This post walks through a layered performance investigation that cut PSE-kafka's infrastructure costs by 83% and ended a run of 19 P1 incidents.
PSE-kafka (price-search-engine-kafka) is an internal microservice. It consumes hotel price Kafka messages and pushes ads to an external Ads service, which drives real revenue for trivago. But the service had a few persistent problems.
At trivago we operate on petabytes of data. In live-traffic applications that are related to the bidding business cases we use our in-house in-memory key-value storage-service written in Java to keep data as close to calculation logic as possible.
When operating applications in Kubernetes, proper lifecycle management is crucial to enable Kubernetes to manage applications correctly throughout their different phases: startup, runtime and shutdown. Improper or incomplete lifecycle management can lead to incidents with unforeseen and difficult to debug application behavior, such as random CrashLoopBackOffs, broken/zombie services not being restarted or even entire services not becoming healthy after a scheduled restart.
Tackling hard technical problems is like going on an adventure - and at trivago, there's no shortage of them. From powering our search and ranking with AI, to exploring the latest tech and working with massive datasets, every challenge here directly shapes the hotel search experience for millions of travelers. Ready for your next adventure?
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