Datadog announced the general availability of Data Streams Monitoring, which makes it simple for organizations to track and manage the performance of applications that rely on messaging systems like RabbitMQ.
Data Streams Monitoring automatically visualizes all interdependencies and key health metrics across all streaming data pipelines to help organizations prevent and troubleshoot latency and downtime.
As part of Datadog's APM platform, Datadog Data Streams Monitoring automatically visualizes interdependencies and key health metrics across all streaming data pipelines. With Data Streams Monitoring, engineers can measure latency between any two points across an entire streaming data pipeline, locate faulty queues or services and mitigate floods of backed-up messages so they can avoid critical downtime.
"There is a gap in visibility between SREs and application developers today, which limits their understanding of how queues are impacting mission-critical services and end-to-end latency of high-value user experiences like the resolution of banking transactions, the generation of shopping recommendations or payment processing," said Omri Sass, Group Product Manager at Datadog. "While existing solutions can only observe individual queues and services, Data Streams Monitoring provides visibility into an organization's entire ecosystem to make troubleshooting quicker and easier."
Data Streams Monitoring is now generally available for Kafka and RabbitMQ, with support for more technologies coming soon.
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