Additionally, we organize your application logs - driver, Kubernetes and executor - as well as maintain the Spark history server so you can always access the Spark UI. We recognize that Spark development and debugging can be challenging, and we’re here to help! With our resource utilization tools, you can understand exactly how your Spark application is performing, identify which resource (I/O, memory, CPU, garbage collection) is affecting application execution and resolve the bottleneck more efficiently. Gain insight into Spark application performance This flexibility can improve application duration and reduce spot kills by up to 79%. Leveraging Ocean’s intelligent spot instance selection, Ocean for Apache Spark removes the need to pair applications with specific instance types, allowing Ocean to choose at runtime the spot instance type that has the highest availability, lowest price, and lowest likelihood of a spot kill. Why Ocean for Apache Spark? Lower application costs, while improving reliability, availability You can also choose from one of our many terraform modules to find the deployment that matches your cloud provider and cluster configuration. Visit the Clusters tab in Ocean for Apache Spark, and you will be prompted to choose the Ocean cluster to import. You can even deploy directly into your existing Ocean cluster. Spot by NetApp users can now easily begin their migration to Ocean for Apache Spark. (Here you can find the complete guide to get started.)
Today, we’re excited to announce that Ocean for Apache Spark is now available to all customers within the Spot console. As the leading managed platform for Spark on Kubernetes, we’ve helped several customers make the decision to move their Spark workloads to Ocean for Apache Spark, taking advantage of strategic spot instance selection, flexible pod configurations, and resource utilization tools that can correct overprovisioning. As the size and frequency of data pipelines scale, organizations are constantly looking for ways to reduce costs and more efficiently utilize their data infrastructure.
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