Monitor application performance with distributed tracing, latency metrics, and bottleneck detection — all within your perimeter.
Visualize the complete journey of every request across microservices, message queues, and databases. Identify exactly where time is spent in complex architectures.
Automatically generate architecture topologies showing dependencies, error rates, and latency between every service. Detect single points of failure before they impact your users.
Analyze latency distributions with p50, p95, and p99 percentiles. Compare performance across deployment versions and detect degradations before they become incidents.
Automatically group errors by type, service, and version. Correlate exceptions with the full request trace to dramatically reduce mean time to resolution (MTTR).
Identify slow queries, locks, and inefficient usage patterns in PostgreSQL, MySQL, MongoDB, and more. Correlate database performance directly with application traces.
Build tailored dashboards with RED metrics (Rate, Error, Duration), SLIs, and SLOs. Share team-specific views and configure alerts based on business thresholds.
| Instrumentation Protocol | Native OpenTelemetry (OTLP) with Jaeger and Zipkin support |
| Supported Languages | Java, Python, Go, Node.js, .NET, Ruby, PHP, and Rust |
| Trace Retention | Configurable from 7 to 90 days; long-term archival to object storage |
| Intelligent Sampling | Head-based and tail-based sampling with per-service rules and error prioritization |
| Latency Overhead | Less than 1 ms per span; under 2% impact on application throughput |
| Ingestion Capacity | Up to 500,000 spans per second per collector node; unlimited horizontal scaling |
| Signal Correlation | Automatic linking between traces, logs, and metrics via trace_id and span_id |
| Deployment | On-premise on Kubernetes (Helm chart), Docker Compose, or bare-metal installation |
Schedule a demo and discover how ByLoniS APM transforms your observability.