For retailers, securing the customer experience is as critical as delivering speed and personalization. A secure and high-performance Java platform is critical for online orders, payment processing, fraud detection, and real-time risk scoring.
In this post you will learn:
- Out-of-the-box Java (based on OpenJDK) suffers from inefficiencies like garbage collection pauses and limited code execution speed improvements
- 71% of organizations have more than 20% of unutilized cloud compute capacity that they pay for
- Retailers use the performance of optimized Java to strengthen security and prevent fraud
- Azul Platform Prime enables retailers to reduce cloud instances by 50% while increasing performance
Many retail environments are built on complex, Java-based architectures which can include hundreds of microservices and e-commerce applications. Without a high-performance Java platform, you’re forced to overprovision cloud resources as transaction volumes fluctuate. Overprovisioning leads to inflated cloud costs and unnecessary IT complexity, but your alternative is to fail to meet consumers’ service expectations.
In an era of sophisticated cyberattacks and increasing fraud, securing the customer experience is as critical as delivering speed and personalization. Providing a secure and high-performance Java platform is critical for payment processing, fraud detection, real-time risk scoring, and of course completing your customers’ online orders. IT and DevOps leaders are faced with the challenge of ensuring their Java runtime can support peak performance while minimizing the number of cloud instances required to maintain service levels.
According to the 2025 State of Java Survey & Report of more than 2,000 Java professionals, 71% of organizations have more than 20% of unutilized cloud compute capacity that they pay for.
While out-of-the-box Java, based on OpenJDK, has made some incremental performance gains, it still suffers from inefficiencies like garbage collection pauses and limited code execution speed improvements from language enhancements. These issues make it challenging to strike the right balance between the speed and scale to serve your customers and the cost efficiency to stay profitable.
Strengthen security and prevent fraud with optimized Java performance
Every year cyberattacks get more sophisticated, and fraud reaches record levels. Securing the customer experience is as critical as delivering speed and personalization. Typical Java runtimes often struggle to meet real-time demands. AI-powered fraud detection platforms analyze massive amounts of data. Any lag in Java performance runtimes, such as latency spikes from garbage collection or compute inefficiencies, can delay detection and leave you exposed to fraud and security data breaches.
Global e-commerce losses to online payment fraud surpassed $44 billion in 2024, according to a report from Statica.
Conclusion
Retail and e-commerce leaders use Azul Platform to overcome performance and scalability constraints of standard Java runtimes. Azul customers routinely save 20% or more on cloud spend by reducing the number of JVMs required to deliver consistent peak performance. This leads to faster page loads, real-time personalization, and lower cart abandonment rates, especially during high-traffic periods like holiday sales or major product drops.
How Azul Platform Prime delivers value:
- Stability at Scale: Maintain performance during flash sales, seasonal spikes, or social traffic surges without overprovisioning infrastructure.
- Lower Cloud Costs: Reduce the need to overprovision infrastructure, often cutting compute and memory expenses by 20% or more.
- Improve Throughput: Increase transaction volumes per JVM instance, enabling retailers to handle more users with fewer servers.
- No Code Changes Required: Improve app performance simply by replacing the runtime —no refactoring, recompilation, or retraining needed.
Backed by FinOps Principles: Azul is a FinOps Foundation member, helping organizations optimize cloud usage and align spend with business outcomes.
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