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Presentation: Grading Observability (Note: Not a Product Pitch!)

Track: Sponsored Solutions Track I

Location: Bayview AB

Duration: 10:35am - 11:25am

Day of week: Monday

Slides: Download Slides

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Abstract

Nobody denies the importance of observability in modern production software: with microservices adding scale, concurrency, and frequent deploys, it’s getting harder and harder to answer even basic questions about application behavior. The conventional wisdom has been that metrics, logging and tracing are “the three pillars” of observability, yet organizations check these boxes and still find themselves grasping at straws during emergencies. The problem is that metrics, logs, and traces are just data – if what we need is a car, all we’re talking about is the fuel. We will continue to disappoint ourselves until we reframe observability around two fundamental activities:

(1) detection and

(2) refinement.

For effective observability, “detection” must be both robust and precise, overcoming cardinality concerns amid massive data volumes. “Refinement” revolves around rapid hypothesis testing: we must understand global context across service boundaries, decipher the side-effects of contention under peak load, and present everything with historical reference points to understand what’s changed and what’s normal behavior. In this session, we’ll summarize the contemporary observability dogma, then present a new observability scorecard for objectively reasoning about and assessing observability solutions for modern distributed systems.

Speaker: Ben Sigelman

CEO and co-founder @LightStepHQ, Co-creator @OpenTracing API standard

Ben Sigelman is a co-founder and the CEO at LightStep, a co-creator of Dapper (Google’s distributed tracing system), and co-creator of the OpenTracing and OpenTelemetry projects (both part of the CNCF). Ben's work and interests gravitate towards observability, especially where microservices, high transaction volumes, and large engineering organizations are involved.

Find Ben Sigelman at

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