CUSTOMER CASE STUDY

Why An AI Platform With 1M Daily Active Users Called For Container Optimization?

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What you can expect in this 10-page report...

When a leading AI platform began its journey in simplifying it's cloud infrastructure, it was up against the challenge of container management. While using Kubernetes was one of the rewarding decisions, the company made. However with such a large & complex infrastructure, it’s effective utilization & scaling in a cost efficient way was complex.

This case study explains these challenges faced by the AI Platform in dealing with Container Orchestration Services and how Opslyft helped them save $ 1M annually in cloud costs.

OpsLyft empowered the team to: 

Connect with existing tools and infrastructure—from data lakes and warehouses to Prometius and Grafana.

Rightsize the resources for every pod, keeping the application-level metrics in check, overall reducing cost by 23%.

Automatically downscale Infrastructure in non-business hours, saving cost by 15%

Monitor data processes, pipelines and workflows with the help of automated alerts and warnings.

Automate and schedule repetitive workflows to reduce human grunt work and prevent errors.

Reduce average monthly bill of the Kubernetes cluster by 56%

Hear it from the guardians of cloud themselves

There’s no doubt that Kubernetes has benefited us by simplifying the deployment & management complexities of our docker based microservices. But the cost of running the k8s clusters is still a high portion of our monthly bill. What we really need is a strategy through which we can reduce our k8s costs without compromising upon platform stability & performance

Tech Lead
DevOps & Infrastructure

Manages financial reporting and Infrastructure for the entire business, including ensuring transparency in audits and approving expenses.