Prime Time

09:00am

Welcome

Join us for Prime Time! You’ll hear from industry experts, seasoned developers, and performance engineers as they dive into real-world use cases for a high-performance Java Platform and strategies for optimizing your Java estates without sacrificing stability or scalability. This virtual event is your gateway to smarter, faster, and more efficient Java.

Anne Plese

Director Product Marketing, Azul

Pratik Patil

VP Developer Advocacy, Azul

09:15am

Write Once, Deploy Everywhere: From Containers to Serverless

While Java apps are technically portable across many platforms, it can be tricky to not tightly couple them to specific deployment platforms, severely degrading their portability. Unfortunately containers alone haven’t fully isolated the myriad of differences across platforms. This session will cover ways that we can build, package, and deploy Java applications, so they remain portable. This enables scaling from cost-efficient and developer environments, to massive scale Kubernetes deployments. Using examples with Spring, you’ll learn how to:

Abstract service configuration / binding
Utilize Test containers across local dev/test & CI
Efficiently avoid cold starts with CRaC and other techniques
Package applications most efficiently for the target platforms

While Java apps are technically portable across many platforms, it can be tricky to not tightly couple them to specific deployment platforms, severely degrading their portability. Unfortunately containers alone haven’t fully isolated the myriad of differences across platforms. This session will cover ways that we can build, package, and deploy Java applications, so they remain portable. This enables scaling from cost-efficient and developer environments, to massive scale Kubernetes deployments. Using examples with Spring, you’ll learn how to:

Abstract service configuration / binding
Utilize Test containers across local dev/test & CI
Efficiently avoid cold starts with CRaC and other techniques
Package applications most efficiently for the target platforms

James Ward

Principal Developer Advocate, AWS

09:45am

Making JVM Fleet Restarts Easier for Java Performance & Scale Using Cloud-Native Compilation

In this session we will break down how one of Azul’s largest e-commerce retailers improved shopper experience during check-out. You will learn how to simplify cloud-native JVM fleet restarts and streamline DevOps workflows. We will look at how to dramatically improve application warm-up by using cloud-native optimizations that reduce the number of instances needed for Java workloads.

You will learn:

A before and after view of a JVM lifecycle where smart compilations are automatically applied and available to the JVM before traffic hits.
Practical ways to accelerate JVM initialization code and boost cloud efficiency using a performance-optimized Java runtime.
How to optimize JVM behavior so it can take traffic earlier in the start-up and warm-up cycles.

In this session we will break down how one of Azul’s largest e-commerce retailers improved shopper experience during check-out. You will learn how to simplify cloud-native JVM fleet restarts and streamline DevOps workflows. We will look at how to dramatically improve application warm-up by using cloud-native optimizations that reduce the number of instances needed for Java workloads.

You will learn:

A before and after view of a JVM lifecycle where smart compilations are automatically applied and available to the JVM before traffic hits.
Practical ways to accelerate JVM initialization code and boost cloud efficiency using a performance-optimized Java runtime.
How to optimize JVM behavior so it can take traffic earlier in the start-up and warm-up cycles.

Simon Ritter

Deputy CTO, Azul

10:15am

Cut Java Cloud Costs; Proven Strategies to Optimize Java Workloads and Reduce Waste

Java applications account for a significant portion of enterprise cloud costs—more than 65% of organizations surveyed say over half their cloud compute spend comes from Java workloads (source: Azul). With FinOps teams prioritizing workload efficiency and waste reduction (source: FinOps Foundation), Java has become a critical area of focus.

What you’ll learn:

How leading DevOps teams at Mastercard, Priceline, and Workday are reducing Java cloud waste while meeting performance SLAs.
Switching your Java runtime is one of the easiest, most impactful ways to boost cloud efficiency and app performance.
Why FinOps teams are focused on optimizing Java workloads and how to get ahead with practical optimization strategies.

