Your CTO messages you out of the blue one day: How much effort would it be to run XYZ on Kubernetes? Shudder. Although there are some nuances to the process, it is fairly straightforward. This article assumes some knowledge of containers, Kubernetes, and JVM applications. Our goal is to migrate the application with as few … Read More
Abstract What do you do when your quest for power leads you to implementations which are not just platform-but processor- and even architecture-version-specific in nature? How do you even start tracking down a bug in a Scala-based implementation which is not only nondeterministic, but only manifests on certain hardware? In this talk, we will dive … Read More
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Ken talks to Dan Boykis, a consultant here at Chariot, about mentoring others remotely, building a JVM from scratch, Clojure, and temporal databases.
Abstract In the Java ecosystem, we have historically been enamored by the concept of the “Application Server,” the runtime engine that not only gave us portable APIs (e.g. JMS, JAX-RS, JSF, EJB) but also gave us critical runtime infrastructure for things like farm deployments, configuration, load-balancing, fail-over, distributed management and monitoring. In this session, we … Read More
Out of many strong JVM based languages Clojure and Java make a great couple. Coming to Clojure from Spring several years ago Anatoly Polinsky really wished, back then, someone could explain functional programming and Clojure ecosystem to me from the Spring/Java point of view. In this talk Anatoly Polinsky of Chariot Solutions will bridge the … Read More
SbtTestGrouping Running tests that use a HiveContext On our current project, we utilize Spark SQL and have several ScalaTest based suites which require a SparkContext and HiveContext. These are started before a suite runs and shut down after it completes via the BeforeAfterAll mixin trait. Unfortunately due to this bug (also see this related pull … Read More
This talk will be an accessible exploration of the JVM Heap, thread stacks and concurrency primitives on the JVM and how to compose multi-threaded code in Java and Scala.
As a JVM/GC performance engineer – I always ask pertinent questions such as – what are performance expectations of the product by the stakeholders? what are the important metrics?, what are the tuning goals?, etc. and then I discuss tradeoffs and finally establish tuning goals.
In this session we are going to talk a bit why JetBrains sees the potential in Kotlin comparing to other JVM languages. Then we’ll see how certain language constructs can be used to make Android more enjoyable. Also we’ll look at a DSL for type-safe dynamic layouts and a simple extension plugin that helps to avoid writing ‘findViewById()’ all the time.
This talk will be an accessible exploration of the JVM Heap, thread stacks and concurrency primitives on the JVM and how to compose multi-threaded code in Java and Scala.
