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Checkmk 2.4 Integrates OpenTelemetry and Synthetic Testing

Checkmk today announced the release of version 2.4, introducing powerful new features  designed to enhance full-stack monitoring. With integrated OpenTelemetry metrics and synthetic testing, IT teams gain end-to-end visibility across all layers of the IT stack — from infrastructure and applications to end-user experience. These capabilities enable faster, more proactive issue resolution and significantly reduce mean time to resolution (MTTR). Version 2.4 also introduces features such as quick setup for cloud workload monitoring and a redesigned Notification Hub, which reduce administrative overhead and lighten the load on overburdened IT teams. With this release, Checkmk addresses two of the biggest challenges in modern IT: rising system complexity and the ongoing shortage of skilled professionals.

Checkmk’s integration of OpenTelemetry allows IT teams to look inside their applications and monitor performance, availability, and potential failure points—right from the application code, all within a single platform. The built-in OpenTelemetry collector ingests data directly or via Prometheus endpoints, translates it into actionable metrics, and maps them to the relevant hosts. This provides clear visibility into not just what is failing, but where and why, enabling faster root cause analysis and targeted fixes — even for previously unidentified issues.

Checkmk 2.4 also introduces enhanced synthetic monitoring capabilities, making it easier for teams to create tests that simulate user behavior and assess availability, performance, and functionality from the end-user perspective. First introduced in version 2.3, synthetic testing is now fully integrated into the Checkmk interface. Test robots that simulate user behavior can be uploaded via the web UI and centrally configured and managed. These managed robots can be cloned, customized, and automatically deployed to Linux or Windows test nodes using the Checkmk Agent Bakery. New features also support synthetic testing in isolated offline environments, and KPI monitoring allows teams to track and analyze individual process steps within each test.

Checkmk 2.4 introduces a range of enhancements that boost usability, increase automation, and improve efficiency — while reducing administrative overhead. 

Highlights include:

  • Quick Setup: Cloud monitoring in minutes - Checkmk’s new Quick Setup feature streamlines and accelerates cloud monitoring configuration across AWS, Azure, and GCP. A guided, step-by-step process handles complex setup tasks in the background and verifies system connections, enabling administrators to achieve full cloud visibility quickly and reliably.
  • Notification Hub: Simplified alert configuration - The new Notification Hub streamlines the configuration, management, and fine-tuning of alerting workflows through an intuitive interface and improved user guidance. Key settings are centralized and accessible with just a few clicks, while real-time status messages and troubleshooting tips help users stay informed and respond quickly. Usability features such as search, slide-outs, and drop-down menus make setup more efficient. A newly added guided mode walks beginners through the configuration process step-by-step — saving time and reducing the risk of misconfiguration.
  • Dynamic host management: Automated control of Kubernetes clusters - In dynamic environments like Kubernetes or virtualized systems, hosts are constantly being created and removed. Checkmk detects these changes in real time, automatically adds new hosts to the monitoring system, and reliably removes those that no longer exist. Designed for maximum scalability, the dynamic host management feature ensures stable, high-performance monitoring — even with hundreds of changes per minute.

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Checkmk 2.4 Integrates OpenTelemetry and Synthetic Testing

Checkmk today announced the release of version 2.4, introducing powerful new features  designed to enhance full-stack monitoring. With integrated OpenTelemetry metrics and synthetic testing, IT teams gain end-to-end visibility across all layers of the IT stack — from infrastructure and applications to end-user experience. These capabilities enable faster, more proactive issue resolution and significantly reduce mean time to resolution (MTTR). Version 2.4 also introduces features such as quick setup for cloud workload monitoring and a redesigned Notification Hub, which reduce administrative overhead and lighten the load on overburdened IT teams. With this release, Checkmk addresses two of the biggest challenges in modern IT: rising system complexity and the ongoing shortage of skilled professionals.

Checkmk’s integration of OpenTelemetry allows IT teams to look inside their applications and monitor performance, availability, and potential failure points—right from the application code, all within a single platform. The built-in OpenTelemetry collector ingests data directly or via Prometheus endpoints, translates it into actionable metrics, and maps them to the relevant hosts. This provides clear visibility into not just what is failing, but where and why, enabling faster root cause analysis and targeted fixes — even for previously unidentified issues.

Checkmk 2.4 also introduces enhanced synthetic monitoring capabilities, making it easier for teams to create tests that simulate user behavior and assess availability, performance, and functionality from the end-user perspective. First introduced in version 2.3, synthetic testing is now fully integrated into the Checkmk interface. Test robots that simulate user behavior can be uploaded via the web UI and centrally configured and managed. These managed robots can be cloned, customized, and automatically deployed to Linux or Windows test nodes using the Checkmk Agent Bakery. New features also support synthetic testing in isolated offline environments, and KPI monitoring allows teams to track and analyze individual process steps within each test.

Checkmk 2.4 introduces a range of enhancements that boost usability, increase automation, and improve efficiency — while reducing administrative overhead. 

Highlights include:

  • Quick Setup: Cloud monitoring in minutes - Checkmk’s new Quick Setup feature streamlines and accelerates cloud monitoring configuration across AWS, Azure, and GCP. A guided, step-by-step process handles complex setup tasks in the background and verifies system connections, enabling administrators to achieve full cloud visibility quickly and reliably.
  • Notification Hub: Simplified alert configuration - The new Notification Hub streamlines the configuration, management, and fine-tuning of alerting workflows through an intuitive interface and improved user guidance. Key settings are centralized and accessible with just a few clicks, while real-time status messages and troubleshooting tips help users stay informed and respond quickly. Usability features such as search, slide-outs, and drop-down menus make setup more efficient. A newly added guided mode walks beginners through the configuration process step-by-step — saving time and reducing the risk of misconfiguration.
  • Dynamic host management: Automated control of Kubernetes clusters - In dynamic environments like Kubernetes or virtualized systems, hosts are constantly being created and removed. Checkmk detects these changes in real time, automatically adds new hosts to the monitoring system, and reliably removes those that no longer exist. Designed for maximum scalability, the dynamic host management feature ensures stable, high-performance monitoring — even with hundreds of changes per minute.

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While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

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 ...

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