Odigos
AI NativeObservability built to conquer outages
Est 2023|Raised $13.5M
Observability built to conquer outages
Published Sep 26, 2026
| Starting Price | OSS free; enterprise/tailored commercial offerings available (public list price not clear) | OSS (Beyla/OBI) free; Grafana commercial stack optional | OSS free |
| Most appropriate for | Teams wanting an automated OTel "control plane" with language detection and pipeline automation on Kubernetes | Teams seeking eBPF-based instrumentation that avoids application code changes and that integrate with Grafana ecosystem | Teams comfortable with annotations/config and language/runtime constraints |
| Key Strength | Automation: pipeline creation and scaling plus a control plane approach; integrates with OTel/OTLP destinations | Strong upstream alignment and community momentum; focused eBPF instrumentation | Standard OpenTelemetry approach; avoids some kernel-level complexity associated with eBPF |
| Key Weakness | eBPF/kernel constraints; enterprise security and compliance posture not clearly documented publicly; limited third-party review coverage | eBPF/kernel troubleshooting remains a consideration; scope focuses on instrumentation rather than pipeline orchestration | May require per-workload configuration and language-specific setup; not necessarily turnkey for all use cases |
Odigos and Beyla/OBI both emphasize eBPF and reducing the need for application code changes. Beyla/OBI’s upstream contribution into OpenTelemetry may reduce vendor lock-in concerns and strengthen community confidence over time. Odigos differentiates by presenting itself as a control plane that also automates pipeline and collector management across destinations.
Compared with the OpenTelemetry Operator, Odigos may reduce the need for workload annotations and provide more automated pipeline orchestration; however, the operator approach is widely understood and avoids some kernel-level assumptions.
Commercial APM suites (Datadog, New Relic, Splunk) often provide unified UX, broader feature sets, and enterprise support, but can be expensive at scale. Odigos’ stated approach is to enable organizations to retain their chosen backend while simplifying OTel adoption; any cost savings depend on downstream ingest and storage choices.