Skip to main content

Checkly Introduces Monitoring as Code Workflow

Checkly announced a new monitoring as code (MaC) workflow — enabled by a new CLI released today in beta — that unites software testing and monitoring in one code-driven workflow that spans development, testing, deployment, and operations.

The company also unveiled new features and enhancements, including general availability of Playwright Test, updated public dashboards, a robust new analytics API, and successful completion of its SOC 2 Type II security audit.

Checkly’s new MaC workflow and CLI enables developers, platform engineers, and SREs to code, test, and deploy their testing and synthetic monitoring in one seamless workflow. The new MaC workflow harnesses the power of Playwright for browser checks, and allows developers to store all resources in a Git repo, alongside their existing application code for increased deployment speed and confidence. The new Checkly MaC CLI also allows developers to code and structure resources using TypeScript, allowing them to take advantage of the improved developer experience and code maintainability.

“Configuring monitoring is often an overly manual process of operations teams. With MaC we are now liberating this traditionally siloed workflow, enabling developers to configure monitoring themselves early during development,” says Hannes Lenke, Checkly Co-Founder and CEO. “We’re thrilled to deliver our MaC workflow supporting Playwright and API checks to give developers the ability to code, test and deploy with confidence.”

Further demonstrating the deep value of the platform to customers and users, Checkly has already run more than 5.0 Billion API and browser checks and, in the last quarter, added nearly one hundred customers and thousands of users, including development teams at top brands and organizations globally.

Product Innovations Announced:

- MaC Workflow and CLI (beta): A new MaC workflow and CLI allows developers to code Playwright-based E2E checks and API checks using TypeScript / JavaScript, then easily test and deploy those checks against Checkly’s global infrastructure.

- GA for Playwright Test: Playwright Test is GA, and Playwright is now the default and recommended testing and monitoring framework to use with Checkly. This release also adds a new UI that includes screenshots, videos, traces, and error logs to improve monitoring efficiency.

- Updated Dashboards: Updates to dashboards allow more users to brand and personalize the look and feel of their dashboards using custom CSS rules, configure custom subdomains, and also features improved readability and accessibility.

- New Analytics API: A new analytics API gives users more freedom to generate reports for business needs. Users can now integrate Checkly data into 3rd party BI platforms like Microsoft PowerBI, Google Data Studio, Grafana, and more.

The Latest

Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026. Part 2 covers data and data platforms ...

Checkly Introduces Monitoring as Code Workflow

Checkly announced a new monitoring as code (MaC) workflow — enabled by a new CLI released today in beta — that unites software testing and monitoring in one code-driven workflow that spans development, testing, deployment, and operations.

The company also unveiled new features and enhancements, including general availability of Playwright Test, updated public dashboards, a robust new analytics API, and successful completion of its SOC 2 Type II security audit.

Checkly’s new MaC workflow and CLI enables developers, platform engineers, and SREs to code, test, and deploy their testing and synthetic monitoring in one seamless workflow. The new MaC workflow harnesses the power of Playwright for browser checks, and allows developers to store all resources in a Git repo, alongside their existing application code for increased deployment speed and confidence. The new Checkly MaC CLI also allows developers to code and structure resources using TypeScript, allowing them to take advantage of the improved developer experience and code maintainability.

“Configuring monitoring is often an overly manual process of operations teams. With MaC we are now liberating this traditionally siloed workflow, enabling developers to configure monitoring themselves early during development,” says Hannes Lenke, Checkly Co-Founder and CEO. “We’re thrilled to deliver our MaC workflow supporting Playwright and API checks to give developers the ability to code, test and deploy with confidence.”

Further demonstrating the deep value of the platform to customers and users, Checkly has already run more than 5.0 Billion API and browser checks and, in the last quarter, added nearly one hundred customers and thousands of users, including development teams at top brands and organizations globally.

Product Innovations Announced:

- MaC Workflow and CLI (beta): A new MaC workflow and CLI allows developers to code Playwright-based E2E checks and API checks using TypeScript / JavaScript, then easily test and deploy those checks against Checkly’s global infrastructure.

- GA for Playwright Test: Playwright Test is GA, and Playwright is now the default and recommended testing and monitoring framework to use with Checkly. This release also adds a new UI that includes screenshots, videos, traces, and error logs to improve monitoring efficiency.

- Updated Dashboards: Updates to dashboards allow more users to brand and personalize the look and feel of their dashboards using custom CSS rules, configure custom subdomains, and also features improved readability and accessibility.

- New Analytics API: A new analytics API gives users more freedom to generate reports for business needs. Users can now integrate Checkly data into 3rd party BI platforms like Microsoft PowerBI, Google Data Studio, Grafana, and more.

The Latest

Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026. Part 2 covers data and data platforms ...