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zendesk.engineering
Originally we implemented a feature to persist an event-stream into DynamoDB to allow customers to retrieve them. This proved effective, serving as a strong use case for a key/value storage, yet the drawback was its high cost. Moving to provisioned billing-mode reduced cost by ~50%, but that was not going to be sustainable as we scaled to more customers. We also kept multiplying the cost each time
ZEN and the art of Reliability Zendesk’s reliability principles and the real-world stories as we transitioned from a humble IT help desk software to providing mission critical systems for enterprises. Zendesk handles approximately 250,000 requests per second at daily peak into our infrastructure, with over ½ of those requests needing to read or write to a database. At our core we’re a humble Ruby
What it feels like when your app is leaking memoryIntroductionOver the last few years at Zendesk, both Go and Kafka have been increasingly growing in importance in our architecture. It was of course inevitable that they should meet, and so various teams have been writing Kafka consumers and producers in Go of late. There are a few different library options for building Kafka apps in Go, but we’ve
How We Started With TensorFlowAt Zendesk we are developing a series of machine learning products, the most recent of which is Answer Bot. It uses machine learning to interpret user questions and responds with relevant knowledge base articles. When a customer has a question, complaint or enquiry, they may submit their request online. Once their request is received, Answer Bot will analyse the reque
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