---
title: Send alerts using data in InfluxDB
description: Query, analyze, and send alerts using time series data stored in InfluxDB.
url: https://docs.influxdata.com/influxdb3/cloud-dedicated/process-data/send-alerts/
estimated_tokens: 7684
product: InfluxDB Cloud Dedicated
version: cloud-dedicated
---

# Send alerts using data in InfluxDB

Query, analyze, and send alerts using time series data stored in InfluxDB.

This guide uses [Python](https://www.python.org/), the [InfluxDB 3 Python client library](https://github.com/InfluxCommunity/influxdb3-python), and the [Python Slack SDK](https://slack.dev/python-slack-sdk/) to demonstrate how to query data from InfluxDB and send alerts to Slack, but you can use your runtime and alerting platform of choice with any of the available [InfluxDB 3 client libraries](/influxdb3/cloud-dedicated/reference/client-libraries/v3/). Whatever clients and platforms you choose the use, the process is the same:

#### Alerting process

1. Use an external runtime and InfluxDB client to query data from InfluxDB.
2. Use the queried data and tools available in your runtime to send alerts.

-   [Create a Slack app](#create-a-slack-app)
-   [Install dependencies](#install-dependencies)
-   [Create an InfluxDB client](#create-an-influxdb-client)
-   [Create a Slack client](#create-a-slack-client)
-   [Query InfluxDB](#query-influxdb)
    -   [Execute the query](#execute-the-query)
-   [Send alerts](#send-alerts)
-   [Full alerting script](#full-alerting-script)

## Create a Slack app

To send alerts to Slack, first create a Slack app and gather the required connection credentials to interact with your app. More information is provided in the [Slack basic app setup documentation](https://api.slack.com/authentication/basics).

## Install dependencies

This guide assumes you have already [setup your Python project and virtual environment](/influxdb3/cloud-dedicated/query-data/execute-queries/client-libraries/python/#create-a-python-virtual-environment).

Use `pip` to install the following dependencies:

-   `influxdb_client_3`
-   `pandas`
-   `slack_sdk`

```sh
pip install influxdb3-python pandas slack_sdk
```

## Create an InfluxDB client

Use the `InfluxDBClient3` function in the `influxdb_client_3` module to instantiate an InfluxDB client. Provide the following credentials:

-   **host**: InfluxDB Cloud Dedicated cluster URL *(without the protocol)*
-   **org**: InfluxDB organization name
-   **token**: [InfluxDB database token](/influxdb3/cloud-dedicated/admin/tokens/#database-tokens) read permissions on the database you want to query
-   **database**: InfluxDB database name

```py
from influxdb_client_3 import InfluxDBClient3
import pandas

# Instantiate an InfluxDBClient3 client configured for your database
influxdb = InfluxDBClient3(
    host='cluster-id.a.influxdb.io',
    token='DATABASE_TOKEN',
    database='DATABASE_NAME'
)
```

## Create a Slack client

1. Import the `WebClient` function from the `slack.sdk` module and the `SlackApiError` function from the `slack_sdk.errors` module.
    
2. Use the `WebClient` function to instantiate a Slack client. Provide the following credentials:
    
    -   **token**: [Slack bot token](https://api.slack.com/authentication/basics#getting-your-authentication-token)

```py
from slack_sdk import WebClient
from slack_sdk.errors import SlackApiError

slack = WebClient(token='SLACK_BOT_TOKEN')
```

## Query InfluxDB

Define either a SQL or InfluxQL query to retrieve data to alert on. Depending on what data you want to alert on, you can:

-   Include logic in the query so it only returns results that should be alerted on.
-   Query data necessary for further processing and then send alerts based on processing performed in your runtime.

The example query below only returns values above a threshold that should trigger alerts.

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**SQL:**

```sql
SELECT
  selector_last(co, time)['time'] AS time,
  selector_last(co, time)['value'] AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
```

**InfluxQL:**

```sql
SELECT
  LAST(co) AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
```

<!-- End tabbed content -->

### Execute the query

1. Assign the query string to a variable.
    
2. Use the `query` method of your [instantiated client](#create-an-influxdb-client) to query raw data from InfluxDB. Provide the following arguments.
    
    -   **query**: Query string to execute
    -   **language**: `sql` or `influxql`
3. Use the `to_pandas` method to convert the returned Arrow table to a Pandas DataFrame.
    

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**SQL:**

```py
# ...

query = '''
SELECT
  selector_last(co, time)['time'] AS time,
  selector_last(co, time)['value'] AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
'''

table = influxdb_raw.query(query=query, language="sql")
data_frame = table.to_pandas()
```

**InfluxQL:**

```py
# ...

query = '''
SELECT
  LAST(co) AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
'''

table = influxdb_raw.query(query=query, language="influxql")
data_frame = table.to_pandas()
```

<!-- End tabbed content -->

## Send alerts

Iterate through the DataFrame and send an alert to Slack for each row.

1. Use the `reset_index` function on the data frame to ensure indexes align with the number of rows in the DataFrame.
    
2. Iterate through each row and use the `chat_postMessage` method of your [Slack client](#create-a-slack-client) to send a message (per row) to Slack. Provide the following arguments:
    
    -   **channel**: Slack channel to send the alert to.
    -   **text**: Message text to send. Use string interpolation to insert column values from each row into the message text.

```py
# ...

data_frame = data_frame.reset_index()

for index, row in data_frame.iterrows():
    slack.chat_postMessage(
        channel="#SLACK_CHANNEL",
        text=f'Carbon monoxide (co) high in {row.room}: {row.co} ppm at {row.time}'
    )
```

## Full alerting script

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**SQL:**

```py
from influxdb_client_3 import InfluxDBClient3
import pandas
from slack_sdk import WebClient
from slack_sdk.errors import SlackApiError

influxdb = InfluxDBClient3(
    host='cluster-id.a.influxdb.io',
    token='DATABASE_TOKEN',
    database='DATABASE_NAME'
)

slack = WebClient(token='SLACK_BOT_TOKEN')

query = '''
SELECT
  selector_last(co, time)['time'] AS time,
  selector_last(co, time)['value'] AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
'''

table = influxdb_raw.query(query=query, language="sql")
data_frame = table.to_pandas()
data_frame = data_frame.reset_index()

for index, row in data_frame.iterrows():
    slack.chat_postMessage(
        channel="#SLACK_CHANNEL",
        text=f'Carbon monoxide (co) high in {row.room}: {row.co} ppm at {row.time}'
    )
```

**InfluxQL:**

```py
from influxdb_client_3 import InfluxDBClient3
import pandas
from slack_sdk import WebClient
from slack_sdk.errors import SlackApiError

influxdb = InfluxDBClient3(
    host='cluster-id.a.influxdb.io',
    token='DATABASE_TOKEN',
    database='DATABASE_NAME'
)

slack = WebClient(token='SLACK_BOT_TOKEN')

query = '''
SELECT
  LAST(co) AS co,
  room
FROM home
WHERE co > 10
GROUP BY room
'''

table = influxdb_raw.query(query=query, language="influxql")
data_frame = table.to_pandas()
data_frame = data_frame.reset_index()

for index, row in data_frame.iterrows():
    slack.chat_postMessage(
        channel="#SLACK_CHANNEL",
        text=f'Carbon monoxide (co) high in {row.room}: {row.co} ppm at {row.time}'
    )
```

<!-- End tabbed content -->