Case Study: ShareChat saves millions and cuts engineering effort with Cast AI

ShareChat saves millions and reduces engineer effort with automation

ShareChat, India’s largest homegrown social media company and a major Google Cloud Platform customer, runs more than 90% of its infrastructure on Kubernetes and handles nearly 7 billion web requests a day. To manage this scale more efficiently, ShareChat turned to CAST AI to help optimize its Kubernetes deployment, improve autoscaling, and reduce resource waste.

With CAST AI’s rebalancing, flexible node pool provisioning, and automation for Committed Use Discount utilization, ShareChat replaced inefficient nodes, improved workload distribution, and dynamically adjusted capacity in real time. The results were significant: cloud waste dropped, commitment utilization rose to nearly 98%, capacity planning effort fell from twice weekly to once every two months, and the team eliminated at least 10 node pool-related support tickets per week while saving more than a million annually in expected cloud costs.

ShareChat

Jenson C S

Senior Engineering Manager