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Catchpoint Releases Mobile RUM

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.” 

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Catchpoint Releases Mobile RUM

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

For decades, traditional observability tools have forced IT professionals to sift through endless dashboards, turning a flood of alerts into actionable insight and driving widespread burnout. While enterprises adopted AI to eliminate this friction, most still deploy it reactively rather than proactively ... As systems become more complex and IT moves to the center of business strategy, a reactive posture is unsustainable ...

Ask an operations team what they monitor and you will hear a familiar list: latency, errors, throughput, uptime. Those signals still matter for AI, but they no longer answer the most important question. As Krishna Sai, CTO of SolarWinds, puts it: "Traditional observability tells you a system is running. AI observability tells you whether it's still reasoning soundly. Those are completely different questions" ...

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...