Synthetic monitoring is essential for ensuring the optimal performance of websites and applications in the digital landscape. This article provides insights into how it works and how it can help organizations maintain high-performance standards and protect their bottom line.

As today’s businesses increasingly rely on digital assets such as websites and applications to engage with customers, ensuring their performance is critical. Slow page load times, errors, and downtime can lead to lost revenue, decreased customer satisfaction, and damaged brand reputation. This is where synthetic monitoring comes in.

Synthetic monitoring is an essential tool for DevOps engineers responsible for managing application performance. By proactively identifying and addressing performance issues, DevOps teams can optimize application performance, reduce downtime, and deliver a better experience for end users. 

So, let’s dive in and explore how synthetic monitoring can help improve application performance.

What is synthetic monitoring?

Synthetic monitoring is a proactive technique used to test and monitor the performance of digital assets such as websites and applications. It involves simulating user behavior and testing from various locations to provide insights into potential issues before they affect actual users. 

It is used to ensure optimal performance and user experience and can help organizations identify and address issues across the infrastructure before they impact their bottom line.

  • Synthetic monitoring solutions collect and analyze performance data to provide insights into application performance.
  • They automatically track application uptime and assess responsiveness to typical user behavior.
  • Synthetic monitoring can pinpoint specific business transactions, such as purchases or web form completion, and alert you to any issues users may experience.

Types of Synthetic Monitoring

There are several different types of synthetic monitoring, each designed to focus on specific service areas. Let’s explore some commonly used types of synthetic monitoring:

1. Browser-based monitoring: 

This type of synthetic monitoring simulates user interactions with a website or web application using a web browser. It ensures that the frameworks integrated into your website or application are compatible and function seamlessly, irrespective of the browser or operating system used by your customers.

Multiple workstations spread out throughout the globe are used in these tests to simulate user interactions and assess important performance indicators like load time, availability, and HTTP codes.

Alerts are promptly generated in the event of any problems to allow for prompt corrective action.

2. API & Endpoint monitoring: 

API & Endpoint monitoring is a type of synthetic monitoring that focuses on testing the performance and availability of APIs (Application Programming Interfaces) and endpoints that support service.

APIs and endpoints are critical components of modern applications, enabling them to communicate with external systems and access data.

API & Endpoint monitoring tools often include in-depth analytics and dashboards that let businesses monitor API usage, spot anomalies, and understand performance trends.

Additionally, these technologies assist enterprises in creating and enforcing Service Level Agreements (SLAs) with API providers and guaranteeing regulatory compliance.

3. Network monitoring:

Network monitoring is a type of synthetic monitoring that tests the performance and availability of a service from a network perspective.

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It simulates transactions from various network locations to measure latency, packet loss, and other metrics.

Network monitoring tools typically simulate user transactions from different geographic locations and network providers, enabling organizations to evaluate network performance across various regions and service providers.

These tools also enable organizations to monitor network bandwidth usage, network utilization, and other key network metrics to identify bottlenecks and proactively address issues.

With Middleware’s synthetic monitoring, you can monitor the performance of APIs across multiple network levels, including HTTP, SSL, DNS, TCP, Websocket, UDP, ICMP, and gRPC. 

4. Mobile monitoring: 

Mobile monitoring is a type of synthetic monitoring that focuses on testing the performance and availability of mobile applications on various mobile devices and operating systems.

It helps organizations identify issues related to mobile app performance, such as slow loading times, crashes, and errors, and ensure that their mobile apps provide a seamless user experience.

Mobile monitoring tools typically provide detailed analytics and dashboards that enable organizations to track mobile app performance across different devices, operating systems, and geographies.

These tools also help organizations establish and enforce Service Level Agreements (SLAs) with mobile app developers and ensure compliance with regulatory requirements.

Why synthetic monitoring?

Synthetic monitoring allows organizations to proactively test their web applications, APIs, and other digital services, by simulating user interactions and providing performance data from various locations and devices.

This helps to identify and resolve potential issues before they affect real users, ensuring better user experience and business continuity.

  • Synthetic monitoring supports A/B testing to evaluate the impact of third-party integrations on the website or application performance.
  • It enables the comparison of performance in pre-production and production environments to identify potential issues before they impact users.
  • Synthetic monitoring helps businesses manage externally monitored SaaS applications and ensure their performance meets service agreements.

Benefits of synthetic monitoring

Synthetic monitoring offers several benefits that help organizations ensure optimal performance, minimize downtime, and enhance user experience. 

Benefits of Synthetic Monitoring

Let’s explore a few benefits of Synthetic Monitoring.

1. Improved application performance and user experience

One of the primary benefits of synthetic monitoring is improved application performance and user experience. Synthetic monitoring helps organizations identify and proactively address performance issues before they impact real users. 

Additionally, synthetic monitoring helps organizations minimize downtime, improve application performance, and ensure compliance with regulatory requirements

2. Reduce downtime and outages

With synthetic monitoring, organizations can get a detailed breakdown of network timing data and response time by location, enabling faster root cause analysis and prompt corrective actions to minimize downtime.

