OpenTelemetry
Overview
OpenTelemetry is an open-source observability framework for collecting, processing, and exporting telemetry data (traces, metrics, and logs) from cloud-native applications. Within KubeDNA, OpenTelemetry provides deep visibility into the behavior and performance of distributed systems.
✅ Current Implementation
In the current release of KubeDNA, the OpenTelemetry Operator is deployed as the foundational component for enabling telemetry collection across the cluster.
Path to install:[Selected Cluster] > Components > OpenTelemetry
The deployment includes the OpenTelemetry Operator only.
Users can manually create
OpenTelemetryCollector
instances to define pipelines for collecting and exporting telemetry data.Best suited for teams that want to integrate custom exporters (e.g., Jaeger, Prometheus, or OpenSearch) manually.
Requires configuration of receivers, processors, and exporters via CRDs.
🔜 Upcoming Release – Full OpenTelemetry Stack
In the next release, KubeDNA will support a fully integrated, ready-to-use OpenTelemetry stack, offering a complete observability solution out-of-the-box.
🚀 Key Features:
Auto-instrumentation Support:
Native support for tracing libraries in Java, Python, Go, Node.js, etc.
Configurable injection for pods and services via annotations
Predefined Collectors:
Ready-to-use
OpenTelemetryCollector
pipelines for logs, traces, and metricsForwarding to OpenSearch, Jaeger, or Prometheus enabled by default
KubeDNA Metrics Integration:
Native telemetry from Kubernetes control plane, workloads, and platform components
Visual Dashboards:
Integration with OpenSearch Dashboards, Grafana, and Jaeger UI for trace exploration
Multi-tenancy & RBAC:
Role-based pipeline configuration and tenant-isolated telemetry streams
🎯 Use Cases
Distributed tracing of microservices
Monitoring performance bottlenecks
End-to-end transaction tracing
Correlating logs, metrics, and traces in a single interface
📌 Notes
Future updates will include UI-driven collector configuration and telemetry profile templates.
Integration with GitOps (via GitLab, GitHub, ArgoCD) will allow declarative pipeline updates.
Support for telemetry retention and filtering policies will also be added.