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Real User Monitoring (RUM) vs. Synthetic Monitoring
Businesses offer their services to customers with the help of websites and web/mobile applications. To increase their service availability, businesses must efficiently fix issues that affects the user experience negatively. Real User Monitoring (RUM) and synthetic monitoring are two different ways of monitoring the user experience and finding performance issues. As an IT decision maker, it is important to understand the various benefits of monitoring the user experience with the right tools.
Understanding Real User Monitoring
In RUM, performance data is collected when real users visit your website or use your business applications. RUM records all the complex ways in which users interact with your service channels. Users use several types of browsers for accessing your website or web application. RUM can help you learn which browser or combination of browsers is being used. With RUM, businesses can gain visibility into the satisfaction level of end-users while using their applications and websites. The results generated from RUM are then used to fix performance issues and enhance service availability.
Usually, JavaScript is used to add tags to business websites and applications. Whenever an end-user logs in to the business application or visits the website, the tags get activated. A RUM system collects various types of performance metrics like website loading time, delays in the transaction process, and others. With the help of data about user interactions, you can gain several insights about customer behavior. Application performance monitoring is essential as customers will skip your website/application if it has a lot of performance issues. RUM has helped CXOs to find out flaws in the company’s website or application and fix them in time.
What is synthetic monitoring?
Can you monitor the performance of your website without publicly launching it? You can do this by simulating traffic via synthetic monitoring. Synthetic monitoring or directed monitoring simulates user paths to find performance issues. For each synthetic user path, several checkpoints are determined by monitoring teams. At each checkpoint, performance metrics are collected that uncover performance issues with the website or application. The simulated user path in directed monitoring will be similar to what an actual user will take.
In synthetic monitoring, instead of a real user, a bot goes through the pre-defined path. Synthetic monitoring is beneficial for businesses that don’t want customers to find their performance issues. It is also used during the testing process before launching web apps or mobile applications. If the performance issues are detected by the users, they may stop using your services. Some user paths are not taken by end-users often and, they remain isolated. To boost service availability, you must improve all aspects of your websites and business applications. Synthetic monitoring helps in identifying performance issues for user paths that are not generally used.
Difference between RUM and Directed Monitoring
RUM and synthetic monitoring are both essential elements of application performance monitoring. Both the techniques are used to understand user behavior, network delays, UX issues, and analyze the health of the website or application. However, the difference between RUM and directed monitoring can be found in their functioning. RUM is done usually in the post-production period. On the other hand, synthetic application performance monitoring is done during the pre-production stages. Synthetic monitoring is always performed in a controlled environment whereas, you cannot control the user paths in RUM.
The major difference between RUM and synthetic monitoring can be found in the test subjects that are used. RUM has real users as test subjects who can take any path according to their preferences. In synthetic monitoring, the user path is known beforehand as it is a simulation. Also, the test subject in synthetic monitoring is a bot (fake user). Both types of application performance monitoring are equally important for a business organization. It is why business organizations use a combination of RUM and directed monitoring to achieve the best results.
Challenges with RUM and synthetic monitoring
Application performance monitoring is a challenging task in today’s scenario. The challenges faced by IT teams before implementing monitoring techniques are as follows:
- The number of digital channels that are used to interact with the customers and offer them services has increased. To ensure high service availability, you will have to perform end-user monitoring for all the digital channels of your organization. Traditional monitoring tools cannot collect performance data from multiple sources.
- The number of customers that use websites and business applications has increased drastically. Application performance monitoring is more intense than ever. Traditional monitoring tools fail to handle the huge traffic on digital channels.
- Since the number of business websites and applications has increased, businesses need more site reliability engineers to detect performance issues. Hiring more system administrators and engineers can cost much to an organization. Age-old application performance monitoring tools cannot perform automatically.
How to perform monitoring effectively in 2021?
AI for application monitoring has proved useful in providing performance data in real-time. AI for ITOps can detect performance issues even before the end-user discovers them. You can use AIOps based analytics platforms to collect performance data from all your digital channels. Additionally, you do not need to hire many reliability engineers for application performance monitoring. AIOps can perform non-stop monitoring of user paths on websites and business applications. With minimum manual interference, you will have access to high-end monitoring analytics to boost your uptime.
During the forecast period of 2021 -2030, the AIOps industry size is expected to increase with a healthy CAGR of 37%. More and more organizations are overcoming monitoring challenges by using AIOps based analytics platforms and specialized monitoring methods such as RUM and synthetic monitoring.
