--- title: Amazon Redshift description: >- A managed, petabyte-scale data warehouse solution for cost-effectively and efficiently analyzing data. breadcrumbs: Docs > Integrations > Amazon Redshift --- # Amazon Redshift ## Overview{% #overview %} Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data. Enable this integration to see all your Redshift metrics in Datadog. ## Setup{% #setup %} ### Installation{% #installation %} If you haven't already, set up the [Amazon Web Services integration first](https://docs.datadoghq.com/integrations/amazon_web_services/). ### Metric collection{% #metric-collection %} 1. In the [AWS integration page](https://app.datadoghq.com/integrations/amazon-web-services), ensure that `Redshift` is enabled under the `Metric Collection` tab. 1. Add these permissions to your [Datadog IAM policy](https://docs.datadoghq.com/integrations/amazon_web_services/#installation) in order to collect Amazon Redshift metrics: - `redshift:DescribeClusters`: List all Redshift Clusters in your account. - `redshift:DescribeLoggingStatus`: Get S3 bucket where Redshift logs are stored. - `tag:GetResources`: Get custom tags on your Redshift clusters. For more information, see the [Redshift policies](https://docs.aws.amazon.com/redshift/latest/mgmt/redshift-iam-authentication-access-control.html) on the AWS website. 1. Install the [Datadog - Amazon Redshift integration](https://app.datadoghq.com/integrations/amazon-redshift). ### Log collection{% #log-collection %} #### Enable logging{% #enable-logging %} Enable the logging on your Redshift Cluster first to collect your logs. Redshift logs can be written to an Amazon S3 bucket and [consumed by a Lambda function](https://docs.datadoghq.com/logs/guide/send-aws-services-logs-with-the-datadog-lambda-function/#collecting-logs-from-s3-buckets). For more information, see [Configuring auditing using the console](https://docs.aws.amazon.com/redshift/latest/mgmt/db-auditing-console.html). #### Send logs to Datadog{% #send-logs-to-datadog %} 1. If you haven't already, set up the [Datadog Forwarder Lambda function](https://docs.datadoghq.com/logs/guide/forwarder/) in your AWS account. 1. Once the Lambda function is installed, there are two ways to collect your Redshift logs: - Automatically: Redshift logs are managed automatically if you grant Datadog access with a set of permissions. See [Automatically Set Up Triggers](https://docs.datadoghq.com/logs/guide/send-aws-services-logs-with-the-datadog-lambda-function/#automatically-set-up-triggers) for more information on configuring automatic log collection on the Datadog Forwarder Lambda function. - Manually: In the AWS console, add a trigger on the S3 bucket that contains your Redshift logs. See the manual installation steps. #### Manual installation steps{% #manual-installation-steps %} 1. If you haven't already, set up the [Datadog Forwarder Lambda function](https://docs.datadoghq.com/logs/guide/forwarder/) in your AWS account. 1. Once set up, go to the Datadog Forwarder Lambda function. In the Function Overview section, click **Add Trigger**. 1. Select the **S3** trigger for the Trigger Configuration. 1. Select the S3 bucket that contains your Redshift logs. 1. Leave the event type as `All object create events`. 1. Click **Add** to add the trigger to your Lambda. Go to the [Log Explorer](https://app.datadoghq.com/logs) to start exploring your logs. For more information on collecting AWS Services logs, see [Send AWS Services Logs with the Datadog Lambda Function](https://docs.datadoghq.com/logs/guide/send-aws-services-logs-with-the-datadog-lambda-function/). ## Data Collected{% #data-collected %} ### Metrics{% #metrics %} | | | | | **aws.redshift.commit\_queue\_length**(count) | The number of transactions ahead of a transaction in the commit queue.*Shown as transaction* | | **aws.redshift.concurrency\_scaling\_active\_clusters**(count) | The number of concurrency scaling clusters that are actively processing queries at any given time. | | **aws.redshift.concurrency\_scaling\_seconds**(gauge) | The number of seconds used by concurrency scaling clusters that have active query processing activity.