Kyle Moore
3,098 viewsRemote and Distributed Build Patterns
Let's review build patterns leveraging remote machines, clarify the definition of remote and distributed builds, and discuss their …
Category
Performance
Kyle Moore
3,098 views
Shai Almog
3,681 viewsSpring Boot Performance Workshop with Vlad Mihalcea
Learn how to improve the performance of a Spring application and diagnose production problems. Lessons from our live workshop covering JPA!
Carl Dea
11,454 viewsBuilding Project Panama's jextract tool by yourself
Learn about jextract, which can generate Java binding code that represents native functions or variables (symbols) from C libraries.
Matt Fleming
2,060 viewsHow DataStax Tracked Down a Linux Kernel Bug with Fallout
Sometimes as a developer, you run into a bug buried deep within the layers of your software stack. Chasing down the root cause requires not …
Artem Chebotko
2,693 viewsOptimizing Distributed Joins: The Case of Google Cloud Spanner and DataStax Astra DB
In this post, learn how relational and NoSQL databases, Google Cloud Spanner and DataStax Astra DB, optimize distributed joins for real-time …
Simon Ritter
3,548 viewsSuperfast Application Startup: Java on CRaC
If you want a superfast startup for your Java applications without warmup time or resources, why not try Java on CRaC?
John Ceccarelli
3,157 viewsLet's Compile Java Code in the Cloud!
Antiquated features of the JVM make it hard to utilize resources on your Cloud instances. Is it time for Java compilation in the Cloud?
Miro Wengner
6,375 viewsDiving into JVM Framework Monitoring and Profiling
Let's look at how frameworks work under the hood, namely Quarkus and Spring Boot, and how many threads they initiate to serve up results.
John Ceccarelli
4,197 viewsGetting More Mileage Out of Kafka: OpenJDK vs. Azul Prime
Kafka is horizontally scalable, fault-tolerant, runs in production for thousands of companies – let's figure out how to get more out of it!
Miro Wengner
13,435 viewsThinking About Massive Throughput? Meet Virtual Threads!
Virtual threads not only help to increase application throughput, they also provide a framework to refactor already existing code.