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Ivan Kruglov

My talk about optimizing golang version of Sereal at Golang Amsterdam meetup. Overall speed up was around 3-4x.

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Service mesh is a dedicated layer of a company's infrastructure which should simplify communication between services and make it reliable, secure and observable. In this talk, we'll go deep into Booking.com's case study of introducing service mesh. We will discover the reasons and objectives of the project. Why Envoy was selected as the base rather than other available options. Find out what is the setup and features of the homegrown control plane. We will expand on what service is provided for developers and how they safely deploy potentially dangerous configuration changes. Finally, we will talk about pitfalls met along the way.

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Booking.com uses Sereal in many applications. One of the biggest use case though is the events pipeline. It was built to delivery messages (events) from generation point to various processors in near real-time fashion. These days it servers billions of messages per day. One of our processors recently faced scalability issues due to growth of the volume of delivered events. In this talk I would like to share what problem we had, how we addressed it and which new features of Sereal helped us.

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Searches are hard, fast searches are harder and even more with growing dataset. At Booking.com we face these problems, especially the last one: we have doubled the number of properties in the last two years. Searching across normalized data in MySQL stopped working for us 3-4 years ago. Optimizing the dataset in MySQL for searches recently began to showing its limits on large destinations like Paris, Italy or the Mediterranean. Join the talk to learn how we’re solving search problems by moving data from MySQL to RocksDB and bringing code to the data.

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Sereal is a schema-less, cross-language binary serialization protocol aiming to replace Storable in Perl. It natively handles almost all Perl data structures including “special" ones such as aliases, weakrefs, regexps and cyclic references. Sereal supports compression and string de-duplication and employs other nice tricks allowing it to produce one of the most compact outputs across available serialization libraries. It is also very fast! Sereal is widely adopted at Booking.com for serialization of objects for storage (MySQL, Redis, Memcached), as the default format for transferring data between different services, and for delivering logging data in our distributed environment. Being very efficient in both speed and space Sereal::Encoder and Sereal::Decoder provide facilities which are not optimal in certain cases. For example many manipulations on encoded documents can be done only through re-serialization. To improve performance characteristics for these cases a set of tools was created: - Sereal::Path - a query engine for Sereal allowing extraction of a single part of a document, similar to XPath and JSONPath. - Sereal::Merger - a tool to combine several Sereal documents into a single one. - Sereal::Splitter - a tool to split large documents into smaller ones. In my talk I will give a quick introduction to Sereal and its internals. I’ll cover some design choices and important features. Finally, I’m going to explain the reasons of creating the tools and the best situations for using them.

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