Continuous Kubernetes rightsizing engineers can trust
No more manual tuning for CPU and memory requests
Your developers shouldn’t have to guess, and your platform team shouldn’t burn cycles tweaking YAML. Our ML-powered engine analyzes usage patterns every 15 seconds to forecast demand and rightsize resources automatically—adjusting in real-time to daily usage spikes and long-term trends.
Rightsizing that works with your autoscalers
Unlike basic tools that break HPA, our bi-dimensional scaling harmonizes vertical and horizontal pod adjustments. We fine-tune both resource requests and HPA utilization targets—cutting overprovisioning while avoiding CPU throttling, latency issues, or OOMKills.
The only rightsizer that understands Java
Standard rightsizing tools miss the mark with Java. We go deeper—optimizing JVM heap sizes and container memory limits in tandem, so your memory footprint shrinks without triggering GC storms or container crashes.
Built to optimize thousands of workloads, automatically
Deployed across some of the largest Kubernetes estates in the world. We auto-discover every pod, learn its patterns in days, and apply optimization recommendations within policy-defined guardrails. Integrates directly into your GitOps pipelines—no rewrites required.
Feature highlights
ML-forecasting
Bi-dimensional scaling (patent pending)
JVM optimization
Policy automation
GitOps integration
Enterprise visibility
Why platform engineers choose CloudBolt
90% faster time-to-savings
From months to hours, for immediate cost reductions.
Reduced manual work
Eliminate repetitive, unsustainable resource tuning
40-60% Kubernetes savings
Right-size workloads and reduce your node footprint.
99% allocation accuracy
Maximize node efficiency and avoid wasted spend.
What our customers say
StormForge has added immediate gains by overall net-capacity savings due to overprovisioned workloads.
StormForge was easy for me to get up and running quickly, and we achieved immediate efficiencies that reduced our cloud costs and lowered the amount of toil we had from manually configuring requests.
The machine learning that StormForge leverages to set requests and limits on pods allows our engineering and SRE teams to focus on our customer experience rather than infrastructure settings.
Ready to put Kubernetes rightsizing on autopilot?
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