Pepperdata | Careers [best]

Most engineers know the pain of the "noisy neighbor"—that one runaway query that starves the other 99 applications on the same cluster. Pepperdata doesn’t just monitor this; it autonomously fixes it in real-time. They built the industry’s first platform for workload-aware auto-scaling and capacity optimization for Kubernetes, Hadoop, and Spark.

Within six months, Maya reduced the e-commerce giant’s annual cloud bill by $2.3 million. She didn’t write a single line of application code. She simply turned on Pepperdata’s "demand-based scaling" feature. pepperdata careers

In the sprawling data centers of a global e-commerce giant, a senior site reliability engineer named Maya stared at a wall of red alerts. It was 3:00 AM on Cyber Monday. The company’s Hadoop cluster—the engine that powered their real-time inventory and recommendation engine—was thrashing. CPUs were maxed out, memory was leaking, and jobs were failing. Most engineers know the pain of the "noisy

Her manager’s feedback? “You didn’t just save money. You saved the team’s weekends.” Within six months, Maya reduced the e-commerce giant’s

The solution, traditionally, was brutalist engineering: Throw more servers at it. But leadership had cut the cloud budget. Maya couldn’t add nodes; she had to optimize.