Découvrez de nombreuses nouveautés à l'occasion de notre lancement du 2e trimestre 2023 : moteur Kora Engine, règles de qualité des données, et bien plus encore | S'inscrire pour une démo
Twilio is a communications company with SMS, Voice APIs which see traffic spikes and troughs based on times of the day and week when companies send out communications(think early morning stock updates) or when end customers interact with companies(think restaurant delivery orders placed at lunch or dinner times) When building a generic monitoring system using Kafka Streams with exactly-once-processing, this spiki-ness can cause some set of our customers(think companies with a lot of interactions as above) to have more traffic at certain times of the day which can let them overpower traffic for other customers(think a group of hospitals sending communication about appointments). This talk elaborates the challenges that Twilio faced when building such a monitoring platform, which can aggregate customer data and send alerts in a timely manner under SLA. The optimizations we would go in depth are :-
Do listen to this talk if building a real time alerting pipeline OR spreading a mix of global and local state stores OR aggregations over upserts OR use of punctuators in the wild piques your interest.