The topic of I built a lightweight OpenTelemetry viewer for local development is currently the subject of lively debate — readers and analysts are keeping a close eye on developments.
This is taking place in a dynamic environment: companies’ decisions and competitors’ reactions can quickly change the picture.
Every time I wanted to test OpenTelemetry instrumentation locally, I had to spin up Jaeger or a full collector stack. docker-compose up, wait, configure exporters, hope nothing clashes on port 4317… It felt like too much ceremony for a "does my trace look right?" check.
So I built otel-front: a single binary that receives OTLP data and shows it in a web UI. No Docker, no external database, no config files.
The backend is Go (Gin). The React frontend is built with Vite and then embedded directly into the binary using Go's embed.FS:
I needed SQL (for flexible filtering and aggregations) without shipping a database. DuckDB fits perfectly — it runs entirely in-process, zero setup, and handles analytical queries well.
Traces, spans, logs, and metrics all land in DuckDB tables with JSON columns for attributes:
Instead of writing protobuf parsers from scratch, I reused the OpenTelemetry Collector's pdata library. It handles deserialization; I just transform the result into my internal models.
PRs and feedback welcome. If you're working with OpenTelemetry locally and
find it useful (or broken), let me know in the comments.
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Why it matters
News like this often changes audience expectations and competitors’ plans.
When one player makes a move, others usually react — it is worth reading the event in context.
What to look out for next
The full picture will become clear in time, but the headline already shows the dynamics of the industry.
Further statements and user reactions will add to the story.