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oam/knowledge base/cloud computing/aws/opensearch.md
Michele Cereda b890a2718a chore(kb/aws): start article about managed opensearch
2024-06-12 21:43:32 +02:00

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Amazon OpenSearch Service

Amazon offering for managed OpenSearch clusters.

  1. Cost-saving measures
  2. Further readings
    1. Sources

Cost-saving measures

  • Choose good instance types and sizes.
    Leverage the ability to select them to tailor the service offering to one's needs.
  • Consider using reserved instances for long-term savings.
  • Enable index-level compression to save storage space and reduce I/O costs.
  • Use Index Lifecycle Management policies to move old data in lower storage tiers.
  • Consider using S3 as data store for infrequently accessed or archived data.
  • Consider adjusting the frequency and retention period of snapshots.
    By default, AWS OpenSearch takes daily snapshots and retains them for 14 days.
  • Enable autoscaling.
  • Optimize indexes' sharding and replication.
  • Optimize queries.
  • Optimize data ingestion.
  • Optimize indexes' mapping and settings.
  • Optimize the JVM heap size.
  • Summarize and compress historical data using Rollups.
  • Check out caches.
  • Reduce the number of requests using throttling and rate limiting.
  • Move to single-AZ deployments.
  • Leverage Spot Instances for data ingestion and processing.
  • Compress source data before sending it to OpenSearch to reduce the storage footprint and data transfer costs.
  • Share a single OpenSearch cluster with multiple accounts to reduce the overall number of instances and resources.

Further readings

Sources