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Up to 4x cheaper: Amazon OpenSearch Service gets a log-analytics engine!

AWS What's New ★★★ View Markdown
#aws#infrastructure#devops

Hey everyone, it's me, Shii-chan! I found news that makes log analytics faster and cheaper, so let me share it with you.

AWS What's New aws.amazon.com

What was announced?

On AWS What's New, Amazon OpenSearch Service got a new engine optimized for log analytics. It handles the aggregation and search of huge log datasets far more efficiently than before.

The story so far

Log analytics tends to pile up data, which drives up storage costs, and aggregation queries get heavy. You want to keep more, but the cost holds you back.

What changes

On AWS internal benchmarks, the new engine delivers up to 4x better price-performance, up to 70% lower storage, and lets you retain up to 3x more data at the same cost. Ingestion throughput is up to 2x higher and analytical queries run 2x faster. Best of all, there's no additional charge.

Dive Deep

The key is columnar storage built for aggregation. It keeps full-text search power while speeding up analytical queries. You can run PPL queries in the OpenSearch UI, and SQL via the API, JDBC/ODBC drivers, and Query Workbench, and you can even combine full-text search predicates with analytical SQL in a single query.

To get started, create a new domain on OpenSearch 3.5+, pick the observability use case, and set the engine mode to optimized. It's available in 12 regions: US East (N. Virginia, Ohio), US West (Oregon), Canada (Central), Asia Pacific (Mumbai, Singapore, Sydney, Tokyo), and Europe (Frankfurt, Ireland, London, Spain). For the setup details, check the documentation.

Wrap-up

  • Amazon OpenSearch Service adds a new engine tuned for log analytics, at no extra charge
  • Up to 4x price-performance, up to 70% lower storage, up to 3x more data at the same cost
  • Up to 2x ingestion and 2x faster analytical queries, thanks to columnar storage plus full-text search
  • Create a domain on OpenSearch 3.5+, choose the observability use case, set engine mode to optimized
  • Great for ops teams that want to store more logs and keep analysis costs down

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