Observability transforms raw system data into actionable insights, empowering teams to detect anomalies and optimize performance. While essential for modern infrastructure, traditional approaches often struggle with:
📉 Implementation complexity requiring code instrumentation
⏳ Resource-intensive maintenance across distributed systems
🔍 Data overload without clear troubleshooting pathways
eBPF-Powered Telemetry Collection
This talk demonstrates how extended Berkeley Packet Filter (eBPF) redefines observability by:
🌐 Capturing Container Intelligence
Real-time network call mapping (HTTP/gRPC/TCP)
Filesystem operation tracking (reads/writes/modifications)
Process execution monitoring across namespaces
📊 Unified Data Pipeline
Metrics: Kernel-level performance indicators
Logs: Context-rich event correlations
Traces: Cross-service dependency mapping
From Data to Action: Smart Troubleshooting
Discover how to:
✅ Identify latency spikes through auto-correlated traces
✅ Detect configuration drift via filesystem change timelines
✅ Pinpoint network bottlenecks using protocol-level metrics
✅ Reduce MTTR (Mean Time to Resolution) by 60-80%
🔮 Attendees will gain actionable strategies to implement lightweight, production-safe observability that scales with Kubernetes-native environments.
Perfect for DevOps engineers and SREs seeking to reduce monitoring overhead while improving system reliability.
Event link: https://seagl.org/archive/2024/zero-instrumentation-observability