Pepperdata helps companies improve the performance of their Spark workloads running on the HPE Ezmeral Runtime using Kubernetes. With Pepperdata, customers can troubleshoot application performance problems, increase resource utilization, and control costs.

The Pepperdata solution automatically captures and analyzes Spark workload performance metrics, provides tuning recommendations, and optimizes the performance of a Kubernetes cluster.

Product Name

Application Spotlight

Product Version

Supervisor version: 6.5.15

Dashboard version: 2.1.66

HPE Ezmeral Runtime Version


Product Name

Capacity Optimizer

Product Version


HPE Ezmeral Runtime Version


HPE Data Fabric Version



Spark Observability and Autonomous Optimization


Today’s world of accelerated cloud and microservices adoption has increased operational complexity, resulting in ephemeral environments with sometimes unpredictable behavior. Because of constant workload changes, siloed solutions limit visibility and do not work across platforms. Today’s big data environments require observability and automatic optimization to handle the complexity and scale required to meet SLAs and business objectives.

The Pepperdata solution provides the observability and autonomous optimization companies need to get dramatic improvements out of their Spark infrastructure and applications. By automatically tuning workloads, enterprises can go from reactive to proactive. Pepperdata helps organizations:

  • Achieve up to an 80% increase in workload throughput.
  • Get accurate operational insights and job-specific recommendations.
  • Optimize cluster resources automatically in real time without any change to the applications, no matter what the volume or velocity.


Additional Information

Evaluate Pepperdata Application Spotlight with a free trial

Explore the industry’s first enterprise-grade container platform for cloud-native and distributed non-cloud native applications, HPE Ezmeral Runtime

Interested in learning more about the HPE Ezmeral Runtime and Pepperdata? Please contact us to learn more.

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