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Open-Source Observability · odigos-io

odigos

Odigos is an open-source distributed tracing platform that automatically instruments applications for observability without requiring code changes. It uses eBPF technology to monitor Java, Python, .NET, Node.js, and Go applications in Kubernetes and VM environments, outputting data in OpenTelemetry format for vendor-agnostic integration.

Source: GitHub — github.com/odigos-io/odigos
3.7k
GitHub stars
254
Forks
Go
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryodigos-io/odigos
Ownerodigos-io
Primary languageGo
LicenseApache-2.0 — OSI-approved
Stars3.7k
Forks254
Open issues141
Latest releasev1.31.1 (2026-07-06)
Last updated2026-07-08
Sourcehttps://github.com/odigos-io/odigos

What odigos is

Odigos provides code-free instrumentation via eBPF-based agents that generate OTLP-formatted traces, metrics, and logs across multi-language runtimes. It includes automatic OpenTelemetry collector scaling, a web UI for configuration, and integrates with any OTLP-compatible observability backend.

Quickstart

Get the odigos source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/odigos-io/odigos.gitcd odigos# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Kubernetes Observability at Scale

Ideal for platform engineers managing multi-language microservices on Kubernetes who need production tracing without modifying application code or rebuilding container images.

Legacy Application Instrumentation

Effective for organizations with compiled or legacy applications (especially Go) where adding instrumentation SDKs is operationally expensive or risky.

Vendor-Agnostic Observability Strategy

Well-suited for teams that want to avoid lock-in by instrumenting applications once and routing traces to multiple or evolving observability platforms via OTLP.

Implementation considerations

  • Requires a functional Kubernetes cluster or VM runtime with eBPF kernel support (Linux 5.0+); eBPF availability varies by cloud provider and kernel version.
  • Installation via CLI is advertised as sub-5-minute, but production readiness assessment (collector tuning, sampling policies, data volume forecasting) requires operational planning.
  • Multi-language support is broad but coverage depth per language is unknown; verify that your specific runtime versions and frameworks are documented and tested.
  • Automatic collector scaling requires resource headroom in the cluster; monitor control plane CPU/memory to avoid cascade failures under high observability data volume.
  • OTLP output is standard, but backend-specific features (sampling strategies, trace storage, retention policies) are delegated to your downstream observability platform.

When to avoid it — and what to weigh

  • Require Pre-Built Instrumentation Plugins — If your observability stack depends on proprietary agent plugins or non-OTLP protocols, Odigos' standard OpenTelemetry output may require additional translation layers.
  • Non-Kubernetes Environments Only — Odigos is optimized for Kubernetes; while it supports VMs, the primary design and UX focus is cloud-native deployments. VM support is not clearly detailed in available documentation.
  • Very High-Frequency, Real-Time Alerting — Odigos separates data recording from processing to reduce overhead; this architecture may introduce latency unsuitable for sub-second alerting requirements.
  • Custom or Proprietary Protocol Requirements — If you require ingestion into proprietary or non-OTLP systems without OTLP translation, integration complexity is high and may require custom work.

License & commercial use

Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved license that allows commercial use, modification, and distribution with attribution and no warranty.

Apache-2.0 permits commercial use without restriction or royalty obligation. Confirm that any commercial support, SLA, or indemnification requirements are negotiated separately with the maintainers; the license itself does not include these. Review the project's support model (community vs. sponsored) to establish support expectations.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityModerate
DEV.co fitGood
Assessment confidenceHigh
Security considerations

eBPF agents run at kernel level with elevated privileges; ensure your security and compliance policies permit kernel-level instrumentation in your environment. No explicit mention of audit logging, data encryption in transit, or compliance certifications (HIPAA, PCI-DSS, SOC 2) in available data. Agent updates and patch management strategy is unknown. Requires review of security documentation and any external audit reports.

Alternatives to consider

Grafana Agent + Prometheus + Loki

Lightweight, widely adopted agent-based stack for metrics and logs; does not provide distributed tracing without additional instrumentation (Tempo) and requires more manual integration.

Datadog APM (proprietary)

Turnkey managed service with code-free instrumentation for many languages; vendor lock-in and licensing cost trade-offs; no eBPF leverage for compiled languages like Go.

Jaeger (open-source)

Mature distributed tracing backend; requires separate instrumentation layer (OpenTelemetry SDKs or agents) and does not provide automatic code-free collection like Odigos.

Software development agency

Build on odigos with DEV.co software developers

Odigos simplifies observability for Kubernetes and multi-language environments. Review the documentation, validate eBPF support in your infrastructure, and run `odigos install` to get started in minutes.

Talk to DEV.co

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odigos FAQ

Does Odigos require code changes?
No. Odigos provides code-free instrumentation via eBPF agents and OpenTelemetry auto-instrumentation, allowing instant tracing without modifying application source or rebuilding containers.
Which programming languages are supported?
Java, Python, .NET, Node.js, and Go are explicitly listed. Odigos uniquely leverages eBPF for Go, a compiled language historically difficult to instrument without code changes.
What observability backends does Odigos support?
Any OTLP-compatible backend (Jaeger, Datadog, Honeycomb, New Relic, etc.). Odigos generates data in OpenTelemetry format, avoiding vendor lock-in.
What are the kernel/platform requirements?
Optimized for Kubernetes; supports VMs. Requires eBPF capability (Linux 5.0+). Exact platform/cloud compatibility matrix is not fully detailed in the README.

Custom software development services

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If odigos is part of your open-source observability roadmap, our team can implement, customize, migrate, and maintain it.

Ready to Enable Tracing Without Code Changes?

Odigos simplifies observability for Kubernetes and multi-language environments. Review the documentation, validate eBPF support in your infrastructure, and run `odigos install` to get started in minutes.