--- title: Amazon Redshift description: >- A managed, petabyte-scale data warehouse solution for cost-effectively and efficiently analyzing data. breadcrumbs: Docs > Integrations > Amazon Redshift --- > For the complete documentation index, see [llms.txt](https://docs.datadoghq.com/llms.txt). # Amazon Redshift Integration version1.0.0 {% callout %} # Important note for users on the following Datadog sites: us2.ddog-gov.com {% alert level="info" %} To find out if this integration is available in your organization, see your [Datadog Integrations](https://app.datadoghq.com/integrations) page or ask your organization administrator. To initiate an exception request to enable this integration for your organization, email [support@ddog-gov.com](mailto:support@ddog-gov.com). {% /alert %} {% /callout %} ## 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.md). ### 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.md#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.md#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.md) 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.md#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.md) 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.md). ## Data Collected{% #data-collected %} ### Metrics{% #metrics %} | | | | | **aws.redshift.auto_copy_error_by_cluster**(count) | The number of auto-copy job errors for the cluster.*Shown as error* | | **aws.redshift.auto_copy_error_by_job**(count) | The number of errors for an auto-copy job.*Shown as error* | | **aws.redshift.auto_copy_sqs_polling_throttled**(count) | The number of times auto-copy polling of the Amazon SQS event notification queue was throttled.*Shown as throttle* | | **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.extra_compute_for_automatic_optimization_seconds**(count) | The number of seconds of extra compute resources used to run automatic optimization tasks.*Shown as second* | | **aws.redshift.health_status**(gauge) | Indicates the health of the cluster. 1 indicates healthy, and 0 indicates unhealthy. | | **aws.redshift.integration_auto_remediation_triggered**(count) | The number of tables that auto-remediation moved to resynchronization during the reporting interval.*Shown as table* | | **aws.redshift.integration_data_transferred**(count) | The amount of data transferred by the zero-ETL integration, in logical bytes.*Shown as byte* | | **aws.redshift.integration_deleted_rows**(count) | The number of rows deleted by the zero-ETL integration.*Shown as row* | | **aws.redshift.integration_duplicate_rows_detected**(count) | The number of tables with duplicate rows identified during the reporting interval.*Shown as table* | | **aws.redshift.integration_inserted_rows**(count) | The number of rows inserted by the zero-ETL integration.*Shown as row* | | **aws.redshift.integration_lag**(gauge) | The lag from the time data is committed to the source to the time the data is available for queries in Amazon Redshift.*Shown as second* | | **aws.redshift.integration_latest_applied_change**(gauge) | The time, in Unix epoch seconds, when the zero-ETL integration last completed ingestion on Amazon Redshift.*Shown as second* | | **aws.redshift.integration_latest_detected_change**(gauge) | The time, in Unix epoch seconds, when the zero-ETL integration last staged a source change in the replication queue.*Shown as second* | | **aws.redshift.integration_latest_source_commit**(gauge) | The time, in Unix epoch seconds, of the latest source commit observed by the zero-ETL integration.*Shown as second* | | **aws.redshift.integration_num_tables_failed_replication**(gauge) | The number of tables that failed replication.*Shown as table* | | **aws.redshift.integration_num_tables_replicated**(gauge) | The number of tables that have been replicated from the source database to Amazon Redshift.*Shown as table* | | **aws.redshift.integration_state**(gauge) | The state of the zero-ETL integration. | | **aws.redshift.integration_updated_rows**(count) | The number of rows updated by the zero-ETL integration.*Shown as row* | | **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.redshift_managed_storage_billed_used_space**(gauge) | The amount of Amazon Redshift managed storage space that is billed.*Shown as megabyte* | | **aws.redshift.redshift_managed_storage_ds_used_space**(gauge) | The amount of Amazon Redshift managed storage space used by data.*Shown as megabyte* | | **aws.redshift.redshift_managed_storage_total_capacity**(gauge) | The total Amazon Redshift managed storage capacity.*Shown as megabyte* | | **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.usage_limit_available**(gauge) | The amount available under a usage limit. Measured in minutes for compute features and in terabytes for data scanning features. | | **aws.redshift.usage_limit_consumed**(gauge) | The amount consumed under a usage limit. Measured in minutes for compute features and in terabytes for data scanning features. | | **aws.redshift.user_queries_failed**(count) | The number of user queries that failed.*Shown as query* | | **aws.redshift.user_queries_succeeded**(count) | The number of user queries that succeeded.*Shown as query* | | **aws.redshift.user_query_duration**(gauge) | The average amount of time to complete a user query.*Shown as microsecond* | | **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/).