/) for a conceptual overview of Flux.
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- [Execute queries](/v2.0/query-data/execute-queries/) to discover a variety of ways to run your queries.
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## Find how long a state persists
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1. Use the [`stateDuration()`](/v2.0/reference/flux/stdlib/built-in/transformations/stateduration/) function to calculate how long a column value has remained the same value (or state). Include the following information:
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- **Column to search:** any tag key, tag value, field key, field value, or measurement.
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- **Value:** the value (or state) to search for in the specified column.
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- **State duration column:** a new column to store the state duration─the length of time that the specified value persists.
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- **Unit:** the unit of time (`1s` (by default), `1m`, `1h`) used to increment the state duration.
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```js
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|> stateDuration(
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fn: (r) =>
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r._column_to_search == "value_to_search_for",
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column: "state_duration",
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unit: 1s)
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```
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2. Use `stateDuration()` to search each point for the specified value:
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- For the first point that evaluates `true`, the state duration is set to `0`. For each consecutive point that evaluates `true`, the state duration increases by the time interval between each consecutive point (in specified units).
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- If the state is `false`, the state duration is reset to `-1`.
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### Example query with stateDuration()
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The following query searches the `doors` bucket over the past 5 minutes to find how many seconds a door has been `closed`.
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```js
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from(bucket: "doors")
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|> range(start: -5m)
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|> stateDuration(
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fn: (r) =>
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r._value == "closed",
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column: "door_closed",
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unit: 1s)
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```
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In this example, `door_closed` is the **State duration** column. If you write data to the `doors` bucket every minute, the state duration increases by `60s` for each consecutive point where `_value` is `closed`. If `_value` is not `closed`, the state duration is reset to `0`.
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#### Query results
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Results for the example query above may look like this (for simplicity, we've omitted the measurement, tag, and field columns):
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```bash
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_time _value door_closed
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2019-10-26T17:39:16Z closed 0
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2019-10-26T17:40:16Z closed 60
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2019-10-26T17:41:16Z closed 120
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2019-10-26T17:42:16Z open -1
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2019-10-26T17:43:16Z closed 0
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2019-10-26T17:44:27Z closed 60
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```
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## Count the number of consecutive states
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1. Use the `stateCount()` function and include the following information:
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- **Column to search:** any tag key, tag value, field key, field value, or measurement.
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- **Value:** to search for in the specified column.
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- **State count column:** a new column to store the state count─the number of consecutive records in which the specified value exists.
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```js
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|> stateCount
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(fn: (r) =>
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r._column_to_search == "value_to_search_for",
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column: "state_count"`
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)
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```
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2. Use `stateCount()` to search each point for the specified value:
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- For the first point that evaluates `true`, the state count is set to `1`. For each consecutive point that evaluates `true`, the state count increases by 1.
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- If the state is `false`, the state count is reset to `-1`.
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### Example query with stateCount()
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The following query searches the `doors` bucket over the past 5 minutes and calculates how many points have `closed` as their `_value`.
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```js
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from(bucket: "doors")
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|> range(start: -5m)
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|> stateDuration(
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fn: (r) =>
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r._value == "closed",
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column: "door_closed")
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```
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This example stores the **state count** in the `door_closed` column. If you write data to the `doors` bucket every minute, the state count increases by `1` for each consecutive point where `_value` is `closed`. If `_value` is not `closed`, the state count is reset to `-1`.
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#### Query results
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Results for the example query above may look like this (for simplicity, we've omitted the measurement, tag, and field columns):
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```bash
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_time _value door_closed
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2019-10-26T17:39:16Z closed 1
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2019-10-26T17:40:16Z closed 2
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2019-10-26T17:41:16Z closed 3
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2019-10-26T17:42:16Z open -1
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2019-10-26T17:43:16Z closed 1
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2019-10-26T17:44:27Z closed 2
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```
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#### Example query to count machine state
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The following query checks the machine state every minute (idle, assigned, or busy). InfluxDB searches the `servers` bucket over the past hour and counts records with a machine state of `idle`, `assigned` or `busy`.
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```
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from(bucket: "servers")
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|> range(start: -1h)
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|> filter(fn: (r) =>
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r.machine_state == "idle" or
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r.machine_state == "assigned" or
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r.machine_state == "busy"
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)
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|> stateCount(fn: (r) => r.machine_state == "busy", column: "_count")
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|> stateCount(fn: (r) => r.machine_state == "assigned", column: "_count")
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|> stateCount(fn: (r) => r.machine_state == "idle", column: "_count")
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```
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<!--## Detect state changes
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Detect state changes with the `monitor.stateChanges()` function. To use the `monitor.stateChanges()` function, set up a **check** to query data (stored in the `_monitoring` bucket > `statuses` measurement > `_level` column; see [Monitor data and send alerts](/v2.0/monitor-alert/) for more detail.
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1. In the InfluxDB user interface, click the **Monitoring and Alerting** icon from the sidebar.
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{{< nav-icon "alerts" >}}
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2. If you haven't already, [create a check](/v2.0/monitor-alert/checks/create/) that stores statuses (`CRIT`, `WARN`, `INFO`, `OK` or `ANY`) in the `_level` column. <!-- specify how to do this with monitor.check() function or in UI, with check threshold or deadman?
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3. Import the InfluxDB `monitor` package.
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4. In your query, the specify the check. <!--can users specify a Flux query with the `monitoring` bucket and _level field without specifying the check? does importing the monitor package create the `monitoring` bucket?
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5. Use the `monitor.stateChanges()` function and include the following information:
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- `fromLevel` (optional; by default, this is set to `any`)
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- `toLevel`
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### Example query with monitor.stateChanges()
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```js
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import "influxdata/influxdb/monitor"
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`from ${ r._check_name}`
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monitor.stateChanges(
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fromLevel: "warn",
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toLevel: "crit")
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```
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<!-- ### Example query results
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TBD what query results look like -->
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<!--traffic lights
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```from(bucket: "doors")
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|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
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|> filter(fn: (r) => r._measurement == "doors")
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|> stateCount(fn: (r) => r._field == "door1", column: "_value")
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```
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|> stateDuration(fn: (r) => r._cpu == "usage_idle <= 10s", column "stateDuration", unit: 1s)
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]]
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|alert()
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// Warn after 1 minute
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.warn(lambda: "state_duration" >= 1)
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// Critical after 5 minutes
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.crit(lambda: "state_duration" >= 5)
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```
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-->
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