Pepperdata Introduces New Kafka Monitoring Capabilities for Mission-Critical Streaming Applications

Pepperdata Introduces Observability and Optimization for Spark On Kubernetes

Observability and Alerting for Streaming Data Applications in the Big Data Stack

Pepperdata, the leader in Analytics Stack Performance (ASP), announced the availability of Streaming Spotlight, a new product in Pepperdata’s data analytics performance suite. The suite is purpose-built for IT operations teams, giving them a single, comprehensive view of their analytics stack, both in the cloud and on premises. With Streaming Spotlight, existing customers can integrate Kafka monitoring metrics into the Pepperdata dashboard, adding detailed visibility into Kafka cluster metrics, broker health, topics and partitions.

Kafka is a distributed event streaming platform and acts as the central hub for an integrated set of messaging systems. Kafka’s architecture of brokers, topics and data replication supports high availability, high-throughput and publish-subscribe environments. For some users, Kafka handles trillions of messages per day. Managing these data pipelines and systems is complex and requires deep insight to ensure these systems run at optimal efficiency.

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Gartner confirms organizations are shifting from traditional processing on databases and batch to a streaming-first approach. Organizations moving to streaming architectures are quickly adopting Kafka for microservices communication, leading to an increased need to monitor Kafka’s overall performance.

To make Kafka monitoring simpler, Pepperdata’s Streaming Spotlight provides visibility into brokers and topics, and enables users to quickly resolve any issues by correlating host metrics. Pepperdata customers report the ability to track the right metrics, and then integrate those metrics as part of their overall big data analytics stack, is integral to their ongoing IT operations success.

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Pepperdata Kafka monitoring benefits include:

  • Automatically detect and alert on atypical Kafka behavior to prevent data loss
  • Ensures preservation of SLAs for real-time stream processing applications
  • Forecast Kafka data streaming capacity needed to protect throughput performance
  • Correlate infrastructure and application metrics across Kafka, Spark, Hive, Impala, HBase and more

“With this new functionality, IT teams have the visibility needed to run their streaming applications as efficiently as possible. The ability to be alerted to faults, and then pinpoint those issues in near real time for remediation is no longer a luxury in mission-critical environments,” said Ash Munshi, CEO, Pepperdata. “We’re providing an elegant solution for observability and monitoring as Kafka is becoming the de-facto standard for streaming applications.”

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