Scale by the Bay
Scale by the Bay is a By the Bay technology conference.
Talks & recordings
94 connected sessions
Workshop (Separate Registration): Buildi...
Together with the leaders in full-stack architectures, we bring you an all -star workshop on the modern microservice architectures as done by Google, Salesforce, Lyft, Starbucks, and other great companies. This is a paid workshop preceding the conference. It requires a separate registration; discounted packages are available together with the conference. In this special one day hands-on workshop you will learn how to take a Cloud Native Application from inception to production. Starting with a base sample application we will learn how to break the application into separate services that communicate via gRPC. We will learn how to take that application into production using Kubernetes. Next we will look at the challenges of reliable service communication in a complex topology of services. The last part of the workshop will layer in Istio to create a service mesh for advance security, traffic management and telemetry. This workshop will be taught by a unique team of engineers who ha
An introduction to Xtract
Xtract is a simple, easy to use scala XML extraction/deserialization library modeled after the JSON library in the Play framework. It uses functional style composition to combine simple parsers into more complex parsers. Lucid Software has successfully used it in our implementation of importing Indesign documents into Lucidpress.
Avoiding Spark Pitfalls at Scale
There’s no doubt that Apache Spark is a very powerful tool for scalable data, but beware, forces lurk in the shadows to bring upon your downfall, especially so at scale! In this talk, we’ll talk about some of the challenges and pitfalls encountered when writing data pipelines with Spark and how we’ve learned to deal with them. Our tales will involve battles with memory management, dataset typesafety, lazy versus strict evaluations, and beyond. This talk will use only the Scala API of Spark, but the tips and tricks presented will apply to Spark in general.
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