CASE STUDY

OpenSearch Cost Optimization with Flink

Reduced infrastructure costs by 90% and improved query performance 3x through strategic OpenSearch optimization and Apache Flink implementation.

90%
Cost Reduction
3x
Faster Queries
100TB+
Data Processed

The Challenge

A growing SaaS company was spending $50K/month on OpenSearch infrastructure to handle their log analytics and search workloads. As data volume increased, costs were spiraling while query performance degraded.

The existing architecture was inefficient, with unnecessary data duplication, oversized clusters, and suboptimal indexing strategies that led to both high costs and slow queries.

The Solution

Apache Flink Integration

Implemented Apache Flink for real-time data processing and aggregation before indexing, reducing the volume of data stored in OpenSearch by 70%.

Index Lifecycle Management

Designed automated index lifecycle policies to transition older data to cheaper storage tiers and delete obsolete data, optimizing storage costs.

Cluster Right-Sizing

Analyzed actual usage patterns and downsized clusters appropriately, using smaller instance types with better price-performance ratios.

Query Optimization

Rewrote expensive queries, implemented caching strategies, and optimized mapping configurations, dramatically improving query performance.

Results & Impact

$45K
Monthly Savings

From $50K to $5K/month

3x
Query Performance

Average query time reduced

70%
Storage Reduction

Through intelligent aggregation

100%
Uptime Maintained

Zero downtime migration

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