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5 Tips for Effective Mobile Monitoring

Eran Kinsbruner

Here are some important guidelines to remember when you start to plan your mobile monitoring strategy ...

1. Real device monitoring is a "must"

Only real devices let you capture the true mobile end user experience in terms of application performance and availability. Be sure to use non-jailbroken/rooted devices, production version apps (non-modified), run complex user scenarios using complex client logic on real devices, and measure client-side performance impact on the overall user experience. Other monitoring solutions, such as browser emulation, fail to reflect the true mobile user experience.

2. Leverage both RUM and Synthetic monitoring techniques

Real User Monitoring is the best way to know what is happening on a user's device, as it is based on an agent within the application that collects data and communicates it to the monitoring server. Synthetic monitoring allows organizations to track application behavior against real networks globally in a “clean-room” environment, and provides an excellent solution for debugging problems identified in the field.

3. Extend your existing monitoring solution to mobile

There is no need to re-invent the wheel. Your operations center has accumulated valuable experience in monitoring and triaging incidents. There is no need to create new processes, re-train personnel or buy completely new solutions. Rather, it is advisable to expand those processes to cover your mobile initiative as well by making it mobile-relevant.

4. Select your synthetic monitoring coverage wisely

Synthetic monitoring, by definition, provides sampled coverage of the audience, devices, carriers and locations, and user scenarios. It is not realistic to provide coverage for everything. Identify those combinations that are relevant to your business objectives and work from there.

5. Ensure the reliability of your monitoring solution to eliminate false alerts

There is nothing most frustrating to your Ops Center staff than false alerts. Your mobile monitoring solution must comply with stringent SLAs to ensure that your engineers do not waste time on alerts caused by problems related to device availability, for example. Device redundancy, together with identification and reduction of alerts driven from known issues, help to ensure proper attention to real issues that are impacting end users.

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5 Tips for Effective Mobile Monitoring

Eran Kinsbruner

Here are some important guidelines to remember when you start to plan your mobile monitoring strategy ...

1. Real device monitoring is a "must"

Only real devices let you capture the true mobile end user experience in terms of application performance and availability. Be sure to use non-jailbroken/rooted devices, production version apps (non-modified), run complex user scenarios using complex client logic on real devices, and measure client-side performance impact on the overall user experience. Other monitoring solutions, such as browser emulation, fail to reflect the true mobile user experience.

2. Leverage both RUM and Synthetic monitoring techniques

Real User Monitoring is the best way to know what is happening on a user's device, as it is based on an agent within the application that collects data and communicates it to the monitoring server. Synthetic monitoring allows organizations to track application behavior against real networks globally in a “clean-room” environment, and provides an excellent solution for debugging problems identified in the field.

3. Extend your existing monitoring solution to mobile

There is no need to re-invent the wheel. Your operations center has accumulated valuable experience in monitoring and triaging incidents. There is no need to create new processes, re-train personnel or buy completely new solutions. Rather, it is advisable to expand those processes to cover your mobile initiative as well by making it mobile-relevant.

4. Select your synthetic monitoring coverage wisely

Synthetic monitoring, by definition, provides sampled coverage of the audience, devices, carriers and locations, and user scenarios. It is not realistic to provide coverage for everything. Identify those combinations that are relevant to your business objectives and work from there.

5. Ensure the reliability of your monitoring solution to eliminate false alerts

There is nothing most frustrating to your Ops Center staff than false alerts. Your mobile monitoring solution must comply with stringent SLAs to ensure that your engineers do not waste time on alerts caused by problems related to device availability, for example. Device redundancy, together with identification and reduction of alerts driven from known issues, help to ensure proper attention to real issues that are impacting end users.

Hot Topics

The Latest

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 4 covers negative impacts of AI ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 3 covers barriers and challenges for AI ...