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This document contains information about chaos engineering and experimenting with latency injection between microservices. It discusses distributing traffic between production, control, and experimental versions of a service called Service A. 98% of traffic would go to the production version, 1% to the control version, and 1% to the experimental version where latency is injected between Service A and downstream services using an injector. This allows experimenting with how systems react to different latency conditions to test resilience and identify problems.
Slides contain various alphanumeric sequences that may represent codes, identifiers, or placeholders.
Slide 4 presents the concept that chaos reveals problems, while slides 5 and 6 provide external links related to chaos engineering.
These slides discuss chaos as both a mechanism (injection) and present resources like chaos proxies from GitHub.
Slide 16 mentions Audible's user engagement metrics, while slides 17-26 show data tables about service performance and latency injectors.