Middleware allows you to quickly identify performance issues with meaningful assertions and a detailed time graph, enabling you to troubleshoot faster and provide a seamless user experience.

3. Faster issue detection and resolution

Faster issue detection and resolution is one of the primary benefits of synthetic monitoring. By detecting and resolving issues proactively, organizations can avoid costly downtime and potential revenue loss.

Detect issues before they become errors.

Synthetic monitoring can also help prevent reputational damage caused by poor application performance or outages.

Moreover, synthetic monitoring allows IT teams to test and validate changes to the application or infrastructure in a safe environment before they are implemented in production.

This reduces the risk of introducing new issues and allows faster and more efficient deployment of updates and changes.

4. Cost savings and increased ROI

Synthetic monitoring can also lead to significant cost savings and increased return on investment (ROI) for organizations. By proactively identifying and resolving issues, synthetic monitoring can reduce the need for expensive emergency support and maintenance services.

It can also help organizations avoid costly downtime, negatively impacting revenue and customer satisfaction.

Implementing Synthetic monitoring using Middleware to improve application performance

Step 1: Defining monitoring goals and metrics

Defining the right monitoring goals and metrics is crucial for effective synthetic monitoring. Defining monitoring goals involves identifying the specific objectives that synthetic monitoring should achieve. 

This could include identifying potential performance bottlenecks, detecting the root causes of performance issues, or improving the website or application performance.

Defining clear monitoring goals helps your DevOps team stay focused on what they want to achieve and how they will measure success.

For example, if the monitoring goal is to improve website performance, metrics such as page load time, time to first byte, and server response time would be relevant. 

Similarly, metrics such as error rate, network traffic, and data transfers may be more appropriate if the monitoring goal is to identify potential security vulnerabilities.

Step 2: Create a new monitor (Test)

Synthetic monitoring allows you to launch single or chained requests to perform verifications on your key systems at various network levels: HTTP test, SSL test, DNS test, WebSocket test, TCP test, UDP test, ICMP test, and gRPC test.

You can create a new monitor by clicking on the ‘Create Monitor’ button:

Create a monitor in Middleware
Create a monitor in Middleware

Now, select the request type to create the monitor:

Select the request type
Select the request type

Step 3: Define the request

Define the request with a name and an environment, then enter the URL where you want to run the test. With an advanced setting option, you can add put request headers, authentication, and query parameters.

Defining the request
Defining the request

Step 4: Define assertions and select the location

Add as many assertions as you need for your request. If you need more specific testing, assertions can help (for example, the status code should be 200 only).

Defining assertions and selecting the location
Defining assertions and selecting the location

You can choose where you want this test to run. Location selection is useful when you have global users and your API is accessed worldwide.

Step 4: Specify test frequency and setup retry rules

You can specify the test frequency by selecting a time interval such as every 1m, 5m, etc., or you can define a custom time interval with a day selection (ex: every Monday at 09:00 AM)

Specify test frequency
Specify test frequency

You can configure when the system should retry the test if it fails.

Step 5: Configure the alert monitoring for the test

You can choose who to notify and what to notify about your test.

Configuration for alert monitoring
Configuration for alert monitoring

View your tests and their details

List of all created monitors

View a list of all monitors with information such as uptime, interval, status, and the ability to pause/start, edit, or delete the test. You can also filter the list by request type or location.

View all monitors in one place
View all monitors in one place

View details of specific test

Select the test from the list to view all the details, including response time by location, network timing, and test run results.

Test results
Test results

View details of the specific test:

Test run results
Test run results

View details of a specific result

You can view the response time timeline for each test result.

View details of a specific result
View details of a specific result

Best practices for synthetic monitoring

To implement synthetic monitoring effectively, businesses need to adopt best practices that can help them achieve their goals efficiently. 

Best practices for synthetic monitoring

These practices encompass different aspects of synthetic monitoring, from setting up tests to analyzing results and taking corrective actions.

1. Regular monitoring frequency

Monitoring too infrequently can lead to missed issues and potential downtime while monitoring too frequently can put unnecessary strain on the system being monitored and potentially skew the results.

The ideal monitoring frequency will depend on several factors, such as the criticality of the system being monitored, the expected level of usage, and the resources available to support the monitoring activities. 

However, it’s also essential to consider the impact of monitoring frequency on the system’s performance.

For example, if the system being monitored is already under heavy load, performing synthetic monitoring too frequently can exacerbate the problem and cause additional issues.

In such cases, it may be necessary to adjust the monitoring frequency to reduce the load on the system.

2. Comprehensive test scenarios

Comprehensive test scenarios are critical to the effectiveness of synthetic monitoring. Test scenarios should accurately reflect real-world user interactions and behavior with the system being monitored to identify potential issues that could impact end-users.

To develop comprehensive test scenarios, organizations should consider several factors, including:

  • User behavior – Test common user tasks and interactions
  • System components – Cover all critical components, including frontend, backend, and third-party services
  • Performance metrics – Measure response time, page load speed, and server uptime
  • Failure scenarios – Test for server downtime, network outages, or database failures

3. Realistic user behavior simulation

Realistic user behavior simulation is a critical aspect of synthetic monitoring. It involves simulating user interactions and behavior with the system being monitored to identify potential issues that could impact end-users.

