Akamas Autonomous performance optimization for banking apps
Performance optimization for banking apps

During the event “Continuous Core Banking Performance Optimization” organized together with our partners Performetriks and Dynatrace, we presented how Akamas allows banks and financial companies to maximize their service performance and resilience, while also reducing costs. In the recorded video (about 20

PurePerformance Podcast Akamas
Busting 4 Java tuning myths with Stefano Doni

Ascolta “Busting 4 Java Tuning Myths with Stefano Doni” su Spreaker. In this PurePerformance episode, Stefano Doni (Akamas CTO) illustrates how some established industry approaches and beliefs about Java Tuning are actually myths: 1) Garbage Collector tuning: do the industry guidelines

Akamas JVM tuning optimization choose the right GC
Make sure to choose the right GC for your application to achieve maximum performance

The Java platform continues to be developed and improved over time. The OpenJDK community has been quite active in improving the performance of the JVM and the garbage collector (GC): new GCs are being developed and existing ones are constantly

AKamas Java tuning short blanket blog
Java application throughput, response time, and cost. Is there a short blanket?

Developers and system owners usually take for granted that there are some intrinsic tradeoffs in the Java design. For example, it is commonly accepted that if you aim at reducing resource usage (e.g. CPU), you must accept some performance degradation.

Beware: improving GC performance may lead to slower applications

One of the most established approaches to improve Java application performance is to tune JVM options, in particular Garbage Collector (GC) parameters.  Indeed, the main task of garbage collection is to free memory up which requires stopping the application threads

Akamas Neotys PAC Hero Java tuning myths
Debunking long-standing Java Tuning myths by leveraging AI Optimization

This presentation by Stefano Doni (Akamas CEO) at Neotys PAC 2021 illustrates how some established industry approaches and beliefs about Java Tuning are simply wrong. By debunking four common JVM tuning myths, some surprising results achieved by adopting AI-based optimization are also

Akamas AI-driven with Micro Focus LoadRunner
AI-driven performance optimization: A real-world example

Modern applications sit atop of many layers, such as Java Virtual Machines, container, database, cloud, and more, each providing hundreds of settings all interacting in complex and counterintuitive ways. Manual and trial-and-error performance tuning cannot cope with this complexity with

Akamas Performance Summit CPU containers
Understanding and measuring CPU throttling in containerized environments

Francesco Fabbrizio, IT Performance Engineer at Moviri, introduces what is throttling and shows how popular open-source and enterprise monitoring solutions address this problem. He also tries to identify new metrics to better understand when throttling is happening. Finally, by the

Akamas Performance Summit Java tuning myths webinar
How AI optimization debunks 4 long-standing Java tuning myths

This presentation by Stefano Doni (Akamas CEO) at Performance Summit 2021 in London illustrates how AI-based optimization provides a more effective approach to Java Tuning that also helps to debunk some common JVM tuning myths based on established industry approaches and beliefs. Key

Akamas Performance Summit 2020 automated performance optimization
From manual performance testing to automated performance optimization

The Akamas team was invited to present our AI-powered performance optimization technology during the London Edition of the Performance Summit, powered by Facebook. Giovanni Gibilisco, Akamas Head of Engineering, demonstrated our novel approach to IT stack tuning: Autonomous Performance Optimization. In this

Case study lastminute Akamas
Faster apps, lower bills: optimizing travel search in the cloud

All online businesses are facing strong challenges in maximizing the throughput of their most critical service during the peak-demand season in a cost-effective way. In less than 2 weeks, Akamas optimized lastminute.com key Java microservice-based application running on Kubernetes, by

Akamas Dynatrace integration Performance clinic
A guide to Autonomous Performance Optimization

In this Performance Clinic episode, Stefano Doni (CTO Akamas) joins Andreas Grabner (DevOps & ACE Activist at Dynatrace). Stefano explains which are the practical steps you need to take to automate optimizations of your enterprise, cloud, or database systems leveraging observability data

Akamas Neoload integration 2020
AI-driven optimization: The key to more performance for lower costs

We had the opportunity to organize a webinar alongside Neotys, our Technological Partners. We wanted to present the integration between our two products, that became available with the Akamas 1.7 update, and what better way to do it than with a webinar?

Akamas Java optimization solution brief
Autonomous Performance Optimization for Java

Many of the world’s mission-critical applications run on Java and, for many years, companies have relied on Java as the platform for enterprise systems. Java is a long-established standard, which offers developers efficiency and stability. Yet, developers and operators are

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