*Shown as second* | | **aws.redshift.cpuutilization**(gauge) | The percentage of CPU utilization. For clusters, this metric represents an aggregation of all nodes (leader and compute) CPU utilization values.*Shown as percent* | | **aws.redshift.database\_connections**(gauge) | The number of database connections to a cluster.*Shown as connection* | | **aws.redshift.health\_status**(gauge) | Indicates the health of the cluster. 1 indicates healthy, and 0 indicates unhealthy. | | **aws.redshift.maintenance\_mode**(gauge) | Indicates whether the cluster is in maintenance mode. 1 indicates on, and 0 indicates off. | | **aws.redshift.max\_configured\_concurrency\_scaling\_clusters**(count) | The maximum number of concurrency scaling clusters configured from the parameter group. | | **aws.redshift.network\_receive\_throughput**(rate) | The rate at which the node or cluster receives data.*Shown as byte* | | **aws.redshift.network\_transmit\_throughput**(rate) | The rate at which the node or cluster writes data.*Shown as byte* | | **aws.redshift.num\_exceeded\_schema\_quotas**(count) | The number of schemas with exceeded quotas. | | **aws.redshift.percentage\_disk\_space\_used**(gauge) | The percent of disk space used.*Shown as percent* | | **aws.redshift.percentage\_quota\_used**(gauge) | The percentage of disk or storage space used relative to the configured schema quota.*Shown as percent* | | **aws.redshift.queries\_completed\_per\_second**(count) | The average number of queries completed per second. Reported in five-minute intervals.*Shown as query* | | **aws.redshift.query\_duration**(gauge) | The average amount of time to complete a query. Reported in five-minute intervals.*Shown as microsecond* | | **aws.redshift.query\_runtime\_breakdown**(gauge) | AWS Redshift query runtime breakdown | | **aws.redshift.read\_iops**(rate) | The average number of disk read operations per second.*Shown as operation* | | **aws.redshift.read\_latency**(gauge) | The average amount of time taken for disk read I/O operations.*Shown as second* | | **aws.redshift.read\_throughput**(rate) | The average number of bytes read from disk per second.*Shown as byte* | | **aws.redshift.schema\_quota**(gauge) | The configured quota for a schema.*Shown as byte* | | **aws.redshift.storage\_used**(gauge) | The disk or storage space used by a schema.*Shown as byte* | | **aws.redshift.total\_table\_count**(count) | The number of user tables open at a particular point in time. This total does not include Spectrum tables.*Shown as table* | | **aws.redshift.wlmqueries\_completed\_per\_second**(count) | The average number of queries completed per second for a workload management (WLM) queue. Reported in five-minute intervals.*Shown as query* | | **aws.redshift.wlmquery\_duration**(gauge) | The average length of time to complete a query for a workload management (WLM) queue. Reported in five-minute intervals.*Shown as microsecond* | | **aws.redshift.wlmqueue\_length**(count) | The number of queries waiting to enter a workload management (WLM) queue.*Shown as query* | | **aws.redshift.wlmqueue\_wait\_time**(gauge) | The total time queries spent waiting in the workload management (WLM) queue.*Shown as millisecond* | | **aws.redshift.wlmrunning\_queries**(count) | The number of queries running from both the main cluster and Concurrency Scaling cluster per WLM queue.*Shown as query* | | **aws.redshift.write\_iops**(rate) | The average number of write operations per second.*Shown as operation* | | **aws.redshift.write\_latency**(gauge) | The average amount of time taken for disk write I/O operations.*Shown as second* | | **aws.redshift.write\_throughput**(rate) | The average number of bytes written to disk per second.*Shown as byte* | Each of the metrics retrieved from AWS are assigned the same tags that appear in the AWS console, including but not limited to host name, security-groups, and more. ### Events{% #events %} The Amazon Redshift integration does not include any events. ### Service Checks{% #service-checks %} The Amazon Redshift integration does not include any service checks. ## Troubleshooting{% #troubleshooting %} Need help? Contact [Datadog support](https://docs.datadoghq.com/help/).