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Datadog Releases Data Streams Monitoring to Assess Streaming Data Pipeline Performance

Data Streams

Data Streams Monitoring, which enables businesses to easily monitor and control the performance of applications that depend on messaging platforms like RabbitMQ, was made generally available today by Datadog, Inc., the company that develops a monitoring and security platform for cloud apps. To assist organisations in preventing and troubleshooting delay and unavailability, Data Streams Monitoring automatically visualises all dependencies and critical health metrics across all streaming data pipelines.

Traditional solutions frequently only offer a narrow perspective of streaming data pipelines and struggle to reliably pinpoint the underlying reasons of problems, such as throughput dips or malfunctioning services. They might also be missing context from dependencies upstream and downstream. As a result, internal teams must spend more time performing manual chores and troubleshooting in order to obtain pertinent data, contextually analyse it, and decide which teams will need to collaborate with them.

Many mission-critical applications, including banking and trading technologies, automotive systems, payment platforms, and video infrastructures, are built around streaming pipelines. As these streaming pipelines are frequently subject to service-level agreements (SLAs) and legal requirements, teams in charge of managing them need accurate measurement of end-to-end request latencies.

Datadog Data Streams Monitoring, a component of Datadog’s APM platform, automatically visualises dependencies and important health metrics across all streaming data pipelines. With Data Streams Monitoring, engineers can identify problematic queues or services, measure the delay between any two points along the entire streaming data pipeline, and mitigate a flood of backed-up messages to prevent critical downtime.

“Building streaming data pipelines to power our digital trading platform requires visibility into throughput and latency across the entire system, including all queues and services”, “With Data Streams Monitoring, our team is able to proactively discover performance bottlenecks and optimize stream processing to ensure maximum throughput and low latency delivery of data to our customers.”

Darren Furr, Solutions Architect, MarketAxess

“Kafka has become a key component in powering our data processing infrastructure and gaming data streams, which are built using highly sophisticated architectures”, “Datadog Data Streams Monitoring allows us to easily map the topology of our Kafka pipelines across our globally spread clusters, monitor end-to-end latency and identify sources of incidents across our entire pipeline in one place. Having Data Streams Monitoring integrate seamlessly with APM helps us ensure that millions of gamers around the world always get the best possible experience.”

SeungYong Oh, VP of Engineering, Devsisters

“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”, “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.”

Omri Sass, Group Product Manager, Datadog

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