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 metrics

  • Forwarding 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.