Kubernetes is increasingly being used with big data deployments. This trend is driving more big data apps to move to GCP, which offers homegrown support for Kubernetes. To make these workloads simpler and cheaper, there’s a need for a new solution for managing data workloads on Google Cloud Dataproc. With GCP’s CAGR estimated to grow by 64% CAGR through 2021, the cloud is now clearly a three-horse race.
Enter Unravel Data, the data operations platform providing full-stack visibility and AI-powered recommendations to drive more reliable performance in modern data applications, and the company’s introduction of a performance management solution for the Google Cloud Dataproc platform that makes data workloads running on the top of the platform simpler to use and cheaper to run.
Unravel for Cloud Dataproc improves the productivity of data teams with a simple and intelligent self-service performance management capability, helping DataOps teams:
- Optimize data pipeline performance and ensure application SLAs are
- Monitor and automatically fix slow, inefficient and failing Spark,
Hive, HBase and Kafka workloads
- Maximize cost savings by containing resource-hogging users or applications
- Get a detailed chargeback view to understand which users or
departments are utilizing the system resources
For enterprises powered by modern data applications that rely on distributed data systems, this class of platform accelerates new cloud workload adoption by operationalizing a reliable data infrastructure, and it ensures enforceable SLAs and lower compute and I/O costs, while drastically lowering storage costs. Furthermore, it reduces operational overhead through rapid mean time to identification (MTTI) and mean time to resolution (MTTR), enabled by unified observability and AIOps capabilities.
“Unravel simplifies the management of data apps wherever they reside – on-premises, in a public cloud, or in a hybrid mix of the two. Extending our platform to Google Cloud Dataproc marks another milestone on our roadmap to radically simplify data operations and accelerate cloud adoption,” said Kunal Agarwal, CEO, Unravel Data. “As enterprises plan and execute their migrations to the cloud, Unravel enables operations and app development teams to improve the performance and reduce the risks commonly associated with these migrations.”
In addition to DataOps
optimization, Unravel provides a cloud migration assessment offering to help
organizations move data workloads to Google Cloud faster and with lower cost.
Unravel has built a goal-driven and adaptive solution that uniquely provides
comprehensive details of the source environment and applications running on it,
identifies workloads suitable for the cloud and determines the optimal cloud
topology based on business strategy, and then computes the anticipated hourly
costs. The assessment also provides actionable recommendations to improve
application performance and enables cloud capacity planning and chargeback
reporting, as well as other critical insights.
“We’re seeing an increased adoption of GCP services for cloud-native workloads as well as on-premises workloads that are targets for cloud migration. Unravel’s full-stack DataOps platform can simplify and speed up the migration of data-centric workloads to GCP giving customers peace of mind by minimizing downtime and lowering risk,” said Mike Leone, Senior Analyst, Enterprise Strategy Group. “Unravel adds operational and business value by delivering actionable recommendations for Dataproc customers. Additionally, the platform can troubleshoot and mitigate migration and operational issues to boost savings and performance for Cloud Dataproc workloads.”
Contributed by Daniel D. Gutierrez, Managing Editor and Resident
Data Scientist for insideBIGDATA. In addition to being a tech
journalist, Daniel also is a consultant in data scientist, author,
educator and sits on a number of advisory boards for various start-up
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