Catchpoint is excited to announce the release of Mobile RUM, its new native real-user monitoring for mobile applications.
Built on OpenTelemetry standards, this new capability gives teams comprehensive visibility into mobile experiences, including insights into anything affecting the mobile user experience in the Internet Stack from app code to network conditions. This launch is part of Catchpoint’s broader platform upgrade, which also includes Benchmarks, an expanded global observability network, BGP private peers, and improved AI-driven capabilities.
Catchpoint was an early adopter of OpenTelemetry with its Code Tracing capabilities. Now, by extending OTel to native mobile RUM, Catchpoint empowers customers with the most comprehensive, future-proof observability platform on the market. OpenTelemetry provides a standardized, vendor-neutral approach to instrumenting software for observability, offering benefits such as consistent data collection, enhanced visibility into application performance, and flexibility in choosing monitoring and observability tools. It streamlines the process of gathering and analyzing telemetry data.
“In today's fast-paced digital landscape, the need for robust and reliable native mobile app real user monitoring (RUM) and the need for borderless visibility has never been greater. We are proud to fulfill this need by offering our newest Mobile RUM capabilities, based on OpenTelemetry, to advance the standards of observability, web performance monitoring, and Internet Stack visibility,” says Mehdi Daoudi, CEO at Catchpoint. “By offering these cutting-edge capabilities to our customers, we empower businesses to deliver exceptional native mobile user experiences, optimize app performance, and stay ahead in the competitive mobile market,” he adds.
The Native Mobile SDK RUM capability enables a holistic view of application performance by capturing data from actual, hyperlocal user sessions in real time.
The latest release from Catchpoint is further augmented by new features such as Benchmarks, Connected Devices, Code Tracing add-ons at no additional cost, Internet Sonar enhancements, private BGP, contemporary testing (e.g., Playwright) capabilities, and more. These capabilities collectively provide ultimate visibility into real-world user experience and anything in the Internet Stack that may impact digital experience.
This launch introduces a new feature that facilitates the collection of code tracing data from synthetic tests at no additional cost. With this added visibility, IT operations teams can see everything in the path from the user, across the Internet, and deep into software code traces. This level of insight helps IPM users quickly identify whether a line of code or a database query is impacting an application experience.
“Mobile RUM advances data ownership and portability through OpenTelemetry. By using OpenTelemetry-based tracing, IT teams can uncover deeper insights across broader observability boundaries,” says Serkan Özal, Architect at Catchpoint. “One major auto manufacturer recently switched tracing providers and pointed data to our collectors in just minutes, which dramatically sped up performance troubleshooting.”
The Latest
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...