This task can be performed using Maple
Open-source observability made simple with unified OpenTelemetry insights
Best product for this task
Maple
analytics
Maple is an OpenTelemetry-native observability stack that unifies traces, logs, and metrics with AI-assisted diagnostics. Engineering teams use it to debug microservices, investigate performance issues, and query massive telemetry datasets in milliseconds.
What to expect from an ideal product
- Maple's OpenTelemetry-native architecture processes telemetry data directly without conversion overhead, enabling sub-second query responses across petabyte-scale datasets
- The unified data model combines traces, logs, and metrics into a single queryable structure, eliminating the need to search multiple systems and reducing query execution time
- Built-in columnar storage and indexing optimizations allow complex aggregations and filters to run in milliseconds even when scanning millions of events
- AI-assisted query optimization automatically rewrites expensive queries and suggests the fastest data access patterns for your specific telemetry schema
- Distributed query execution spreads workload across multiple nodes, parallelizing data processing to handle massive datasets while maintaining lightning-fast response times
