Pepperdata, the Big Data performance company, announced it is expanding its product portfolio with Pepperdata Application Profiler, providing Hadoop and Spark developers with easy to understand recommendations for improving job performance. Application Profiler is currently available in early access and will be generally available in the second quarter of 2017.
Modern distributed systems and applications are more complex than ever, and achieving optimal performance remains one of the most significant challenges of Big Data. “For Big Data, performance can mean the difference between business critical and business useless,” said Ash Munshi, CEO of Pepperdata. “For four years, Pepperdata has been helping Ops Teams with their Big Data infrastructure. Now we are empowering Dev Teams by providing them with clear insight and actionable suggestions on improving Hadoop and Spark job performance.”
Application Profiler is based on the open source Dr. Elephant project originally created by LinkedIn Corporation. Application Profiler and Dr. Elephant help improve Hadoop and Spark developer productivity and increase cluster efficiency by making clear recommendations on how to tune workloads and configurations. Application Profiler delivers the capabilities of Dr. Elephant, but as a simple to adopt SaaS offering, that is very easy to deploy and use. Application Profiler supports Spark and MapReduce on all standard Hadoop distributions: Cloudera, Hortonworks, MapR, IBM and Apache.
“Our close work with LinkedIn and Dr. Elephant represents a new open source focus for Pepperdata,” explained Munshi. “Tighter integration of our products with open source projects provides greater value to our customers and will drive significantly faster innovation and adoption. Not only are we responding swiftly to our customers’ needs, but we are also embracing the larger community through open source.”
Pepperdata to Increase Performance Focus on DevOps for Big Data
Application Profiler is the first of several new products that Pepperdata will be releasing this year that are targeted at DevOps for Big Data. These products will extend our support for developers and operators, building from the experience Pepperdata has gained working with DevOps teams running production clusters.
Pepperdata products and services are designed to accelerate the production use of Big Data applications by ensuring that performance is tightly integrated into the DevOps for Big Data cycle. Along with the introduction of Application Profiler, Pepperdata has organized its current offerings into an integrated suite of products:
Pepperdata Cluster Analyzer:
- Correlate cluster-wide events to users and jobs
- Identify rogue users and applications
- Get accurate chargeback reporting
- Report on capacity trends
Pepperdata Capacity Optimizer:
- Run more jobs on your existing cluster
- Run jobs faster on your existing cluster
- Automatically reclaim wasted resources
- Fully utilize your infrastructure investment
Pepperdata Policy Enforcer:
- Ensure on-time execution of critical jobs to meet Quality of Service commitments
- Support multi-tenancy allowing business-critical workloads and less critical workloads to share the same cluster
- Safely run ad-hoc jobs without impacting critical workloads