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Simon Ritter looks at the fundamentals of how modularity in Java works. He explains the impact project Jigsaw has on developers in terms of building their applications, as well as helping them to understand how things like encapsulation will change in JDK 9.
Ben Stopford looks at the implications of mixing toolsets from the stream processing world into real-time business applications: how to effectively handle infinite streams, how to leverage a high throughput, persistent Log and deploy dynamic, fault tolerant, and streaming services.
How do you handle a long list of defects in your project? You don't. If it is not worth fixing a defect right now, it’s not likely that we will find the time to do it later. Also, it becomes more and more difficult over time to correct the defect, so it cheaper to solve it now. Kirill Klimov explains why you should solve defects right away, or state that you will not solve them.
Manuel Fahndrich describes how they tackled one particular resource allocation aspect of Google Cloud Dataflow pipelines, namely, horizontal scaling of worker pools as a function of pipeline input rate. Managing the redistribution of key ranges across new pool sizes and the associated persistent data storage was particularly challenging.
New YorkJun 13-17
San FranciscoNov 7-11
LondonMar 6-10, 2017
Project Jigsaw in JDK 9: Modularity Comes To Java
A Look at Microsoft DNA Storage
Controlling Hybrid Cloud Complexity with Containers: CoreOS, rkt, and Image Standards
Microservices for a Streaming World
Microsoft Releases BizTalk Server 2016 CTP 1
Now or Never: The Ultimate Strategy for Handling Defects
Business Mapping: Building an Agile Organization
How Comcast Uses Data Science and ML to Improve the Customer Experience
AirFlow Joins Apache Incubator
Streaming Auto-scaling in Google Cloud Dataflow
DevOps Days for the Enterprise
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