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Synthetic monitoring is a practice in application performance monitoring that simulates user interactions with an application. By using scripts to replicate user behavior across various scenarios, geographic locations, device types, and other variables, a Splunk license provides a comprehensive analysis of application performance.
Once this valuable performance data is collected and analyzed, a synthetic monitoring solution can:
By utilizing synthetic monitoring, you gain a deeper understanding of potential user experiences and can proactively address performance issues.
In synthetic monitoring, a robot client application installed on a browser, device, or computer sends a series of automated transactions to your application. These server calls and testing scripts mimic an end user’s actions as they navigate through key areas of your application. These tests typically run every 15 minutes, but you can configure them for different frequencies or trigger them immediately based on specific actions.
Once the robot client receives a response from your application, it reports the results back to the synthetic system. If an error is detected during one of its scheduled tests, the monitoring system will prompt the client to run the test again. If the follow-up test also detects an error, the system confirms the issue and escalates it within the organization as appropriate.
This tools can be configured in various ways to meet a company’s requirements. For example, you can set up a robot client on a machine behind your firewall to confirm that the internal environment is functioning as expected. Alternatively, you can deploy a robot client on a computer outside the firewall to gauge the application’s performance externally. For a more comprehensive view of application availability and performance, you can configure multiple robot clients on browsers across various locations.
Synthetic monitoring is often compared to another application performance technique called Real User Monitoring (RUM). Unlike (SM), which simulates user actions, RUM tracks the actions of actual users. Organizations typically implement RUM by embedding JavaScript code into a webpage, which collects performance data in the background as users interact with the page.
Identifying Short-Term Issues: Synthetic monitoring is particularly useful for spotting short-term performance issues that might affect user experience while an application is still being developed.
Early Detection: It enables businesses to catch potential performance problems early, allowing them to address these issues before they impact real users.
Regression Testing: This method is effective for regression testing, ensuring new code changes do not disrupt existing functionality.
Production Site Monitoring: It is also valuable for monitoring production environments, simulating user interactions to ensure the application performs well under various conditions.
Understanding Long-Term Trends: RUM is ideal for understanding long-term trends in an application’s performance after deployment.
Tracking Actual User Interactions: By monitoring real user interactions, RUM provides insights into genuine user experiences, helping businesses make data-driven decisions based on actual user behavior.
In summary, synthetic monitoring is best for early-stage development, regression testing, and proactive issue detection, while RUM is suited for analyzing long-term performance trends and real user experiences post-deployment.
If your application fails to perform well when customers use it, they will quickly seek out better alternatives. This can manifest in several ways:
High Bounce Rates: Slow-loading websites result in high bounce rates. You might also be unaware that your application performance lags behind competitors, which can harm your ability to acquire new customers and expand your market share.
Difficulty Troubleshooting: Even if your organization knows there’s an issue, pinpointing the problem can be challenging. IT teams, often overextended and handling multiple priorities, may struggle to quickly diagnose and resolve performance issues. During this period of uncertainty, your organization could suffer significant and immediate financial impacts.
Monitor System Health: Synthetic monitoring checks your website’s availability, speed, key transaction functionality, and potential slowdowns or failures.
Improve Performance: Over time, synthetic monitoring provides performance benchmarks, highlighting areas needing improvement and optimization.
Prevent Issues Early: By identifying and fixing potential errors before they affect users, synthetic monitoring enhances the user experience. This is especially useful in continuous integration and continuous deployment (CI/CD) environments.
Increase Resiliency: Synthetic monitoring prepares you for peak traffic periods and helps anticipate performance requirements in new regions or markets.
Additionally, synthetic monitoring tools help ensure you meet service level agreements (SLAs) with your end-users. They also empower you to hold third-party providers accountable if issues arise.
Synthetic monitoring generally includes three main types: availability monitoring, web performance monitoring, and transaction monitoring.
Availability Monitoring: Ensures that a site or application is accessible and responsive to requests. It can also take a more detailed approach, such as verifying the availability of specific content or the success of particular API calls.
Web Performance Monitoring: Focuses on specific web metrics like page load speed and the performance of individual elements on a webpage. It checks web content, identifies errors, and detects slow response times.
Transaction Monitoring: Attempts to complete specific transactions, such as logging in, filling out a form, or completing a checkout process.
Within synthetic monitoring, there are two primary categories of tests:
Browser Tests: A robot client simulates transactions that a user might attempt, such as making a purchase.
API Tests: Organizations monitor specific endpoints across each layer of the network and application infrastructure to ensure they are functioning correctly.
These synthetic monitoring techniques help organizations ensure optimal performance, identify and resolve issues proactively, and provide a better user experience.
Modern applications are inherently complex, with users accessing them from various locations and contexts. This complexity means that synthetic monitoring alone is often insufficient to capture all potential errors or situations that might arise. DevOps teams are addressing this challenge by prioritizing application testing earlier in the software development life cycle. However, setting up synthetic monitoring properly still requires specialized technical knowledge and is time-consuming, even for skilled team members.
Synthetic tests are not very resilient and can easily fail when minor UI changes occur, generating unnecessary alert noise. For instance, a change as small as modifying a button requires updating the corresponding test. This frequent need for test updates can be burdensome and inefficient.
Many synthetic monitoring tools lack the necessary context to explain why a specific failure occurred or what the business implications might be. This gap in information prolongs the time to resolution and makes it challenging to prioritize application performance issues effectively.
Despite these challenges, synthetic monitoring remains a valuable tool for early-stage development, regression testing, and proactive issue detection. However, it should be complemented with other monitoring strategies to provide a more comprehensive view of application performance.
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