
Aviad contributed to the Odigos project by enhancing observability and build processes across the AvihuHenya/odigos and BenElferink/odigos repositories. He developed a Go Redis instrumentation feature that adds a sub_category attribute, improving data granularity for Redis operations and enabling more precise troubleshooting. Aviad also optimized the odiglet base image using Docker multi-stage builds to include rsync, reducing build times and supporting extensibility. Additionally, he expanded support for custom eBPF-based instrumentation probes in both Java and Go, updating CRDs and documentation to streamline developer adoption. His work demonstrated depth in Go, Docker, Kubernetes, and system-level automation.

Month: 2025-10 — Focused on strengthening Odigos build reliability and extensibility by integrating rsync into base images and expanding instrumentation capabilities. Delivered targeted changes across two repositories (AvihuHenya/odigos and BenElferink/odigos) to optimize images, simplify builds, and enable custom eBPF-based instrumentation. These efforts reduce image sizes and build times, streamline customization, and lay groundwork for broader observability use-cases, with clear alignment to performance and operational goals.
Month: 2025-10 — Focused on strengthening Odigos build reliability and extensibility by integrating rsync into base images and expanding instrumentation capabilities. Delivered targeted changes across two repositories (AvihuHenya/odigos and BenElferink/odigos) to optimize images, simplify builds, and enable custom eBPF-based instrumentation. These efforts reduce image sizes and build times, streamline customization, and lay groundwork for broader observability use-cases, with clear alignment to performance and operational goals.
Monthly summary for 2025-08 (AvihuHenya/odigos): Key feature delivered: Go Redis instrumentation enhancement that adds a sub_category attribute populated from db.system.name for Redis operations across multiple versions of the Go Redis client. This improves data granularity and observability for Redis interactions. The work is captured in commit bb2a24f17c3c733e0e355fe8dc0b15cbb5533655 with message RUN-117. Major bugs fixed: None reported this month for this repository. Overall impact and accomplishments: Enhanced telemetry and data granularity for Redis operations, enabling more precise filtering, faster root-cause analysis, and improved operational insight. This supports better troubleshooting, capacity planning, and customer experience by reducing time to diagnose Redis-related issues. Technologies/skills demonstrated: Go, Redis instrumentation, telemetry data modeling, cross-version compatibility, commit-based change tracking, code quality improvements.
Monthly summary for 2025-08 (AvihuHenya/odigos): Key feature delivered: Go Redis instrumentation enhancement that adds a sub_category attribute populated from db.system.name for Redis operations across multiple versions of the Go Redis client. This improves data granularity and observability for Redis interactions. The work is captured in commit bb2a24f17c3c733e0e355fe8dc0b15cbb5533655 with message RUN-117. Major bugs fixed: None reported this month for this repository. Overall impact and accomplishments: Enhanced telemetry and data granularity for Redis operations, enabling more precise filtering, faster root-cause analysis, and improved operational insight. This supports better troubleshooting, capacity planning, and customer experience by reducing time to diagnose Redis-related issues. Technologies/skills demonstrated: Go, Redis instrumentation, telemetry data modeling, cross-version compatibility, commit-based change tracking, code quality improvements.
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