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.
If you haven’t already, set up the Amazon Web Services integration first.
In the AWS integration tile, ensure that Redshift is checked under metric collection.
Add these permissions to your Datadog IAM policy 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 on the AWS website.
Install the Datadog - AWS Redshift integration.
Enable the logging on your Redshift Cluster first to collect your logs. Redshift logs can be written to an AWS S3 bucket and consumed by a Lambda function. For more information, see Configuring auditing using the console.
If you haven’t already, set up the Datadog log collection AWS Lambda function.
Once the lambda function is installed, there are two ways to collect your Redshift logs:
Object Created (All) then click on the add button.Once done, go in your Datadog Log section to start exploring your logs!
| 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.
The AWS Redshift integration does not include any events.
The AWS Redshift integration does not include any service checks.
Need help? Contact Datadog support.
