Unravel Optimize Webinar Series | Accelerate Amazon EMR for Spark & More!

Logo
Presented by

Chris Santiago, Director of Solutions Engineering, Unravel Data

About this talk

Amazon EMR is growing in popularity, and is emerging as the leading platform for big data processing on AWS. EMR is the preferred platform for “lift and shift” migration of existing Hadoop and Spark workloads to the cloud, with minimal refactoring. You get better control, enhanced flexibility, and greater responsiveness. Would your organization benefit from rapid troubleshooting and performance optimization for your Amazon EMR workloads? If you’re running significant workloads on Amazon EMR then you may be looking for ways to get faster performance, and meet SLAs, without excessive resource use and cost. You will want to find the equivalents to the approaches you used on-premises, plus cloud-specific ways to get the job(s) done, faster. Join Chris Santiago, Director of Solutions Engineering at Unravel Data, on August 19th to see how Unravel can deliver: - AI-powered recommendations and automated actions to enable intelligent optimization of your big data pipelines and applications. - End-to-end monitoring, measurement, and troubleshooting of apps using Spark, Hadoop, Kafka, and related technologies. - Detailed insights, plain language recommendations, and auto-tuning of apps to make the most of your Amazon EMR environment. Don’t wait. Register today for this informative and actionable webinar.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (51)
Subscribers (5811)
At Unravel, we see an urgent need to help every business understand and optimize the performance of their applications, while managing data operations with greater insight, intelligence, and automation. For these businesses, Unravel is the AI-powered data operations company. We offer novel solutions that leverage AI, machine learning, and advanced analytics to help you fully operationalize the way you drive predictable performance in your modern data applications and pipelines.