SL Announces Monitoring as a Service for Apache Kafka
RTView Cloud for Middleware Monitoring is now generally availablePress Releases, RTView, SL in the News
July 10, 2018 – Corte Madera, CA – SL is now offering Apache Kafka Monitoring as a Service with initial availability for Kafka Monitoring with RTView Cloud.
RTView Cloud provides users with a way to proactively monitor their complex Kafka environments to maximize uptime and reduce the time required to address incidents. The solution consists of pre-built dashboards for monitoring Kafka brokers, producers, consumers, topics and zookeepers. With dozens of pre-defined alerts and pre-built monitoring displays, users can quickly deploy a powerful monitoring solution without the time, skill and expense necessary to build or configure their own monitoring applications.
The new RTView Cloud designer provides additional capability for users to create custom monitoring displays from a browser and without the need to do any custom programming. This enables middleware support teams to offer custom displays to their end users that provide them with the exact metrics they need in the exact way they would like to see them.
Data security with RTView Cloud is enhanced through the use of a hybrid architecture which ensures all monitoring data stays securely behind the firewall. Performance metrics and alert data are accessed directly from users’ browsers and never pushed out to the Cloud.
“Apache Kafka is being adopted by many of our integration customers,” said Tom Lubinski, CEO of SL. “We are excited to announce support for monitoring Kafka as a service and believe this will appeal to many of our customers because of the ease of implementation.”
SL is a San Francisco Bay Area-based software company that develops real-time monitoring, visualization and diagnostic software for Global 1000 and mid-market companies whose businesses depend on complex, high-performance applications. The company has deep expertise in monitoring and management of custom, distributed applications running in heterogeneous middleware environments.