Posts in distributed-tracing

Pivot Tracing

Pivot Tracing lets users define arbitrary metrics over trace data at runtime. It does so by combining two powerful techniques:

  1. A Happen-Before operator that allows users to perform queries based on the causal relationship of the events.
  2. The ability to instrument code dinamically without having to redeploy.

written in distributed-tracing, observability, papers Read on →

Sifter: Scalable Sampling for Distributed Tracing

Distributed tracing can be ridiculously expensive if you try to trace a hundred percent of requests. A common technique to reduce costs is to sample only a small portion of the traffic. But naive sampling techniques like uniform sampling will inevitably capture more common-case executions and might miss the more interesting edge cases. Instead, [Sifter’s approach][1] is to bias sampling decisions towards outliers and anomalous traces. This way, anomalous traces have a higher chance of being sampled, and the more uninteresting traces are discarded.

written in distributed-tracing, observability, papers, sampling Read on →