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@@ -67,6 +67,8 @@ For more details about the interface provided by the base class, browse the [API
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To change the collection interval of your check, use `min_collection_interval` in the configuration file. The default value is `15` which means the `check` method from your class is invoked with the same interval as the rest of the integrations on the Agent.
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**Note**: The `min_collection_interval` parameter is available for both standard and custom integrations.
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{{< tabs >}}
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{{% tab "Agent v6 & v7" %}}
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For Agent 6, `min_collection_interval` must be added at an instance level and is configured individually for each instance.
Copy file name to clipboardExpand all lines: content/en/getting_started/integrations/_index.md
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@@ -20,37 +20,37 @@ An integration, at the highest level, is when you assemble a unified system from
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Datadog provides three main types of integrations:
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-**Agent-based integrations** are installed with the Datadog Agent and use a Python class method called `check` to define the metrics to collect.
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-**Authentication (crawler) based integrations** are set up in the [Datadog App][2] where you provide credentials for obtaining metrics with the API. These include popular integrations like [Slack][3],[AWS][4],[Azure][5], and [PagerDuty][6].
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-**Library integrations** use the [Datadog API][7] to allow you to monitor applications based on the language they are written in, like [Node.js][8] or [Python][9].
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-**Agent-based** integrations are installed with the Datadog Agent and use a Python class method called `check` to define the metrics to collect.
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-**Authentication (crawler) based**integrations are set up in [Datadog][2] where you provide credentials for obtaining metrics with the API. These include popular integrations like [Slack][3],[AWS][4],[Azure][5], and [PagerDuty][6].
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-**Library** integrations use the [Datadog API][7] to allow you to monitor applications based on the language they are written in, like [Node.js][8] or [Python][9].
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You can also build a [custom check][10] to define and send metrics to Datadog from your unique in-house system.
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## Setting up an integration
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The Datadog Agent package includes integrations officially supported by Datadog, in [integrations core][11]. To use the integrations in integrations core, download the Datadog agent. Community-based integrations are in [integrations extras][12], and to use those, you need to download the [developer toolkit][13]. For more information on installing or managing these integrations, see the [integrations management guide][14].
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The Datadog Agent package includes integrations officially supported by Datadog, in [integrations core][11]. To use those integrations, download the Datadog Agent. Community-based integrations are in [integrations extras][12], and to use those, you need to download the [developer toolkit][13]. For more information on installing or managing these integrations, see the [integrations management guide][14].
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### API and Application keys
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In order to [install the Datadog Agent][15], you need an [API key][16]. If the Agent is already downloaded, make sure to set up the API key in the `datadog.yaml` file. To use most additional Datadog functionality besides submitting metrics and events, you need an [application key][16]. You can manage your accounts API and application keys in the [API Settings page][17] of the UI.
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To [install the Datadog Agent][15], you need an [API key][16]. If the Agent is already downloaded, make sure to set up the API key in the `datadog.yaml` file. To use most additional Datadog functionality besides submitting metrics and events, you need an [application key][16]. You can manage your accounts API and application keys in the [API Settings page][17].
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### Installation
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If you want to connect with a crawler or library based integration, navigate to that provider on the [Integrations page][18] for specific instructions on how to connect. For other supported integrations, install the [Datadog Agent][19]. Most integrations are supported on our containerized agents: [Docker][20], and [Kubernetes][21]. After you've downloaded the Agent, go to the [Integrations page][18] section to find specific configuration instructions for individual integrations.
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If you want to connect with a crawler or library based integration, navigate to that provider on the [Integrations page][18] for specific instructions on how to connect. For other supported integrations, install the [Datadog Agent][15]. Most integrations are supported for the containerized Agents: [Docker][19] and [Kubernetes][20]. After you've downloaded the Agent, go to the [Integrations page][18] to find specific configuration instructions for individual integrations.
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### Configuring Agent integrations
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Configurations are specific to [individual integrations][18]. In the `conf.d/<INTEGRATION_NAME>.d` folder at the root of your Agent's configuration directory, there is a folder named `<INTEGRATION_NAME>.d` for each officially supported Agent integration which contains a sample`conf.yaml.example` that lists all available configuration options for this particular integration.
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Most configuration parameters are specific to the [individual integration][18]. Configure Agent integrations by navigating to the `conf.d` folder at the root of your Agent's configuration directory. Each integration has a folder named `<INTEGRATION_NAME>.d`, which contains the file`conf.yaml.example`. This example file lists all available configuration options for the particular integration.
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To activate a given integration:
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1. Rename the `conf.yaml.example` file (in the corresponding `<INTEGRATION_NAME>.d` folder) to `conf.yaml`.
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2. Update the required parameters inside the newly created configuration file with the values corresponding to your environment.
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3.[Restart the Datadog Agent][22].
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3.[Restart the Datadog Agent][21].
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**Note**: All configuration files follow the format documented in the [parameters documentation][23].
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**Note**: All configuration files follow the format documented in the [parameters documentation][22].
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For example, this is the minimum `conf.yaml` configuration file needed to collect metrics and logs from the [apache integration][24]:
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For example, this is the minimum `conf.yaml` configuration file needed to collect metrics and logs from the [apache integration][23]:
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```yaml
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init_config:
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sourcecategory: http_web_access
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```
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To create multiple instances in the same Agent check to monitor two Apache services, create a new instance with a `-` in the `instances:` section:
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To create multiple instances in the same Agent check to monitor two Apache services, create a new instance with a `-` in the `instances` section:
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```yaml
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init_config:
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service: remote-apache
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```
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#### Collection interval
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The default collection interval for all Datadog standard integrations is 15 seconds. To change the collection interval, use the parameter `min_collection_interval`. For more details, see the [developer documentation][24].
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### Tagging
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Tagging is a key part of filtering and aggregating the data coming into Datadog across many sources. For more information about tagging, see [Getting started with tags][25].
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If you define tags in the `datadog.yaml` file, the tags are applied to all of your integrations data. Once you've defined a tag in `datadog.yaml`, all new integrations inherit it.
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For example, setting `service` in your config file is the recommended [agent setup][26] for monitoring separate, independent systems.
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For example, setting `service` in your config file is the recommended [Agent setup][26] for monitoring separate, independent systems.
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To better unify your environment, it is also recommended to configure the `env` tag in the Agent. To learn more about unified service tagging, refer to the dedicated [unified service tagging][12] documentation.
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@@ -165,16 +169,16 @@ If you continue to have problems, reach out to [our awesome Support team][37].
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