Cloud Native Compiler streams an application’s fully optimized compiled code to every new instance at start-up, slashing the warm-up tax

Azul, the trusted leader in enterprise Java for today’s AI-first world, today announced that Azul Prime now delivers 2x-5x faster application warm-up versus standard OpenJDK, letting enterprises run leaner, more dynamic and more cost-efficient Java deployments.

The improvement comes from Azul Optimizer Hub’s Cloud Native Compiler, a unique capability of Azul Prime, which centralizes and caches just-in-time (JIT) compilations across a fleet of Java Virtual Machines (JVMs) instead of leaving each JVM to optimize performance in isolation. New instances launched for a given application or microservice receive streamed, fully optimized compiled code at startup even before they take traffic, helping applications reach full performance far sooner than on standard OpenJDK.

The Fleet-Wide Warm-Up Tax

The shift to container-based cloud applications and services that scale dynamically, coupled with code being deployed at much higher velocity through the use of AI codegen tools, makes efficient JVM warm-up more critical than ever. Nearly two-thirds of Kubernetes organizations now scale automatically, up from around 55% less than two years ago, according to Datadog’s 2025 State of Containers and Serverless report.¹ At the same time, developers pushed nearly 1 billion commits to GitHub in 2025, up 25% year over year, as AI coding tools accelerate the pace of change, according to GitHub’s 2025 Octoverse report.²

In traditional deployments, each JVM of an application has no knowledge of what other instances in the fleet have already learned and optimized, so every new instance runs slower, less optimized code until it learns as it runs that code segments are being used often enough to be optimized — creating the common “warm-up” problem when starting new instances. Scale doesn’t fix this: no matter how many instances a fleet has already warmed up, the next one starts cold.

Teams work around the warm-up tax today either by over-provisioning compute capacity to absorb slow warm-up or simply accepting a period of degraded performance and latency after every deploy. Those workarounds result in either higher costs from idle capacity, lost revenue from missed transactions as applications start, or poor customer experience from visible slowdowns. That habit is getting more expensive: CPU overprovisioning in Kubernetes — the gap between provisioned capacity and what workloads actually request — rose from 40% to 69% year over year, according to Cast AI's 2026 State of Kubernetes Optimization Report.³

Solving the Warm-up Problem Across Java Fleets

The warm-up problem is a long-standing challenge with Java deployments, and Azul has been providing capabilities to help address it since 2014, when it introduced ReadyNow to address warm-up delays for individual JVMs in latency-sensitive workloads. In 2023, Azul extended that with ReadyNow Orchestrator, which monitors and learns the best warm-up optimization profile across an application’s fleet of JVMs, and serves it to any instance that requests it. Cloud Native Compiler now takes that same fleet-wide intelligence further, shifting from serving compiled code on request to delivering it preemptively at start-up, so each instance warms up 2x-5x faster than standard OpenJDK. With this new capability, each JVM instance of an application or microservice now receives:

• Predictive delivery: Instead of requesting and receiving compiled code method-by-method, an instance receives, as a single stream at start-up, the fully optimized code predicted to be needed based on previous instance starts across an application’s fleet.
• Preemptive installation: Rather than discovering hot code paths through slow code interpretation and promotion, the new instance being started installs code the application’s fleet has already optimized — captured from how identical workloads have already successfully run — so those optimizations are in place before real traffic arrives, not reacting to it.
• No application changes: There is no rewrite, recompile, or re-architecture for applications or microservices; a simple configuration setting in Azul Prime with Cloud Native Compiler enables this unique capability.

The result is that every new instance inherits the application fleet’s prior work instead of re-learning it, reaching full production speed well ahead of standard OpenJDK deployments. Unlike Ahead-of-Time approaches, Cloud Native Compiler accumulates optimizations across a live fleet, and continues to learn and optimize as the application runs — so the benefit compounds as more of the fleet runs. No other JVM or OpenJDK distribution offers comparable fleet-wide optimization and warm-up benefits.

