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Monitoring as Code: Worth The Hype?

Hannes Lenke
Checkly

Configuring application Monitoring as Code (MaC) is the next logical step in modern software development. Today, configuring monitoring is often an overly manual process. It's a bottleneck that DevOps teams are addressing to ship code faster with greater confidence.

Before we explore the relatively new MaC concept, we should step back and discuss the "as Code" movement in general. The most prominent current example is Infrastructure as Code (IaC), which became the gold standard for infrastructure provisioning in recent years. IaC lets developers write files that define how servers should be set up. Building on that concept, IaC tools apply those configurations automatically, often fully integrated into the CI/CD process.

Bringing key aspects of the software development workflow closer to the application code enables developers to automate and ultimately ship their services faster and more often, continuously. Hence ‘as code' has become popular in recent years. However, continuous delivery (CD) requires more than infrastructure automation. It also requires automation of other software delivery aspects. Without this additional automation, how would DevOps teams be able to ship code updates dozens of times a day or even more often?

Next to automation, one key aspect of CD is that cross-functional DevOps teams are now responsible for their services from one end to the other. The motto "You build it; you test it; you run it!" rings true for teams not only tasked to ship often but to simultaneously test and operate those deployed services. It's vital for modern DevOps teams to embrace automation for other functions in their pipeline, including crucial aspects like monitoring. In that context, health and performance monitoring need to be described as code too.

Let's look at some key reasons why monitoring as code is here to stay.

Monitoring shouldn't become the bottleneck for software delivery

Creating checks for larger APIs or websites are often repetitive manual tasks that require a lot of time. In addition, the demand on DevOps teams to make daily — or even hourly — changes to target applications translates into exploding workloads and testing requirements.
In contrast, defining something as code enables you to replicate the actions you would usually do manually — using a UI or CLI — and automate these.

Lack of transparency makes cross-team collaboration harder

Traditional monitoring processes require manual provisioning, meaning users need to create tickets to have new monitoring resources provisioned for them or request permission to apply the changes themselves. In turn, central IT teams are often required to work through different UIs and flows.

This makes it difficult to maintain consistency across an entire infrastructure while simultaneously avoiding duplication of effort across teams. It also complicated the task of auditing changes, making it difficult to review wrongly configured monitoring checks, thereby lengthening an important feedback loop.

Monitoring should be CI/CD integrated

Eventually, the speed of checks-provisioning does not match the pace at which the target applications are evolving. This results from a mismatch of approaches: the CI/CD workflow through which the websites and APIs are iterated upon on one side vs. the fully manual approach on the other.

Applying lessons learned from IaC, MaC brings check definitions closer to the application's source code by having them written as code.

This method allows check definitions to live in source control, boosting cross-team visibility. Additionally, code is text, which is useful for version control and generating an audit trail of all changes. This makes it easier to roll back changes in case of incidents.

With software taking over the provisioning of monitoring checks, hundreds or thousands of checks can be created or edited in a matter of seconds. This is a game-changer for development, operations, and DevOps teams, allowing them to reallocate time spent on manual configuration toward improving the coverage and robustness of their monitoring setup.

To summarize, MaC is revolutionizing the way monitoring is configured by providing:

1. Better scalability through faster, more efficient provisioning

2. Increased transparency and easier rollbacks via source control

3. Unification of previously fragmented processes in a CI/CD workflow

Hannes Lenke is CEO and Co-Founder of Checkly

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Monitoring as Code: Worth The Hype?

Hannes Lenke
Checkly

Configuring application Monitoring as Code (MaC) is the next logical step in modern software development. Today, configuring monitoring is often an overly manual process. It's a bottleneck that DevOps teams are addressing to ship code faster with greater confidence.

Before we explore the relatively new MaC concept, we should step back and discuss the "as Code" movement in general. The most prominent current example is Infrastructure as Code (IaC), which became the gold standard for infrastructure provisioning in recent years. IaC lets developers write files that define how servers should be set up. Building on that concept, IaC tools apply those configurations automatically, often fully integrated into the CI/CD process.

Bringing key aspects of the software development workflow closer to the application code enables developers to automate and ultimately ship their services faster and more often, continuously. Hence ‘as code' has become popular in recent years. However, continuous delivery (CD) requires more than infrastructure automation. It also requires automation of other software delivery aspects. Without this additional automation, how would DevOps teams be able to ship code updates dozens of times a day or even more often?

Next to automation, one key aspect of CD is that cross-functional DevOps teams are now responsible for their services from one end to the other. The motto "You build it; you test it; you run it!" rings true for teams not only tasked to ship often but to simultaneously test and operate those deployed services. It's vital for modern DevOps teams to embrace automation for other functions in their pipeline, including crucial aspects like monitoring. In that context, health and performance monitoring need to be described as code too.

Let's look at some key reasons why monitoring as code is here to stay.

Monitoring shouldn't become the bottleneck for software delivery

Creating checks for larger APIs or websites are often repetitive manual tasks that require a lot of time. In addition, the demand on DevOps teams to make daily — or even hourly — changes to target applications translates into exploding workloads and testing requirements.
In contrast, defining something as code enables you to replicate the actions you would usually do manually — using a UI or CLI — and automate these.

Lack of transparency makes cross-team collaboration harder

Traditional monitoring processes require manual provisioning, meaning users need to create tickets to have new monitoring resources provisioned for them or request permission to apply the changes themselves. In turn, central IT teams are often required to work through different UIs and flows.

This makes it difficult to maintain consistency across an entire infrastructure while simultaneously avoiding duplication of effort across teams. It also complicated the task of auditing changes, making it difficult to review wrongly configured monitoring checks, thereby lengthening an important feedback loop.

Monitoring should be CI/CD integrated

Eventually, the speed of checks-provisioning does not match the pace at which the target applications are evolving. This results from a mismatch of approaches: the CI/CD workflow through which the websites and APIs are iterated upon on one side vs. the fully manual approach on the other.

Applying lessons learned from IaC, MaC brings check definitions closer to the application's source code by having them written as code.

This method allows check definitions to live in source control, boosting cross-team visibility. Additionally, code is text, which is useful for version control and generating an audit trail of all changes. This makes it easier to roll back changes in case of incidents.

With software taking over the provisioning of monitoring checks, hundreds or thousands of checks can be created or edited in a matter of seconds. This is a game-changer for development, operations, and DevOps teams, allowing them to reallocate time spent on manual configuration toward improving the coverage and robustness of their monitoring setup.

To summarize, MaC is revolutionizing the way monitoring is configured by providing:

1. Better scalability through faster, more efficient provisioning

2. Increased transparency and easier rollbacks via source control

3. Unification of previously fragmented processes in a CI/CD workflow

Hannes Lenke is CEO and Co-Founder of Checkly

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Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

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Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

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