Akamas 1.8 Is Here!

15 Jul

We are pleased to announce the release of Akamas 1.8! This version is packed with several highly-requested features:

Oracle Optimization: We now officially support out-of-the-box optimization for Oracle, the leading database in the market. Enterprise customers can now ensure that their Oracle-based applications run at top speed and that the database itself is right-sized to minimize infrastructure and licensing costs.
LoadRunner: Akamas now natively integrates with LoadRunner, the flagship load testing solution from Micro Focus. LoadRunner users can now easily integrate Akamas in their existing environments and deploy AI-driven performance optimization.
Improvements: This release includes enhancements to several Optimization Packs such as Linux, MongoDB, and MySQL, as well as some new usability features and several bug fixes

Oracle Optimization Pack

Optimizing databases to reduce query execution time and support increasing workload demands, while keeping license and infrastructure costs under control, has always been a top challenge for IT departments.

For decades, performance engineers and DBAs have focused on optimizing SQL statements. But the problem might lie in the database tuning instead. With 300+ configuration settings, properly optimizing an Oracle database for a given business goal (e.g. increase payments per second) is unthinkable with today’s manual tuning approaches.

Fear not. Akamas latest release includes support for Oracle database versions 18c/12c/11g, running both on premises and on AWS RDS managed cloud services. The new optimization pack covers 100+ database configuration parameters, plus purpose-built workflow operators that allow you to easily automate the database settings’ configuration.

The wait is over. Discover what AI-driven optimization can do for your Oracle databases!

LoadRunner Integration

For decades, LoadRunner has been a market-leading performance testing tool and is still very popular in the enterprise. We heard loud and clear that our customers wanted a native Akamas integration with LoadRunner, and we listened!

With today’s release, if you are using LoadRunner for your performance testing needs, you can now easily integrate Akamas and leverage the power of AI to automate performance tuning of your applications – all without changing a single line of your test scripts.

The native integration provides a LoadRunner operator to automatically launch your preferred load test scenarios, and a LoadRunner telemetry provider to import results (transactions throughput and response times) from LoadRunner Controller directly into Akamas.

Take advantage of advanced features like end-to-end load test automation, goal-driven scoring, tracking, and experiments results and configurations analysis. Just relax, go for a swim, and let Akamas do the hard work for you.

Optimization Packs Improvements

The latest Akamas release goes all-in on database technology. In addition to launching the Oracle optimization pack, we have also enhanced the MySQL and MongoDB optimization packs. We have added several key parameters and extended Prometheus telemetry to gather database metrics out-of-the-box with zero configuration. You have no more excuses for slow queries and expensive databases!

We have also improved our Linux optimization pack by adding support for Ubuntu 20.04, Centos 8, and RedHat Enterprise Linux 8. This update allows the optimization of several new performance-impacting tunables for storage and memory management that were introduced in the latest Linux kernels. You can now optimize any application running on these Linux distributions with the Akamas native configuration operator.

Usability Improvements

Akamas usability is a core focus for us. We love to receive your feedback and add new features that make your life easier!

Constraints relative to the baseline

A unique feature of Akamas is its goal-driven design. Not only can you optimize your business metrics, such as transactions or costs, but you can also set constraints like “don’t slow the application down”: Akamas AI takes them into account, delivering a truly hands-off and reliable optimization experience.

In previous versions, goal constraints could only be expressed using absolute values. This version adds support for baseline-relative constraints, so that you can now simply state, for example, “I don’t want my app to be slower than 20%”. Of course, you can define constraints on any load testing metrics and any metric produced by Akamas-connected telemetry providers like Dynatrace and Prometheus.

Updating Akamas resources from the UI

Sometimes, Akamas users can make mistakes in writing an IP address or copying a file path in an Akamas YAML file. To make it easier to fix small but tedious errors, we have added the ability to edit your systems and workflows directly from the Akamas UI. No need to switch back to the CLI once you have created your study. Just fix that IP address and launch it directly from your browser!

Read our FAQ to discover more about Autonomous Performance Optimization, how it works, and how long does it take for an optimization.

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