HomeOperationsHow StormForge brings deeper visibility into Kubernetes

How StormForge brings deeper visibility into Kubernetes

Of late, Kubernetes has gained popularity in DevOps teams given its ease when deploying and managing cloud-native applications. It is flexible, portable, and has features like multi-cloud capability in its arsenal which can prove to be highly productive. Given these benefits, Kubernetes is being rapidly deployed across enterprises which has uncovered various unforeseen complexities that come with the aggravating explosive adoption it has witnessed.

Keeping all the benefits and flexibility offered to the business aside, practically, Kubernetes can be quite complex, and this can lead to inefficient configuration, resulting in tens of thousands of dollars wasted on lost productivity, availability issues, and unused cloud resources. According to a recent survey published by the Cloud Native Computing Foundation (CNCF), 68% of respondents claimed their Kubernetes-related costs have increased, with their bills spiking by more than 20% for half of them. Is there a solution to the cost challenges Kubernetes users face today?

Watch also this interview: You’re probably overspending by up to 80% on Kubernetes

The StormForge Platform

The StormForge platform is a one-stop Kubernetes performance testing and optimization solution. It utilizes the fact that businesses can often greatly reduce their spending simply by being more effective in monitoring their Kubernetes costs, predicting them, and installing methods to curtail overspending. Using machine learning, StormForge optimizes Kubernetes environments that in turn help reduce cloud costs and improve application performance. This makes it one of the most elegantly efficient solutions for automating Kubernetes resource management at scale. This allows developers to focus on innovating and not on fixing Kubernetes errors.

Kubernetes Performance Testing as a Service

StormForge can be integrated into your DevOps workflow thus allowing you to load test your applications for both availability and performance at scale. You can create these tests within a few minutes and scale them to simulate millions of users and hundreds of thousands of requests every second. In fact, you can run a bench test with real production traffic to reflect expected traffic patterns.

Key benefits

StormForge shifts performance testing to the left of the software delivery pipeline. This ensures that by the time of the release, your product is both reliable and performant. Here are some of its key benefits:

  • It guarantees high-performance execution by automating load tests into your CI/CD process.
  • It tests with real-world parameters to ensure every deployment is successful when released into production.
  • It mitigates any issues that can impact your business or your SLAs.

Key features

  • Reporting and analytics: StormForge’s extensive analytics help benchmark, interpret, and compare results.
  • Open workload model: The open workload model accurately simulates real-world scenarios and detects problems better than closed workload tools.
  • Test run comparability: StormForge aims to offer you comparability between different test case runs and help identify trends and performance issues if any.

Deep application analysis

StormForge relies on non-production scenario planning as well as quick experimentation to deliver in-depth application insights. It is only by analyzing the application’s behaviours under a wide spectrum of conditions can you accurately pinpoint developments to your cloud-native architecture and allocate resources accordingly. More than that, it helps determine how the application will behave in production under stress.

It embraces machine learning

StormForge is now treading beyond scenario analysis in non-production environments to help users take actions based on the observability data through Optimize Live. Aimed at bridging the data-to-value gap, Optimize Live makes use of the data you collect and applies machine learning to make your Kubernetes production environment more efficient while reducing resource slack.

With observability data at the helm, StormForge’s Optimize Live uses machine learning to discover opportunities where you can reduce the usage of cloud resources without running the risk of out-of-memory errors or CPU throttling. Its patent-pending ML model can altogether eliminate numerous time-consuming manual application tuning processes and recommend configuration changes in real time. This model can analyze a range of application parameters to support many business goals, performance and costs most of all.

Optimize Live also has other features on top of machine learning. These include:

  • Configurable policies for increased flexibility and automation.
  • Better recommendations than what’s provided by VPA since the data used is specific to the user.
  • Compatibility with other user management platforms, RBAC, SSO, release automation, etc.


StormForge offers compatibility with a range of platforms including AWS, Datadog, and Prometheus. Very soon it will also support observability tools like Dynatrace as well.


StormForge is an Amazon Web Services Independent Software Vendor (ISV) and this program allows it to provide software solutions that can be integrated with AWS. StormForge Optimize itself is built on AWS services and is available to customers via AWS Marketplace and can further improve the efficiency of your AWS EKS-based applications to reduce cloud costs.


StormForge can be integrated with Datadog — the world’s leading monitoring service for cloud-based applications — to deliver an ultimate solution that helps organizations better understand their complex multi-cloud environments. StormForge helps Datadog customers ensure smarter business trade-offs and efficiency in operations. Optimize Pro from StormForge can be integrated with the Datadog platform to query metrics on top of the promised efficiency.


Prometheus is another leading monitoring tool used for event monitoring and alerting. It records metrics in real-time and stores them in a time series database developed over an HTTP pull model. StormForge collects these metrics following the completion of a trial run job which can be used along with numerous additional template functions.

Final thoughts

StormForge is the leading solution provider for Kubernetes optimization and overall increased operational efficiency. It analyses applications under simulated production conditions and uses a patent-pending machine learning model to treat every customer use case uniquely. Try StormForge to keep your cloud-native costs in check.

If you have questions related to this topic, feel free to book a meeting with one of our solutions experts, mail to sales@amazic.com.


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