On one hand, organizations are increasingly relying on web applications to engage customers and deliver value across multiple touchpoints. On the other hand, the complexity of web application environments has intensified significantly due to the prevalence of microservices architecture, content delivery networks (CDNs), and load balancing, among others. At the same time, end users expect a web application to be highly responsive, available around the clock, and accessible from anywhere on any device.
Consequently, monitoring web applications has become critical to ensure they perform as expected; however, this can be challenging for any organization due to various monitoring tools offering different capabilities. In addition to choosing the right tools, an organization should implement an apt strategy to improve monitoring efficiency by minimizing noise and alert fatigue and helping its IT personnel find root causes quickly and remediate issues.
Web application monitoring helps:
- understand end-user experience
- monitor uptime, page load times, and bounce rates, among other critical metrics
- gain visibility into the overall performance of a web application
- reduce mean time to recovery (MTTR)
- tap into root cause summaries to prevent issues from recurring
- improve overall end-user experience
This article explains the elements of efficient web app monitoring and offers some guidance to help choose proper monitoring tools.
Generally, web application monitoring consists of four aspects.
- Real user monitoring
- Synthetic monitoring
- Application performance monitoring (APM)
- Log monitoring
Real User Monitoring
Real user monitoring is the process of collecting performance data from end-user activity on a web application. Real user monitoring tools, like SolarWinds® Pingdom®, usually achieve this through a JavaScript code snippet embedded throughout the web application. The tool then processes the collected data into monitoring metrics and visualizations, such as bar graphs, pie charts, and geographic maps.
Real user monitoring helps understand how end users are experiencing a web application in real time. Any anomalous events present in this type of monitoring indicate the end users are facing issues. While real user monitoring can reveal what problem end users are facing and whether an issue is isolated in a specific geolocation, it cannot offer in-depth insights from an infrastructure or application performance management perspective since it’s limited to monitoring end-user activity.
Synthetic Monitoring
Synthetic monitoring is the process of simulating end-user transactions using a network of servers distributed geographically. This type of monitoring performs availability checks continually to monitor the uptime of a web application or endpoint in the world wide web. It can also monitor transaction flows using automated checks to help ensure end users can reliably achieve various business-critical outcomes; typical examples of transaction flows are sign-up, e-commerce orders, and inquiry forms, among others.
Like real user monitoring, synthetic monitoring can only provide monitoring insights from an end-user perspective. While both real user and synthetic monitoring are essential to web application monitoring, it’s also crucial to monitor the application environment and its underlying infrastructure.
Application Performance Monitoring (APM)
APM is the process of monitoring the application environment from an IT perspective using various techniques, including live code profiling, exception tracking, and distributed tracing. In addition to APM, some tools—like AppOptics—also monitor the underlying infrastructure of the application environment, such as application hosts, database servers, and cloud services. APM typically requires application instrumentation to monitor, and it can sometimes affect the application performance or its underlying infrastructure. This is also why choosing the right APM tool is essential to implement an efficient monitoring strategy.
APM provides in-depth insights into application performance as it can:
- trace how a request is traversed through the application environment through distributed tracing
- monitor code-level performance events and metrics through live code profiling
- track exceptions caused by performance errors
- provide application service maps representing how each component in the application is connected to one another
- provide root cause summaries to pinpoint performance problems efficiently
APM can identify potential performance issues in the initial stages and help remediate the issue before affecting end users. An organization can use APM in tandem with real user and synthetic monitoring to proactively identify and remediate performance issues.
Log Monitoring
An application environment typically consists of various components, including database management systems, web servers, load balancers, and containers. These components log various granular events in a specific format. While this log data can provide granular performance information, it can be challenging to collect log data from multiple sources and parse it into a standard searchable format. A good log management system can alleviate these problems; however, it can be challenging to correlate log data with trace data to gain in-depth insights. Therefore, an integrated APM experience is essential to efficient application monitoring.
An organization can achieve an integrated APM experience by auto-correlating trace data with log data. Some tools like AppOptics and Loggly can natively integrate to achieve this, improving visibility into the performance to a greater extent.
By employing the four types of web app monitoring, an organization can move in the right direction. Since each web application serves a different purpose—and is developed, deployed, and maintained differently, an organization should focus on implementing monitoring optimally for a particular application, which requires to:
- collect all the data related to performance
- synthesize data and relevant metrics into an easily readable or consumable format
- correlate data from multiple sources, including log events and traces
- gain visibility into how each component in the application environment performs and contributes to application performance
- minimize alert fatigue and false positives
Conclusion
Depending on the size of an organization and its revenue model, every minute of application downtime can cost thousands of dollars in lost revenue. An organization can mitigate the possibility of downtime by proactively monitoring its web applications and taking preventative steps as soon as a performance anomaly is discovered.