Search result for 'Redshift'

Amazon Redshift allows users to create snapshots, which are point-in-time backups of their data warehouse clusters. These snapshots can be vital for disaster recovery scenarios, testing, or data replication. When a user needs to restore a cluster from a snapshot, AWS Redshift creates a new cluster and populates it with the data from the snapshot. The new cluster will inherit the configuration ...

In AWS Redshift, when restoring a cluster from a snapshot, it's essential to track the restoration progress to ensure timely data availability and system readiness. Monitoring the progress allows users to estimate when the cluster will be operational and identify any potential issues during the restoration process. Checking the restoration progress helps in maintaining transparency and ensurin...

In AWS Redshift, snapshots are backups that capture the entire system state of a cluster at a specific point in time. Users may need to fetch or list these available snapshots for various reasons, such as monitoring, auditing, or planning a recovery operation. By fetching the list of snapshots, users can view details like snapshot creation time, source cluster, and snapshot size. Retrieving th...

In AWS Redshift, snapshots provide point-in-time backups of clusters. This runbook aims to restore Redshift clusters from a Snapshot for recovery purposes or any other purpose, users can restore these snapshots, resulting in the creation of a new cluster with data from the chosen snapshot. As the data is restored, the new cluster's status indicates the progress until it becomes 'available' for...

This task involves terminating specific Amazon Redshift clusters, effectively removing them from an AWS account. Deleting a Redshift cluster permanently erases all the data within the cluster and cannot be undone. This process might be undertaken to manage costs, decommission outdated data warehouses, or perform clean-up operations. It's crucial to ensure appropriate backups (snapshots) are in...

This task pertains to identifying Amazon Redshift clusters that exhibit consistently low CPU utilization over a predefined time span. By leveraging Amazon CloudWatch metrics, organizations can detect underutilized Redshift clusters. Recognizing such clusters provides valuable insights, allowing teams to make informed decisions about potential downscaling, resource reallocation, or other optimi...

This process retrieves a list of all Amazon Redshift clusters within an AWS account. Amazon Redshift is a fully managed data warehouse service in the cloud that allows users to run complex analytic queries against petabytes of structured data. By fetching all Redshift clusters, users can gain insights into the number of active clusters, their configurations, statuses, and other related metadat...

This runbook involves identifying Amazon Redshift clusters that have consistently low CPU utilization over a specified period and then deleting them to optimize resource usage and reduce costs. By monitoring the CPU metrics of Redshift clusters using Amazon CloudWatch, organizations can determine which clusters are underutilized and might be candidates for deletion or resizing. Deleting or res...

Pausing an AWS Redshift cluster is a cost-saving measure that allows users to temporarily halt all computational activities within the cluster while preserving its data. Once paused, you are not charged for cluster usage, though storage charges still apply. This feature is particularly useful during predictable downtime periods or when cluster analysis isn't required. Utilizing the pause funct...

Resuming an AWS Redshift cluster is the process of reactivating a previously paused cluster, bringing it back to its full operational state. This task resumes a cluster which means that computational capabilities are restored, and users can immediately execute queries, access data, and perform other database tasks. Resuming is swift, ensuring minimal downtime and enabling seamless transitions ...

In AWS Redshift, clusters can exist in various states such as 'available', 'creating', 'deleting', and 'paused'. By filtering Redshift clusters based on their state, users can quickly identify which clusters are operational, which are undergoing changes, or which are temporarily inactive. This task provides this ability to categorize and monitor clusters which facilitates efficient resource ma...