Case Study: Palo Alto Networks reduces cloud costs and improves availability with Sedai

Palo Alto Networks saves $3.5M and cuts Kubernetes costs 46% with Sedai

Palo Alto Networks, a global cybersecurity leader, faced the immense challenge of managing and optimizing its highly complex, multi-cloud environment for its Prisma SASE service. The company needed to ensure near-perfect availability (99.999%) while simultaneously reducing its significant cloud costs and freeing its engineers from overwhelming manual toil. To address this, they partnered with Sedai, an autonomous cloud management platform.

Sedai implemented its platform, which uses deep reinforcement learning to understand Palo Alto Networks' entire cloud architecture. After a period of building trust through recommendations, Sedai began taking autonomous actions in Autopilot mode to optimize costs, performance, and availability. The solution delivered by Sedai resulted in staggering savings of $3.5 million in cloud spend, a 46% reduction in Kubernetes costs, and empowered engineers to focus on higher-value work while maintaining their critical availability standards.

Palo Alto Networks