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Granulate, an Intel Company, announced the upcoming launch of its latest free cost-reduction solution, gMaestro, a continuous workload and pod rightsizing tool for Kubernetes cost optimization.
Granulate's gMaestro provides DevOps, SREs, and FinOps teams full visibility into their K8s clusters allowing them to eliminate over-provisioning and reduce costs by up to 60%.
gMaestro, which can be installed with a single line of code, provides visibility into inefficiencies within Kubernetes clusters. Users can automatically apply HPA, CPU, and Memory request changes that can be employed to save up to 60%. The fully autonomous capability will be generally available next month, enabling all gMaestro users to implement the recommendations with a click of a button.
"Organizations are taking a hard look at their budgets due to the current economic realities and looking for any opportunity to reduce costs," said Asaf Ezra, CEO of Granulate. "Part of our goal at Granulate has been to democratize solutions for the engineering community by making optimizations easy to achieve and even fully autonomous. We are fortunate that as an Intel company we can continue bringing new tools to the market to further that vision."
Granulate's gMaestro provides several benefits for development and software engineers managing orchestration applications:
- Eliminate over-provisioning: Automatic workload rightsizing so you pay only for what you use
- Gain full visibility into your K8s clusters: A simplified, end-to-end overview of K8s objects -- namespaces, deployments, containers, and more.
- Ensure optimal performance: Keep your competitive SLAs while reducing your Kubernetes cost without compromising performance metrics.
- No limitations: Works with HPA and different resource reservation sizes and cluster autoscalers.
gMaestro is CSP agnostic and runs on all of the major CSPs including GCP, Azure, AWS, as well as OpenShift and K8s, and complies with the highest security standards with SOC2, ISO, HIPAA, and GDPR certifications.
gMaestro is set to launch on August 22, 2022.
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