We’ll explore how leading companies are optimizing their Java workloads to dramatically reduce cloud waste, without sacrificing performance. You’ll learn practical steps to modernize your approach to Java, including the impact of choosing the right Java runtime when building high-performance, cloud-efficient applications.

Java applications account for a significant portion of enterprise cloud costs—more than 65% of organizations surveyed say over half their cloud compute spend comes from Java workloads (source: Azul). With FinOps teams prioritizing workload efficiency and waste reduction (source: FinOps Foundation), Java has become a critical area of focus.

What you’ll learn:

How leading DevOps teams at Mastercard, Priceline, and Workday are reducing Java cloud waste while meeting performance SLAs.
Switching your Java runtime is one of the easiest, most impactful ways to boost cloud efficiency and app performance.
Why FinOps teams are focused on optimizing Java workloads and how to get ahead with practical optimization strategies.

We’ll explore how leading companies are optimizing their Java workloads to dramatically reduce cloud waste, without sacrificing performance. You’ll learn practical steps to modernize your approach to Java, including the impact of choosing the right Java runtime when building high-performance, cloud-efficient applications.

10:45am

Java & AI, Moving from Experiments to Business Implementations

In the ongoing Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLM) revolution, Python has played a crucial role and has become the standard language for a lot of data scientists and machine learning engineers. However, as we move from experiments to business implementations, many organizations want to rely on the many benefits of Java and its stability and maturity. In this session, we want to highlight why Java deserves to be the primary choice for training AI and ML models and LLM-based applications in production environments.

Frank Delporte

Senior Technical Writer, Azul

11:15am

Migrating Java Workloads to the Cloud

Modernizing Java applications doesn’t have to mean rewriting them. In this session, we’ll show you how to unlock the full power of cloud elasticity and scalability—without changing a single line of your existing code. Learn how organizations are running legacy Java workloads more efficiently in the cloud, with immediate performance improvements and minimal disruption.

You’ll discover:

How to migrate legacy Java apps to the cloud with zero refactoring
Strategies to enhance scalability and elasticity for existing workloads
Real-world examples of improved Java performance in cloud environments

Modernizing Java applications doesn’t have to mean rewriting them. In this session, we’ll show you how to unlock the full power of cloud elasticity and scalability—without changing a single line of your existing code. Learn how organizations are running legacy Java workloads more efficiently in the cloud, with immediate performance improvements and minimal disruption.

You’ll discover:

How to migrate legacy Java apps to the cloud with zero refactoring
Strategies to enhance scalability and elasticity for existing workloads
Real-world examples of improved Java performance in cloud environments

11:45am

Java Perf & Scale: Mastering Techniques for Efficient Applications

Building performant and scalable Java applications involves several key strategies that span from coding, to architecture, to deployment. In this session, we’ll start at a high level and dive deep into code and talk about scaling.

We’ll cover these topics:

Code Profiling and Bottleneck Identification
Efficient Coding Practices
Caching and Connection Pooling
Memory Management and Garbage Collection
Scalability Techniques

After this session, you’ll have specific techniques you can apply to your own Java applications to make them run with lower latency, faster throughput, and higher stability!

Building performant and scalable Java applications involves several key strategies that span from coding, to architecture, to deployment. In this session, we’ll start at a high level and dive deep into code and talk about scaling.

We’ll cover these topics:

Code Profiling and Bottleneck Identification
Efficient Coding Practices
Caching and Connection Pooling
Memory Management and Garbage Collection
Scalability Techniques

After this session, you’ll have specific techniques you can apply to your own Java applications to make them run with lower latency, faster throughput, and higher stability!

Pratik Patil

VP Developer Advocacy, Azul

12:15pm

Powering Production-Ready AI with Spring AI, Amazon Bedrock, and MC

Building production-worthy AI systems and services isn’t hard – you just need the right tools. Join AWS developer advocate James Ward and Spring Developer Advocate Josh Long as they explore how to wield Spring AI, Amazon Bedrock, MCP and more to build scalable AI systems.