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Redshift Cluster

In the context of big data analytics, Redshift clusters in Amazon Web Services are a critical resource, often utilized by data engineers for complex data processing and analysis tasks.

Implementation Effort: Medium - Estimated time: 2-4 hours. Verify no active queries or BI tool dependencies, take a snapshot, then pause or delete the cluster.

However, these clusters can become a significant source of waste, especially when they are underutilized. Due to the high cost associated with Redshift — particularly for multi-node clusters — it's essential to monitor their actual usage carefully.

We identify idle Redshift clusters through a detection algorithm that analyzes multiple CloudWatch metrics over an extended observation period, including:

  • Database connections — whether any clients are actively connecting to the cluster
  • CPU utilization — sustained compute activity levels across cluster nodes
  • Disk I/O — read and write operations indicating active query processing and data changes

Only clusters where all signals consistently indicate inactivity are flagged as unused, ensuring high-confidence results without false positives.

By surfacing truly idle clusters, data engineers and FinOps teams can make informed decisions to pause, downsize, or decommission Redshift resources that are not contributing to active workloads — turning a costly oversight into meaningful savings.