Unravel for AWS Databricks: Supporting big data workloads wherever they reside
Unravel Data announced Unravel for AWS Databricks, a solution to deliver comprehensive monitoring, troubleshooting, and application performance management for AWS Databricks environments.
Unravel for AWS Databricks leverages Unravel’s AI-powered data operations platform to accelerate performance of Spark on AWS while providing unprecedented visibility into runtime behavior, resource usage, and cloud costs.
“As business needs evolve, data workloads are moving to a growing variety of settings, stretching across on-prem environments, public clouds, multiple clouds and a hybrid mix of all of these. It’s important that organizations can get the same performance, reliability and value out of their data applications no matter where they are,” said Kunal Agarwal, CEO, Unravel Data.
“Unravel for AWS is our latest effort to expand the platform to accommodate Big Data wherever it exists. With this addition, Unravel now supports Databricks in both AWS and Azure, and the Unravel platform is broadly available in every major public cloud as well as on-premises and in hybrid settings. We were always committed to being infrastructure-agnostic and this is another milestone in that mission.”
The announcement is the latest development in a long relationship between Unravel and AWS. Unravel already supports Amazon EMR, as well as Cloudera/Hortonworks on IaaS for AWS.
This release provides further support for customers deploying modern data apps on AWS. In addition, Unravel is an existing member of the AWS Partner Network and member of AWS global startup program.
AWS Databricks is a unified data analytics platform for accelerating innovation across data science, data engineering, and business analytics, integrated with AWS infrastructure.
Unravel for AWS Databricks helps operationalize Spark apps on the platform: AWS Databricks customers will shorten the cycle of getting Spark applications into production by relying on the visibility, operational intelligence, and data driven insights and recommendations that only Unravel can provide.
Users will enjoy greater productivity by eliminating the time spent on tedious, low value tasks such as log data collection, root cause analysis and application tuning.
Key features of Unravel for AWS Databricks include:
- Application Performance Management for AWS Databricks – Unravel delivers visibility and understanding of Spark applications, clusters, workflows, and the underlying software stack
- Automated root cause analysis of Spark apps – Unravel can automatically identify, diagnose, and remediate Spark jobs and the full Spark stack, achieving simpler and faster resolution of issues for Spark applications on AWS Databricks clusters
- Comprehensive reporting, alerting, and dashboards – AWS Databricks users can now enjoy detailed insights, plain-language recommendations, and a host of new dashboards, alerts, and reporting on chargeback accounting, cluster resource usage, Spark runtime behavior and much more