Technical Components
SignalSDK — Observability & Telemetry Framework
SignalSDK
Organizations building production systems face observability challenges: **Incomplete Instrumentation**: Adding metrics, traces, and logs throughout application code is tedious work that gets deprioritized during development. By the time you reach production, critical code paths lack instrumentation. When incidents occur, you don't have the data to understand what's happening. Adding instrumentation during an outage is impossible—you needed it before the problem started. **Excessive Performance Overhead**: Detailed tracing and logging can consume 5-20% of application CPU and generate massive data volumes. To avoid performance impact, teams reduce sampling rates or disable instrumentation entirely—losing visibility precisely when load is highest and problems most likely. You're forced to choose between performance and observability. **Data Without Context**: Collecting millions of metrics doesn't help if you can't find the relevant ones during incidents. Without structured attributes, queries require knowing exact metric names in advance. Distributed traces span dozens of services but lack the business context linking them to customer impact. You're drowning in data while lacking actionable insights.
Who This Is For
**SRE Teams** responsible for production reliability where current monitoring provides insufficient visibility into distributed system behavior during incidents. **Platform Engineers** building shared infrastructure where enabling observability across all services requires standardized, low-friction instrumentation. **Development Leads** managing microservices architectures where understanding cross-service behavior and performance is essential but current tooling makes instrumentation too difficult. This is for organizations with distributed systems (5+ services) where debugging production issues takes hours because telemetry is incomplete or difficult to query. If you're adding print statements during incidents, can't trace requests across services, or instrumentation work keeps getting postponed, standardized observability framework becomes essential.
What You Get
SignalSDK delivers comprehensive observability with <1% performance overhead through efficient instrumentation patterns and intelligent sampling. You get automatic metric collection, distributed tracing across all service boundaries, and structured logging—all with minimal code changes to existing applications. Your SRE and development teams gain the visibility needed to diagnose production issues quickly, understand performance characteristics, and validate that changes have intended effects. Incidents that previously took hours to debug now resolve in minutes with clear telemetry data.
How We Work
Key Deliverables
1
Multi-Language Instrumentation SDK
Lightweight libraries for all major languages:
2
Automatic Metric Collection
Zero-configuration metrics for common patterns:
3
Distributed Tracing
End-to-end request flow visibility:
4
Structured Logging Integration
Contextual logging with trace correlation:
5
Business Context Attribution
Enriching telemetry with business meaning:
6
Observability Backend Integration
Flexible export to multiple backends:
7
Performance Impact Analysis
Quantifying observability overhead:
8
Exemplar Dashboards & Alerts
Pre-built monitoring configurations:
9
Best Practices & Patterns
Guidance for effective instrumentation:
10
Training & Support
Ensuring teams use observability effectively: