Magalix KubeAdvisor built-in best practices advisors will report best practices that your cluster and workloads are missing.
Quickly balance resources (CPU/Memory) with usage and cost-efficiency.
Apply your own standards with custom advisors. Magalix supports the Open Policy Agent (OPA) framework.
We sequence the automation process to make sure your cluster's stability is not impacted by too many changes at the same time.
Resources optimizations are applied for different reasons, such as performance, utilization, or cost savings. Select your reason and automate optimizations based on your needs!
Magalix has the features you’ll need to accelerate your cloud-native journey. Get in-depth analysis and recommendations to run a secure, reliable, and efficient Kubernetes clusters.
Get top throttled containers and how this impacts your cluster's resources. The Autopilot will recommend what to do next!
Understand how each container contribute to network consumption and how you can improve its I/O performance
Magalix AI builds prediction models of containers CPU consumption. It proactively adjusts allocated cores to make sure containers are performant all the time
Get insights if you have the right amount of resources. Compare what your containers have been consuming to allocate the right amount of cores and memory.
Avoid containers crashes or throttling because you didn't allocate the right amount of resources to it. Avoid over provisioning of your cluster
The whole cluster is scanned hourly to make sure it is ready for any anticipated changes in workloads and resources needs.
Get the best combination of VM (instance) type and size through daily scans. It makes sure you got the cheapest and the most performant VM (instance) type from your cloud provider.
Adjust Node Advisor analysis policies to optimize for density or reliability based on your business needs.
Analyze different billing models from your provider and understand which model makes more sense for your business needs.
Instead of waiting for spikes or over-provisioning your cluster, Magalix autopilot proactively adjusts resources to meet those anticipated workload changes.
Limit the scalability to only slow times. Control when your pods can scale and how frequently.
Instead of containers going into infinite crash loops, Magalix agent will automatically adjust needed resources to safely run the container without any crashes. You will be notified of course!
Set the buffer and when to engage the autopilot inside your cluster for better control.
Bring developers to the full picture with automatic dashboards. Share with them how their namespaces and containers performing and utilizing cluster resources.
Drill down to a single container dashboard and events and share with your team members
"Magalix made it easy for us to understand performance issues in our containers, cluster resources utilization, achieve significant savings"
Support Lead at Medstreaming
"I recently discovered Magalix while browsing the GCP marketplace. It promised an auto-pilot, cost-cutting monitoring agent for our k8s platform. Sounds too good to be true. It is true."
Director of DevOps at Spire Digital
"The value of AI and what Magalix has done is really taking this human judgment and automating it in a way that is more proactive than reactive."
GM at Microsoft Azure