What Faster Warm-Up Unlocks

Reaching full speed much faster, rather than warming up instance-by-instance, changes the economics of running a Java fleet at scale in two important ways:

• Smoother autoscaling, lower cloud costs: Java teams typically keep extra warm standby instances as capacity that exists only to cover the time a new instance needs to warm-up. When new instances are productive far faster, that required headroom can be dramatically reduced, if not eliminated. Operators who statically over-provision or use scheduled autoscaling may now be able to dynamically autoscale and bring warm instances online quickly to slash standby compute capacity.
• Responsive customer experience: In standard OpenJDK deployments, customer requests are most likely to time out, have long latencies or experience disruption on a cold JVM where first transactions run on slower, less optimized code. By substantially reducing the warm-up penalty, every newly scaled or redeployed instance typically behaves like the rest of the optimized fleet from its first request, whether that’s during a traffic spike or a routine redeploy, improving performance from the get-go and creating a seamless customer experience.

The result is especially important for businesses where peak performance from the very first request is non-negotiable: fraud detection, real-time ad bidding, digital payments, multi-player gaming and e-commerce.

A Turnkey Approach for Channel Partners

This new capability in Azul Prime with Cloud Native Compiler enables Azul’s channel partners to deliver significant cost savings for the benefit of their customers, including through their professional services and managed deployment offerings — all from Java application infrastructure already in place, and without the need for application re-writes or re-architecture.

“Teams have lived with slow JVM warm-up for so long they treat it as a given, over-provisioning and avoiding autoscaling just to hide it,” said Scott Sellers, co-founder and CEO of Azul. “Azul Prime with Cloud Native Compiler fixes that. A new application instance inherits the compiler optimizations its fleet has already learned and executed instead of starting cold. You stop paying the warm-up tax on every single instance, thereby slashing the time required for a given application instance to reach its full performance.”

Cloud Native Compiler is available at no additional charge as part of Azul Prime.

To see how Azul Prime’s Cloud Native Compiler can cut warm-up time across your Java fleet, visit the Cloud Native Compiler page.

FAQs

Why does a Java application instance start up slowly, even when the code hasn’t changed?
The Java Virtual Machine (JVM) is responsible for running the application code, and at start-up, it begins to interpret and (over time) compile the code into more optimized execution. This “cold start” process takes time, and each instance in an application’s fleet goes through this slow process even if other instances are already running at full speed. Azul Prime’s Cloud Native Compiler reduces that penalty by streaming an application fleet’s already-compiled code to each new instance at start-up, so it reaches full speed 2x-5x faster compared to standard OpenJDK.

How can I stop over-provisioning cloud capacity just to absorb slow JVM warm-up?
Over-provisioning and keeping extra warm standby instances is a workaround for a JVM that warms up too slowly, not a fix. Azul Prime addresses the root cause: new application instances inherit their fleet’s compiled code the moment they start, so teams can reduce, if not eliminate, that idle capacity they were carrying to mask warm-up problems.

Is there a way to share JIT compilation across an application’s fleet instead of repeating it in for every JVM started?
Yes. Azul Prime’s Cloud Native Compiler caches the compiled code an application’s fleet produces in a centralized service; its newest capability streams that code preemptively to every new instance at start-up, further reducing the time required for an instance to reach full performance.

What’s the fastest way to get consistent performance and latency across instances for a horizontally scaled Java application?
Consistency across an application JVM fleet depends on how fast new instances warm-up and reach fully optimized performance. Azul Prime with Cloud Native Compiler substantially reduces an instance’s warm-up time by having new instances install their fleet’s accumulated optimizations before real traffic arrives, compared to traditional deployments where each instance is warmed up independently with the resultant poor performance and latency during that warm-up period.

Can I improve Java warm-up performance without changing application code?
Yes. Azul Prime’s fleet-wide compiled-code streaming is enabled with a single configuration change to a Cloud Native Compiler deployment: no application rewrites, recompilation or re-architecture required.

About Azul

Azul is the trusted leader in enterprise Java for today’s AI-first world. Its open source-based Java platform empowers organizations to optimize the entire Java lifecycle to accelerate performance, strengthen security, reduce licensing and cloud costs, and boost developer productivity. Azul powers mission-critical systems for 37% of the Fortune 100, 50% of the Forbes Top 10 World’s Most Valuable Brands, and the world’s top 10 financial trading companies. Learn more at azul.com and follow @azulsystems.

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The result is especially important for businesses where peak performance from the very first request is non-negotiable: fraud detection, real-time ad bidding, digital payments, multi-player gaming and e-commerce.