ManageEngine announced that Applications Manager, its application performance monitoring solution, now supports performance monitoring for Apache Spark.
The move enables development and operations teams in enterprises to gain visibility into the performance of the big data engine as well as the business-critical applications relying on Spark.
Apache Spark is an open source analytics engine built on top of the Hadoop Distributed File System (HDFS). Spark is steadily gaining prominence for its fast data processing capabilities and is being used for data streaming, fog computing, machine learning, and interactive analysis. It is one of the four widely used technologies in the Hadoop ecosystem. However, many components come together to make a Spark application work, so it presents unique complexities in monitoring and troubleshooting.
"Consumer-centric businesses are rapidly deploying data processing engines, such as Spark, to convert tons of data into quick business decisions. As these businesses scale their Spark deployments, it becomes more challenging for operations teams and data scientists to comprehend what is going on,” said Dev Anand, Director of Product Management at ManageEngine. “We want to uncomplicate performance monitoring for big data technologies so businesses can get the most out of their big data projects. That’s why we added performance monitoring and troubleshooting for Apache Spark in Applications Manager. Now, businesses can be more confident about deploying Spark and other big data applications in their production environments."
Proactive Monitoring and Troubleshooting for Apache Spark Clusters
Applications Manager enables comprehensive performance monitoring of the Apache Spark in-memory analytics engine to minimize downtime and performance degradation as well as take corrective actions before any problems arise. Applications Manager monitors key performance indicators of Apache Spark, including indicators related to drivers, executors, RDD blocks, tasks, job stages, CPU and memory usage, and JVM metrics.
The latest monitoring capabilities in Applications Manager help IT personnel:
- View a holistic picture of the health and performance of Apache Spark clusters, big data applications that rely on Spark, and associated infrastructure components using customer, interactive dashboards.
- Diagnose common causes of performance failures in the Spark infrastructure, drill down to their root cause and resolve them quickly before the failure propagates through the Spark infrastructure to the application.
- Gain insights into the overall cluster utilization and resource bottlenecks as well as plan capacity effectively to handle the increasing size and complexity of Spark workloads.
- Ensure Spark applications are consistently delivering a high-quality experience for end users.
Support for Apache Spark complements Applications Manager’s existing monitoring support for the Hadoop platform and key components of the Hadoop ecosystem, such as Apache HBase, Elasticsearch, ZooKeeper, Kafka and Solr search engine. Applications Manager also provides out-of-the-box support for more than 80 applications and infrastructure components, including other NoSQL and in-memory technologies such as Cassandra, MongoDB, Redis, Memcached, Couchbase, Oracle NoSQL, Oracle Coherence and SAP HANA.
Applications Manager 13.2 is available immediately.
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