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Checkly Introduces Activity Log and Code Exporter

Checkly announced the launch of two features that will significantly enhance the user experience and streamline the monitoring process: the Checkly Activity Log and Checkly Code Exporter.

These features enable and empower users to adopt MaC practices more efficiently and effectively into their software development lifecycle, reinforcing Checkly's leadership in the MaC movement.

The Activity Log provides users with a comprehensive history of their Checkly resources. It offers detailed insights into the origin of a resource, including who created or updated it, when it was modified, and the method used for modification, be it the Web UI, Checkly CLI, Terraform, Pulumi, or the Checkly API. This feature enhances transparency and accountability, providing users with a clear understanding of their resource history.

Code Exporter is a feature that allows users to export their resources into Terraform HCL code or TypeScript code compatible with the Checkly CLI, providing a kickstart to their MaC practices. This feature is designed to simplify the adoption of the MaC workflow. It allows users to get started with the Checkly UI first, export their resources and scale their monitoring setup as code from their repository afterward.

Together, these features offer users an end-to-end workflow, making it easier than ever to adopt and benefit from MaC practices.

Checkly's approach to MaC, including the introduction of these new features, is founded on the company’s three key pillars of MaC: Code, Test, and Deploy. This approach allows teams to code their monitoring on their local machine, test their preview deployments in CI, and monitor in production. It's a code-first workflow that integrates seamlessly with modern software development practices and DevOps and SRE toolchains, enabling teams to collaborate, share, optimize, and increase the scalability of synthetic monitoring setups.

The Code Exporter and Activity Log are available for a wide range of resources, including API checks, browser checks, groups, alert channels, maintenance windows, dashboards, private locations, and environment variables. They are free to use on all plans, with data retention limits varying based on the plan type.

"Checkly is at the forefront of advancing Monitoring as Code, equipping users with innovative solutions that not only accelerate their adoption of MaC but also enhance their efficiency and productivity throughout their software development," said Tim Nolet, Checkly CTO and co-founder. "Our latest features show our unwavering commitment to drive the MaC movement, deliver an exceptional user experience, and provide tangible value to our users by simplifying their monitoring processes."

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Checkly Introduces Activity Log and Code Exporter

Checkly announced the launch of two features that will significantly enhance the user experience and streamline the monitoring process: the Checkly Activity Log and Checkly Code Exporter.

These features enable and empower users to adopt MaC practices more efficiently and effectively into their software development lifecycle, reinforcing Checkly's leadership in the MaC movement.

The Activity Log provides users with a comprehensive history of their Checkly resources. It offers detailed insights into the origin of a resource, including who created or updated it, when it was modified, and the method used for modification, be it the Web UI, Checkly CLI, Terraform, Pulumi, or the Checkly API. This feature enhances transparency and accountability, providing users with a clear understanding of their resource history.

Code Exporter is a feature that allows users to export their resources into Terraform HCL code or TypeScript code compatible with the Checkly CLI, providing a kickstart to their MaC practices. This feature is designed to simplify the adoption of the MaC workflow. It allows users to get started with the Checkly UI first, export their resources and scale their monitoring setup as code from their repository afterward.

Together, these features offer users an end-to-end workflow, making it easier than ever to adopt and benefit from MaC practices.

Checkly's approach to MaC, including the introduction of these new features, is founded on the company’s three key pillars of MaC: Code, Test, and Deploy. This approach allows teams to code their monitoring on their local machine, test their preview deployments in CI, and monitor in production. It's a code-first workflow that integrates seamlessly with modern software development practices and DevOps and SRE toolchains, enabling teams to collaborate, share, optimize, and increase the scalability of synthetic monitoring setups.

The Code Exporter and Activity Log are available for a wide range of resources, including API checks, browser checks, groups, alert channels, maintenance windows, dashboards, private locations, and environment variables. They are free to use on all plans, with data retention limits varying based on the plan type.

"Checkly is at the forefront of advancing Monitoring as Code, equipping users with innovative solutions that not only accelerate their adoption of MaC but also enhance their efficiency and productivity throughout their software development," said Tim Nolet, Checkly CTO and co-founder. "Our latest features show our unwavering commitment to drive the MaC movement, deliver an exceptional user experience, and provide tangible value to our users by simplifying their monitoring processes."

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...