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Kubernetes cost optimization made easy with gMaestro

Written by Granulate

Kubernetes have played a key role in managing containerized environments and reducing development times, yet cost and resource management remain challenging. 

The costs of over-provisioning and mismanaged, idle, and even forgotten resources have become a significant financial burden for companies globally.

But they shouldn’t be.

At Granulate, we believe optimization of cost and performance should be easy to achieve, and even fully autonomous.

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That’s why we are proud to announce the coming launch of our newest free cost-reduction solution, gMaestro: an autonomous, continuous workload and pod rightsizing tool for Kubernetes cost optimization. 

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% with a click of a button.

”gMaestro enabled us to immediately and easily achieve over 25% cost reduction in our Kubernetes clusters”

Vivek Kumar, Technical Lead at ShareChat

gMaestro can be installed with a single line of code, providing 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%. 

To ensure we give our future users the best experience and results, we’ve worked with several of our enterprise customers, including ShareChat, India’s largest social networking service with over 250 million monthly active users. “gMaestro enabled us to immediately and easily achieve over 25% cost reduction in our Kubernetes clusters,” says Vivek Kumar, Technical Lead at ShareChat.

gMaestro provides several unique benefits for companies managing orchestration applications:

  1. Eliminate over-provisioning: Automatic rightsizing for workloads so you pay only for what you use
  2. Gain full visibility into your K8s clusters: A simplified, end-to-end overview of K8s objects — namespaces, deployments, containers, and more
  3. Ensure optimal performance: Keep your competitive SLAs while reducing your Kubernetes cost without compromising performance metrics
  4. No limitations: Works with HPA and different resource reservation sizes and cluster autoscalers
Autonomous, continuous workload and pod rightsizing by gMaestro

gMaestro is CSP agnostic and runs on GCP, Azure, AWS, as well as OpenShift and K8s. The tool also complies with the highest security standards with SOC2, ISO, HIPAA, GDPR certifications.

Be the first to experience gMaestro. Register for our free beta version here and join our Slack community with fellow gMaestros like yourself. 

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