Introducing automatic resource scanning and guided optimization in the latest StormForge release

When we launched the StormForge platform last year, our mission was to transform containerized application optimization from a time-consuming manual, reactive function to an automatic, proactive, and continuous approach to improving cloud performance and cost efficiency.

The initial release was a big step forward from manual, trial-and-error tuning approaches, but it still required some in-depth Kubernetes expertise to identify which parameters could be tuned and to manually build YAML-based optimization experiments.

But our belief is that running Kubernetes applications efficiently shouldn’t require you to be a Kubernetes guru. So, we’re happy to announce that our latest release takes ease of use to a whole new level, significantly reducing the time and expertise required to optimize containerized applications.

New features being introduced today include automatic scanning of application resources and guided walkthroughs for optimizing applications quickly and easily. The result? Faster cloud-native development and deployments, regardless of the level of in-house expertise.

In-cluster resource scanning

Prior to this release, optimizing application resources with StormForge meant users had to write YAML files that required advanced knowledge of Kubernetes. This was time consuming even with k8s expertise.

With this release, StormForge can now scan your cluster resources. StormForge will identify all of the tunable parameters (e.g. CPU, Memory and Replicas) within your application. The user can specify which resources they want to optimize by selecting from the namespaces found and then filtering using label selectors. The scanning functionality also detects the current values for these parameters to be used as your baseline, and automatically sets a range for the machine learning to test between.

Scanning also allows us to generate the necessary patches that will allow the StormForge controller to update the application with the parameters the machine learning has chosen for each trial during the optimization lifecycle.

Automatic resource scanning means you can achieve optimal efficiency for your application, even if you’re not a Kubernetes expert and lack in-depth knowledge of your application’s parameters.

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Guided optimization walk-through

Identifying parameters that can be tuned is a key part of optimizing an application, but you also need to identify which test case to use and define your optimization objectives. With this release, we’re introducing a step-by-step, guided walkthrough to make it easy and fast for users to optimize their applications.

StormForge walks you step-by-step through the process of optimizing your app

The guided walkthrough, currently accessible via the latest StormForge command line interface (CLI), takes users through the following steps to fully build and execute an optimization experiment:

  1. Select a StormForge test case. When using a StormForge performance test, all you need is to download and authenticate the Forge CLI. Once this is installed the `redskyctl run` command will automatically detect all of your load tests. Simply select the one you want to use for optimizing your application.
  2. Select the Kubernetes namespace. Identify which namespaces your application resources are in. You may select multiple namespaces. 
  3. Optionally, select specific application resources to be optimized. Use label selectors to first filter down which resources to scan for within your selected namespaces. By default we will scan all deployments and stateful sets in the namespaces selected. Next, you can further filter down where to discover CPU, memory and replicas.
  4. Select optimization objectives. This allows you to choose from a common set of metrics for optimization, including cost and p50, p95, and p99 latency.
  5. Run the optimization. At this point, you can immediately kick off the optimization process, or you can exit and run your optimization at a later time. 

While the guided optimization walkthrough makes it easy to quickly create experiments, we still give users complete flexibility to customize the optimization settings by directly editing the manifest that was automatically created during this process. You can also continue to use the app.yaml format to optimize for advanced use cases such as using your own load test or metrics.

New UI for improved ease of use and faster innovation

Lastly, we have completely revamped the StormForge user interface to deliver a better and more consistent user experience, improved ease of use, faster time to value, and greater accessibility. The new UI also establishes a design system framework that provides a foundation for faster innovation and scale moving forward, so expect more great things to come soon.

StormForge Director of Product Design, Josh King, explains the significance of the new StormForge UI

Try it today

The latest version of StormForge Optimization including these new capabilities is available now. Request a demo of StormForge to see for yourself.