Here are a few things you should keep in mind:

  • Define user personas representing different types of users.
  • Develop use case scenarios based on real-world usage patterns.
  • Map user journeys to identify potential issues or bottlenecks.
  • Vary testing parameters to simulate different scenarios and edge cases.
  • Continuously review and update user behavior simulation to ensure relevance and effectiveness.
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4. Configuring Alerts

Setting alerts is a critical component of synthetic monitoring, as it allows organizations to receive timely notifications of potential issues and take proactive measures to address them. 

To set effective alerts, organizations should consider the following best practices:

  • Identify critical performance metrics
  • Set alert thresholds
  • Choose appropriate alerting channels
  • Customize alerting rules
  • Test alerting mechanisms regularly.

5. Continuous monitoring and improvement

Continuously review and update synthetic monitoring strategies and tools to ensure their effectiveness over time. Here are some best practices for continuous monitoring and improvement:

  • Regularly review and analyze data
  • Use automated tools
  • Collaborate with relevant teams
  • Set improvement goals
  • Continuously test and optimize the system.

Top synthetic monitoring tools

Here are the top three synthetic monitoring tools:

1. Middleware

Middleware is a monitoring platform that specializes in complex, multi-tiered applications. It tracks the performance of web pages and APIs at various network levels, and you can easily deploy and scale with any environment like Docker, Kubernetes, and more.

  • Visualize application performance and uptime data alongside key business metrics to find issues faster.
  • Use a detailed time graph to find which step or endpoint has performance issues.
  • View a breakdown of network timing data and response time by location for faster root cause analysis.

2.  Datadog

Datadog offers Synthetic monitoring, which enables users to create code-free tests that simulate user transactions on applications and monitor key network endpoints across different layers of systems.

  • Stay ahead of issues by proactively monitoring your endpoints through API tests.
  • Easily capture critical transactions without writing any code using our fully hosted web recorder.
  • Ensure secure monitoring of any environment by using your own private locations.

3. New Relic

New Relic is a cloud-based observability platform that offers real-time monitoring of software applications, infrastructure, and customer experiences.

  • Detects low-performing entities such as URLs, APIs, and services proactively.
  • Collaborate to resolve issues automatically generated from affected tests.
  • Leverage alerts and AI to seamlessly transition from synthetic checks to automatically generated tickets within AIOps.

Real-user monitoring vs. Synthetic monitoring: Differences and similarities

Real-User Monitoring (RUM) and Synthetic Monitoring are two different approaches to monitoring the performance and availability of web applications.

RUM collects data from real users’ interactions with the application, while Synthetic Monitoring generates artificial traffic to simulate user behavior.

The main difference between the two approaches is that RUM provides insights into user experiences, while Synthetic Monitoring can identify potential issues before users encounter them. RUM is reactive, while Synthetic Monitoring is proactive.

Real-User Monitoring (RUM) and Synthetic Monitoring share the common goal of monitoring and improving the performance of digital applications.

They both provide valuable insights into application performance and user experience, allowing for proactive identification and resolution of issues.

Additionally, both RUM and Synthetic Monitoring can be used to track and analyze key performance metrics, such as response time and error rates.

Real-User Monitoring (RUM)Synthetic Monitoring
ProsProvides real-time, actual user data.Offers detailed insight into user behavior.

Allows for drill-down analysis to isolate issues and identify root causes.
Provides consistent and reliable testing of critical user paths and application components.

Can test at scale and under different conditions.Can provide proactive monitoring.
ConsCan be resource-intensive, requiring significant data storage and processing power.

May not capture all user activity, particularly for users with ad-blockers or other browser extensions.

Requires actual users to visit the site, limiting the ability to test under different conditions or at scale.
May not reflect actual user behavior and interactions.

May not detect issues that only occur with actual user traffic, such as performance issues related to peak usage times.

How to choose the right monitoring method for your needs? 

To choose the right monitoring method for your needs, you should consider several factors, including the complexity of your applications, the criticality of your services, the target audience, and your budget.

Things to consider when choosing a monitoring method:

  • The types of applications or services you are monitoring, such as web applications, mobile applications, APIs, or microservices
  • The criticality of your services and the potential impact of downtime or performance issues
  • The target audience of your services, such as internal employees, external customers, or partners
  • The level of visibility and granularity required for monitoring, such as transaction traces, code-level visibility, or network performance
  • The cost and resources required for implementing and maintaining the monitoring solution
  • The level of automation and integration required for monitoring, such as integration with other tools or platforms
  • The level of expertise and experience required for managing and interpreting the monitoring data
  • The compliance and regulatory requirements that your organization needs to meet

Synthetic monitoring is essential for organizations looking to ensure their applications and services’ optimal performance and availability.

Organizations can proactively detect issues and optimize their systems by implementing best practices and choosing the right synthetic monitoring tool (like Middleware). Leading to a better end-user experience, increased revenue, and improved customer satisfaction.

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