Why do you need big data APM?
Modern enterprise applications produce a volume, velocity and variety of transaction data at a scale that presents a big data challenge for application performance monitoring (APM). In order to scale in these environments, most APM vendors have opted for stopgap measures, such as sampling or snapshotting transactions on a subset of tiers. This results in a patchy, incomplete data set that can lead to inaccurate analysis and leave many performance issues unresolved.
Big data technology applied to APM directly addresses enterprise monitoring requirements by delivering deep diagnostics at unparalleled scale. It captures, stores and indexes across billions of transactions a day without sacrificing data completeness, granularity or depth. With big data APM, you always have all the evidence you need to reconstruct incidents in great detail for immediate insight into even infrequent or intermittent issues, and quickly resolve problems before end users are impacted.
How does big data APM maintain the highest levels of data quality at any scale?
Big data technology for APM enables:
- End-to-end distributed transaction tracing across all tiers at any scale
- Auto-tuning of instrumentation overhead for deep call stack visibility
- Clustered architecture for analyzing tens of thousands of application components
- Efficient data transfer and storage
- 1-second metrics
- All metadata detail
