Published on 00/00/0000
Last updated on 00/00/0000
Published on 00/00/0000
Last updated on 00/00/0000
Share
Share
INSIGHTS
8 min read
Share
Software applications have become key drivers for realizing growth and profitability in the modern business world. That's why application performance has become more significant to business stakeholders and IT teams have shifted focus to ensuring applications can continuously meet consumer expectations. In this post, we outline why this has led to the need for the active monitoring technique known as Synthetic Monitoring—and explain what it can do for you.
Application Performance Monitoring (APM) outlines a set of tools and practices to identify bugs and vulnerabilities, enhance user experience, and ensure the computing environment meets agreed-upon performance standards.
Synthetic Monitoring (SM) is an active monitoring technique that follows an APM methodology to simulate the paths users take when accessing an application. IT teams use this technique to gain insights into application uptime, common user access patterns, and the performance of transactions in the application. Let's explore the basics of synthetic monitoring and its significance for modern software teams.
Organizations use Synthetic Monitoring to determine an application’s availability, response speed, transaction performance, cost-effectiveness, and points of failure. SM relies on machines or checkpoints that interact with the application through a common network entity. These machines issue simulated instructions to the application just as a normal user would. The instructions are contained in scripts sent periodically to provide a consistent stream of availability and performance information.
Synthetic Monitoring scripts are sent from machines located close to the users to gain an accurate insight into the application's performance. Teams often deploy checkpoints on multiple servers in different locations to better gauge the application’s global responsiveness and availability. The typical workflow for synthetic monitoring is as follows:
The APM system chooses a checkpoint to perform the simulated access function and sends the script to the selected checkpoint.
The checkpoint then tries to contact the target application, checks for the response, sends the instructions, and proceeds, depending on the check required by the APM system.
If the application fails the check, the APM sends a new test through another checkpoint; if this new check fails, the APM system confirms an error.
The APM then alerts teams to the confirmed error for escalation or attempts a fix if this is set up in the duty schedules and escalation settings.
While there exists a myriad of monitors that simulate user behavior, Synthetic Monitoring mainly covers three areas: web performance, availability, and transactions.
Web performance monitoring checks for the availability and performance of web servers and applications. IT teams can use web performance monitoring to identify issues with page-loading speed, frontend and backend response times, and the performance of all application components. Some of the issues teams can detect using Web Performance Monitoring include:
This is the basic form of monitoring used to establish an application’s uptime and to check that its functions are working as expected. Some synthetic monitoring tools come with advanced availability monitors that can check for specific performance information such as:
Transaction monitoring techniques are used to examine the user experience through specific paths in an application. This takes synthetic monitoring to a higher level by simulating specific patterns that follow a certain task to completion. Transaction monitoring can be used to examine a login service, form completion, product purchase, or how users respond to system prompts.
While Synthetic Monitoring relies on simulated actions to gauge the performance of an application, Real User Monitoring (RUM) involves the tracking of a user experience. RUM is achieved by injecting code into a web page so it collects information on user interactions in the background. There are, therefore, a few fundamental differences between the two monitoring techniques, including:
RUM uses packet and data-capture mechanisms to collect traffic information, while SM uses scripted actions and application responses.
RUM is used to identify historical trends, while SM is mostly used to identify short-term application issues that need immediate remediation.
Synthetic Monitoring uses robot-monitoring clients on checkpoint machines to report on predefined business transactions and system availability. With proper synthetic monitoring, software teams can easily and quickly identify the root causes of performance issues for rapid resolution. This section explores the use cases of synthetic monitoring and top tools to integrate it into your application development and performance management.
If you implement it effectively, Synthetic Monitoring allows software teams to experience the application from a user’s perspective. Teams can view the performance of their applications and integrations before committing them to production and see whether users will have a fulfilling experience. Below, we discuss some of the top use cases for Synthetic Monitoring in application development today.
With Synthetic Monitoring, developers and administrators can deploy checkpoints to monitor applications at flexible locations and intervals. They can then use the SM data to establish a performance baseline and develop improvement strategies after identifying underperforming areas.
Scaling an application across a larger deployment environment may pose challenges to software teams. Synthetic Monitoring enables teams to test their products in new regions. They can simply deploy different checkpoints to evaluate the response speeds from a user’s viewpoint and make improvements as needed for a better user experience.
Most websites today must include numerous third-party plugins, which makes it difficult to pinpoint the root cause of an issue. By evaluating transactions with these tools using Synthetic Monitoring, APM tools can identify the exact point of failure and alert administrators.
Service Level Agreements are important to modern business, as organizations use them for accountability in service delivery. With information from SM systems, application developers can set achievable Service Level Objectives and agree on metrics for successful performance.
The top tools to enable Synthetic Monitoring for Business Service Management include the following:
Epsagon, acquired by Cisco in 2021, is a cloud-native monitoring and automation platform that enables explicit observability of the topology of requests flowing through applications. Epsagon is microservice-based, lightweight, and integrates seamlessly with cloud-native services for end-to-end performance management of modern architectures. By automatically discovering application stacks, Espagon provides visibility into the performance measures of any production environment without needing manual configuration.
Besides this, the platform uses automatic tracing libraries to collect each application-level call without manual code changes, logs, configurations, or sidecars. Epsagon allows administrators to set up notifications for failure alerts based on pre-selected categories and share them via one of various communication channels. The platform also includes an Issue Manager interface that aggregates and correlates data from various SM tools for easier and faster management of alerts. Leveraging a Trace Search mechanism, Espagon allows efficient querying and searching of API calls as well. Epsagon can additionally connect with multiple data sources and lets you create custom dashboards for simplified performance monitoring.
AppDynamics synthetic monitoring enables users to monitor business transactions and performance from the browser to the back-end.
Sematext includes Sematext Synthetics, a Synthetic Monitoring tool that facilitates the delivery of fast, reliable, and consistent websites.
A cloud-native intelligent and automated observability platform, Dynatrace leverages artificial intelligence to simplify cloud monitoring and automation.
Datadog’s synthetic monitor enables the creation of code-free tests to monitor key network endpoints, detect user-facing issues, and jumpstart system-wide investigations into performance and user-experience issues.
SolarWinds’ Synthetic End User Monitor, uses a simple recorder for monitoring a wide range of applications and transactions, including SaaS, web transactions, CRM platforms, etc.
Synthetic monitoring lets organizations understand detrimental steps in transaction processes and application performance to optimize their online strategies. Some benefits of adopting Synthetic Monitoring include:
Easy monitoring of large, complex, modular applications by emulating user transactions and processes
Synthetic Monitoring enables software teams to identify short-term issues with performance that can impact the user experience. SM is typically performed without user input within the production environment for insights into how the application responds to user requests. Epsagon simplifies Synthetic Monitoring through automated tracing, instant alerts, and trace search capabilities.
If you want to learn more, we recommend checking out our piece on observability in security.
Get emerging insights on innovative technology straight to your inbox.
Discover how AI assistants can revolutionize your business, from automating routine tasks and improving employee productivity to delivering personalized customer experiences and bridging the AI skills gap.
The Shift is Outshift’s exclusive newsletter.
The latest news and updates on generative AI, quantum computing, and other groundbreaking innovations shaping the future of technology.