Constant optimization can exhaust your team and lead to decision fatigue. We eliminate decision fatigue by prioritizing optimizations by their biggest impact on cost or user experience. Don't worry - we still sweat the small stuff too.
Instead of spot analyzing metrics and guessing at the best CPU/memory requests and limits, or estimating the best VM types, use our once-daily 95th percentile of 1-minute resolution as a guideline to set your limits and requests.
Change your limits and requests for any resource without disrupting your cluster or application. KubeOptimizer has the necessary guardrails to apply changes to your containers with failures and rollback scenarios considered.
Get detailed plans that make sure pod CPU/memory allocation is in harmony with allocatable VM capacity. Get maximum value out of your cloud bill.
Allocating the right CPU or memory values has endless possibilities given the complex interactions between containers and available capacity. KubeOptimizer prioritizes recommendations that will make a difference in your cluster's stability, application performance, and cost savings. Apply most impactful optimizations more frequently and in one click!
Changing the allocation of pods CPU/memory requests or limits is not an easy decision, especially for production workloads.
Get a detailed analysis to be confident about any change before applying it. See metrics impacting recommendations, current values, and the suggested values. Learn why a change is required. Understand the impact on your system if not applied. Your team will make the right decisions much faster and with high confidence.
VM optimization is critical to actually realize cost savings or performance improvements across all your applications.
Get detailed VM allocation analysis and recommendations. Your plan considers all pods' CPU and memory allocation and also considers the system's overhead to run with safe margins. Achieve your optimization goals with more peace of mind.
We sequence the automation process to make sure your cluster's stability is not impacted by too many changes at the same time. The Magalix Agent makes sure that a change is successfully executed before it moves to the next fix.
Resource optimizations are applied for different reasons, such as performance, utilization, or cost savings. Select your reason and automate optimizations based on your needs!