Synthetic vs Real Application Monitoring: Why You Need Both
September 04, 2014

Denis Goodwin
SmartBear

Share this

In order to properly manage your applications and user experience you need to start with monitoring them. Application monitoring is evolving — from its beginnings of simply pinging a server to see if it is up, to new, more sophisticated techniques which monitor every detail of a user interaction. How do you decide what techniques to use, should you abandon old methods for new? What’s the difference between Synthetic monitoring and real application monitoring?

There are advantages and disadvantages to both and no need to pick just one. Let’s take a brief look at each technique and see why together they’re better.

There are two main techniques used to monitor applications.

Synthetic monitoring, also called directed monitoring, and Real monitoring, also called passive monitoring; with each method there can be variations in the specifics of performing the task.


What is Synthetic Monitoring?

Synthetic or directed monitoring is a method to monitor your applications by simulating users – directing the path taken through the application. This directed monitoring provides information as to the uptime and performance of your critical business transactions, and most common paths in the application.

The questions that synthetic monitoring answers include:

■ Is my site up?

■ How fast is my site?

■ Are transactions working?

■ If there is a slow down or failure where is it in the infrastructure?

■ Are my third party components operating correctly?

■ How is my overall performance?

■ Am I striking the correct balance of performance versus cost?

Synthetic monitoring does not definitively tell you what your actual users are actually experiencing. In practice that means that you can have all green lights in the data center but a user experience that is broken, slow, and impacting business. Some examples of problems that synthetic monitoring does not find include:

■ Problems with specific browsers or devices that are not included in the synthetic tests

■ Problems with a path other than the ones being tested

■ Geographical problems not specifically measured- the network between a particular location and your application server.

■ Specific individual actions taken by users such as choosing items to add to a cart, can cause problems and synthetic testing cannot cover every iteration.

■ Intermittent problems can be highly troublesome since synthetic tests may not experience the problem when they are run.

What is Real Monitoring?

Real or passive monitoring is a method to monitor your end user activity on your application. Also known as real-user measurement, real-user metrics, or end-user experience monitoring (EUM), this passive monitoring, relies on Web-monitoring services that continuously observe your system in action, tracking availability, functionality, and responsiveness.

So in contrast to synthetic monitoring, real monitoring is unscripted. Information is gathered as users use the application live so the information is only about what users are doing. When an alert is issued, then it is something that actual users experience.

Real monitoring answers these questions:

■ What are users actually doing on the site-traffic flow?

■ What is the performance of the pages, and which components are slowest?

■ Am I fulfilling SLAs?

■ Did my latest release affect the user experience?

■ How does the user experience tie back to other areas of the company such as support?

Real monitoring doesn’t tell you anything about system availability if there are no users on the system. It can’t tell you if there are any problems in the infrastructure along paths that users aren’t on.

The Power of Using Synthetic and Real Together

Where real monitoring techniques provide insight into how your user actually interacts with your website or application, synthetic monitoring provides a similar assessment of expected user experience along with the benefits of true availability monitoring, third-party impact, and consistent base lining capabilities.

Combining synthetic and real monitoring gives a complete view of the user experience along with high level root cause clues. Real monitoring can miss outages, page errors, and third-party problems; while synthetic is really only a proxy for real-user experience and can miss problems experienced by various user populations. In this case, the whole really is greater than the sum of the parts. Using synthetic and real monitoring together provides a complete view of the system, infrastructure and user experience. Using both techniques in tandem eliminates those inherent blind spots and can provide an organization with the best view of their users’ experience – both actual and potential.

As important as these technical advances are, they also support organizational change creating a climate where everyone is responsible for the user experience.

■ Visibility provides efficiencies

■ Eliminates finger pointing

■ Reduces MTTR

■ Understanding impact on actual users allows for better business decisions

■ Brings business owners into the discussion

A unified system combining both synthetic and real monitoring not only facilitates these organizational changes but if it is implemented well, it provides much greater ease of use, with only one system to learn and data combined and displayed in a common manner.

This blog is an excerpt from a new interactive eBook from SmartBear, The Definitive Guide to Synthetic Vs Real Application Monitoring.

Denis Goodwin is Director of Product Management, APM, AlertSite UXM, SmartBear Software.

Share this

The Latest

May 20, 2024

Amid economic disruption, fintech competition, and other headwinds in recent years, banks have had to quickly adjust to the demands of the market. This adaptation is often reliant on having the right technology infrastructure in place ...

May 17, 2024

In MEAN TIME TO INSIGHT Episode 6, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network automation ...

May 16, 2024

In the ever-evolving landscape of software development and infrastructure management, observability stands as a crucial pillar. Among its fundamental components lies log collection ... However, traditional methods of log collection have faced challenges, especially in high-volume and dynamic environments. Enter eBPF, a groundbreaking technology ...

May 15, 2024

Businesses are dazzled by the promise of generative AI, as it touts the capability to increase productivity and efficiency, cut costs, and provide competitive advantages. With more and more generative AI options available today, businesses are now investigating how to convert the AI promise into profit. One way businesses are looking to do this is by using AI to improve personalized customer engagement ...

May 14, 2024

In the fast-evolving realm of cloud computing, where innovation collides with fiscal responsibility, the Flexera 2024 State of the Cloud Report illuminates the challenges and triumphs shaping the digital landscape ... At the forefront of this year's findings is the resounding chorus of organizations grappling with cloud costs ...

May 13, 2024

Government agencies are transforming to improve the digital experience for employees and citizens, allowing them to achieve key goals, including unleashing staff productivity, recruiting and retaining talent in the public sector, and delivering on the mission, according to the Global Digital Employee Experience (DEX) Survey from Riverbed ...

May 09, 2024

App sprawl has been a concern for technologists for some time, but it has never presented such a challenge as now. As organizations move to implement generative AI into their applications, it's only going to become more complex ... Observability is a necessary component for understanding the vast amounts of complex data within AI-infused applications, and it must be the centerpiece of an app- and data-centric strategy to truly manage app sprawl ...

May 08, 2024

Fundamentally, investments in digital transformation — often an amorphous budget category for enterprises — have not yielded their anticipated productivity and value ... In the wake of the tsunami of money thrown at digital transformation, most businesses don't actually know what technology they've acquired, or the extent of it, and how it's being used, which is directly tied to how people do their jobs. Now, AI transformation represents the biggest change management challenge organizations will face in the next one to two years ...

May 07, 2024

As businesses focus more and more on uncovering new ways to unlock the value of their data, generative AI (GenAI) is presenting some new opportunities to do so, particularly when it comes to data management and how organizations collect, process, analyze, and derive insights from their assets. In the near future, I expect to see six key ways in which GenAI will reshape our current data management landscape ...

May 06, 2024

The rise of AI is ushering in a new disrupt-or-die era. "Data-ready enterprises that connect and unify broad structured and unstructured data sets into an intelligent data infrastructure are best positioned to win in the age of AI ...