Why Synthetic Monitoring and End-to-End Testing Belong Together

Hannes Lenke
Checkly
Learn more about Checkly

Synthetic monitoring is crucial to deploy code with confidence as catching bugs with E2E tests on staging is becoming increasingly difficult. It isn't trivial to provide realistic staging systems, especially because today's apps are intertwined with many third-party APIs.

That's why nowadays, the low-hanging fruit is to set up checks that constantly monitor your production environment from an end-user perspective. This allows you to quickly find and fix issues on production before they become a problem for your customers. However, you need both testing in pre-production and monitoring on production.

Whether e-commerce shops or complex banking setups, systems are becoming increasingly intertwined and also distributed. They do not only rely on internal services but also on many external APIs such as payment APIs. It's nearly impossible to spin up production-like staging systems for these architectures. However, developers are, for many reasons, tasked to ship small pieces of new software numerous times a day. And this requires automation that ensures changes do not introduce bugs and break crucial flows while still delivering at speed and scale.

So on one side, we have complex systems that are nearly impossible to test fully in pre-production, and on the other, we have an increasing need for faster software delivery. These two things are like two trains on the same track heading for a collision. Thankfully, synthetic monitoring is here for the rescue!

But what is testing, and what is synthetic monitoring?

Let's look at synthetic monitoring and testing and what both could learn from each other. I'm sure ChatGPT can help us to define both terms:

Synthetic Monitoring

Synthetic monitoring tests and examines websites, applications, or services to ensure all components, including APIs, function as expected. It helps identify potential issues before they become a problem for the user or connected systems. It can be done from worldwide distributed remote locations. In simple terms, synthetic monitoring is having automated scripts checking your assets constantly to see if they are working correctly.

E2E testing

E2E testing helps to ensure the complete flow of an application or website works as expected before it gets deployed to production. It involves running tests to ensure all components work correctly from start to finish, as a real user would. In other words, it's like having an automated virtual tester check your web app to see if it works how it should.

Synthetics + Testing

In theory, synthetic monitoring and E2E testing are quite similar. While monitoring is meant to test your app on production constantly, E2E testing is intended to catch bugs before you deploy. The main difference in the past was that quality assurance (QA) teams performed testing while monitoring was the responsibility of operations (OPS), so the responsibility was split between two siloed teams. Not anymore!

Testing matured during the last decade from proprietary algorithms to open-source-based code hosted in your repository next to your application code. Today, cross-functional DevOps teams continuously run automated E2E tests in their CI/CD pipeline instead of isolated QA teams testing new versions of your app for three months before release.

Synthetic monitoring is also evolving similarly. It follows the transition E2E testing has already made: From proprietary scripts living in closed monitoring platforms to open-source-based scripts embedded in your repository. Monitoring is shifting left, as testing did, and is becoming integral to your developer's pipeline. The industry should encourage and enable developers to use the same scripts for pre-production tests and production monitoring. Doing so will blur the lines between E2E testing and synthetic monitoring.

So what does modern synthetic monitoring look like? Monitoring as code (MaC) is the next evolution of synthetic monitoring. To be successful in a MaC approach, we need to look at three essential pillars that make up the MaC concept: code, test, and deploy:

1. Code: Automated tests are defined as code and live in a repository, often close to your application code. When I write code, I mean code, not just configuration files saved in a repository. With that approach, MaC enables flexibility and programmability, allowing you to test your backend and UI by supporting complex API and browser checks.

2. Test: Synthetic monitoring was traditionally meant to run on production only. Now, checks as code enable us to run all or some of these checks locally and in a CI/CD flow to be tested on staging before a new version gets deployed. Monitoring is becoming testing, and testing is becoming monitoring, blurring the lines between the two.

3. Deploy: The main difference between testing and monitoring is scheduling. MaC enables us to schedule our tests, executing these constantly, 24/7, in distributed remote locations worldwide. In other words, your tests are deployable. In addition, deploying your tests via your CI/CD process allows monitors to be updated with application code changes.

Synthetic monitoring has been evolving quickly during the last months. We see many exciting approaches to enable developers to ensure that their apps are reliable and resilient. Monitoring as code is the only logical next step, as it has many advantages and enables you to reuse your tests.

Hannes Lenke is CEO and Co-Founder of Checkly

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Why Synthetic Monitoring and End-to-End Testing Belong Together

Hannes Lenke
Checkly
Learn more about Checkly

Synthetic monitoring is crucial to deploy code with confidence as catching bugs with E2E tests on staging is becoming increasingly difficult. It isn't trivial to provide realistic staging systems, especially because today's apps are intertwined with many third-party APIs.

