StormForge Application Performance Optimization Demo

Cloud and Kubernetes complexity makes it almost impossible for enterprises to deliver the performance and stability that users expect, and to do it in a cost-efficient and time-efficient way.

DevOps teams struggle with the trade-off between cost and performance, relying on a resource-intensive, trial-and-error approach to application resource management and tuning. And even with all that effort, the result is costly over-provisioning, unacceptable user experience, and developer burnout.

StormForge puts an end to all that.

StormForge uses machine learning to improve the performance and availability of your containerized applications while significantly lowering cloud costs.

StormForge provides optimal performance and resource efficiency automatically, without the need for manual configuration, reactive trial and error, or resource-intensive tuning.

It starts with performance testing. Using StormForge performance testing, you can understand how your application will perform under production load. You can measure your application health using the apdex score, error rate, and the range of latency. You can also get a detailed second-by-second analysis of metrics, such as 99th percentile latency and CPU utilization.

This serves as our baseline for optimization.

StormForge Optimization works through a process of rapid experimentation.

An experiment consists of multiple trials, each running your previously created load test. As the experiment progresses, our machine learning homes in on the best set of parameters, such as memory and CPU requests and limits, among the billions of possible combinations, to optimize for performance, cost, and any other metric you specify.

Creating an experiment is easy, and fully automatic. Choose your load test, select the namespace where your application is running, and then StormForge scans your cluster to understand what resources can be tuned. We then guide you step by step through the process of creating and running your experiment.

When the experiment finishes, you can see that the StormForge machine learning engine has provided a set of optimal application configurations. From that set, we show you a recommended solution that best balances your optimization goals. No more guessing at the right application settings.

For your recommended trial, we can see the improvement compared to the baseline for the metrics that you care about. Think about what that would mean in terms of real cloud costs and improvements to your user experience, not to mention the time you can save compared to a trial and error approach.

StormForge lets you explore and analyze all the tested solutions on a simple chart with the most optimal solutions highlighted. While StormForge recommends solutions, the power is always in your hands to choose. With a single click, you can export the manifest for your chosen configuration, making it easy to release your applications knowing with confidence exactly how they will behave.

StormForge establishes a foundation for Kubernetes success. The combination of cloud-native performance testing and machine-learning powered optimization allows you to dramatically improve performance, stability, and cost-efficiency of your Kubernetes apps. StormForge automates resource efficiency, letting you focus on innovating, not configuring and tuning your environment.

StormForge is your foundation for Kubernetes success. Try it for yourself and start optimizing today.