That's why nowadays, the low-hanging fruit is to set up checks that constantly monitor your production environment from an end-user perspective. This allows you to quickly find and fix issues on production before they become a problem for your customers. However, you need both testing in pre-production and monitoring on production.

Whether e-commerce shops or complex banking setups, systems are becoming increasingly intertwined and also distributed. They do not only rely on internal services but also on many external APIs such as payment APIs. It's nearly impossible to spin up production-like staging systems for these architectures. However, developers are, for many reasons, tasked to ship small pieces of new software numerous times a day. And this requires automation that ensures changes do not introduce bugs and break crucial flows while still delivering at speed and scale.

So on one side, we have complex systems that are nearly impossible to test fully in pre-production, and on the other, we have an increasing need for faster software delivery. These two things are like two trains on the same track heading for a collision. Thankfully, synthetic monitoring is here for the rescue!

But what is testing, and what is synthetic monitoring?

Let's look at synthetic monitoring and testing and what both could learn from each other. I'm sure ChatGPT can help us to define both terms:

Synthetic Monitoring

Synthetic monitoring tests and examines websites, applications, or services to ensure all components, including APIs, function as expected. It helps identify potential issues before they become a problem for the user or connected systems. It can be done from worldwide distributed remote locations. In simple terms, synthetic monitoring is having automated scripts checking your assets constantly to see if they are working correctly.

E2E testing

E2E testing helps to ensure the complete flow of an application or website works as expected before it gets deployed to production. It involves running tests to ensure all components work correctly from start to finish, as a real user would. In other words, it's like having an automated virtual tester check your web app to see if it works how it should.

Synthetics + Testing

In theory, synthetic monitoring and E2E testing are quite similar. While monitoring is meant to test your app on production constantly, E2E testing is intended to catch bugs before you deploy. The main difference in the past was that quality assurance (QA) teams performed testing while monitoring was the responsibility of operations (OPS), so the responsibility was split between two siloed teams. Not anymore!

Testing matured during the last decade from proprietary algorithms to open-source-based code hosted in your repository next to your application code. Today, cross-functional DevOps teams continuously run automated E2E tests in their CI/CD pipeline instead of isolated QA teams testing new versions of your app for three months before release.

Synthetic monitoring is also evolving similarly. It follows the transition E2E testing has already made: From proprietary scripts living in closed monitoring platforms to open-source-based scripts embedded in your repository. Monitoring is shifting left, as testing did, and is becoming integral to your developer's pipeline. The industry should encourage and enable developers to use the same scripts for pre-production tests and production monitoring. Doing so will blur the lines between E2E testing and synthetic monitoring.

So what does modern synthetic monitoring look like? Monitoring as code (MaC) is the next evolution of synthetic monitoring. To be successful in a MaC approach, we need to look at three essential pillars that make up the MaC concept: code, test, and deploy:

1. Code: Automated tests are defined as code and live in a repository, often close to your application code. When I write code, I mean code, not just configuration files saved in a repository. With that approach, MaC enables flexibility and programmability, allowing you to test your backend and UI by supporting complex API and browser checks.

2. Test: Synthetic monitoring was traditionally meant to run on production only. Now, checks as code enable us to run all or some of these checks locally and in a CI/CD flow to be tested on staging before a new version gets deployed. Monitoring is becoming testing, and testing is becoming monitoring, blurring the lines between the two.

3. Deploy: The main difference between testing and monitoring is scheduling. MaC enables us to schedule our tests, executing these constantly, 24/7, in distributed remote locations worldwide. In other words, your tests are deployable. In addition, deploying your tests via your CI/CD process allows monitors to be updated with application code changes.

Synthetic monitoring has been evolving quickly during the last months. We see many exciting approaches to enable developers to ensure that their apps are reliable and resilient. Monitoring as code is the only logical next step, as it has many advantages and enables you to reuse your tests.

Hannes Lenke is CEO and Co-Founder of Checkly

Related Links

Hot Topics

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The Latest

When Automating Forever Becomes Faster Than Doing It Once

People want to be doing more engaging work, yet their day often gets overrun by addressing urgent IT tickets. But thanks to advances in AI "vibe coding," where a user describes what they want in plain English and the AI turns it into working code, IT teams can automate ticketing workflows and offload much of that work. Password resets that used to take 5 minutes per request now get resolved automatically ...

Smarter Systems for Disinformation: How Data-Centric Design Could Transform Online Trust

Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

The 5 Pillars of Cross-Platform Observability

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

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For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

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From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

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Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

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The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...