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Checkmk 2.3 Released

Checkmk released Checkmk 2.3, which extends IT monitoring with synthetic monitoring. Administrators and DevOps teams can use Checkmk Synthetic Monitoring to simulate user interactions with applications in order to monitor the availability, performance, and functionality of those applications from the user's perspective. Checkmk thus helps to build a monitoring stack that includes critical user journeys as well as the IT infrastructure to immediately resolve or proactively prevent incidents. In addition, Checkmk continues to drive out-of-the-box monitoring for a wide range of workloads in hybrid and multi-cloud IT infrastructures. With the new release 2.3, IT service providers will also benefit from significantly enhanced cloud monitoring and even more automation. "For our customers, end-to-end visibility into their IT and rapid problem resolution are critical. They want to know immediately if a business-critical application is not working properly for end users, and whether the problem lies in the application or in the infrastructure. With Checkmk 2.3, we therefore seamlessly integrate application monitoring from the user's perspective into our Checkmk platform," said Jan Justus, CEO at Checkmk. Checkmk Synthetic Monitoring allows for automated testing of application functionality, performance, and availability in order to view a system’s health from the users’ point of view. By simulating user interactions with an application from different geographic locations and devices under real-world conditions, Checkmk Synthetic Monitoring helps to proactively identify and resolve issues in critical user journeys before they negatively impact customer satisfaction and business operations. It enables you to test modern web applications, REST APIs, network protocols, and even local Windows applications, regardless of whether they have an API or run in the browser. At the heart of Checkmk Synthetic Monitoring is the leading open-source-based test automation tool, Robot Framework. Even IT administrators without in-depth programming knowledge can create synthetic tests for a wide range of use cases, such as the online store ordering process or loading times of documents in legacy systems. Monitoring of web services: The HTTP check for web service availability and performance monitoring has been completely redesigned to enable the monitoring of websites, including their certificates. This, as well as more detailed notifications – such as for outdated TLS versions and expiring website certificates – makes it easier to ensure the stability of critical web services. In addition, Checkmk 2.3 not only checks certificates provided over HTTPS but also any application that provides a certificate over a TCP port, such as databases. This allows man-in-the-middle attacks to be detected efficiently and quickly throughout the network. Database monitoring: Now you can monitor all databases compatible with MS SQL queries with the redesigned MS SQL plug-in. The more powerful architecture enables monitoring of all local databases and in-depth monitoring of remote databases such as MS Azure SQL. The plug-in also supports a wide range of MS SQL setups and customized handling of long-running queries. Identify resource hogs: Developed in response to community requests, the top list dashboard dashlet helps IT teams keep track of their ten biggest pain points (hosts or services). For example, being able to view at a glance the systems with the highest resource usage in terms of CPU or disk space makes it easier to manage large IT environments. Numerous visualizations of network connections: For deeper insights into the network topology and quicker mean time to resolution (MTTR), Checkmk 2.3 offers different modes of visualizing network connections. Users can choose whether they want all hosts and their relationships to be displayed, or a combined view of hosts and interfaces, or just hosts and interfaces with problems. In addition to the many minor enhancements to its 2,000+ monitoring plug-ins, Checkmk 2.3 now supports monitoring of Redfish, Nutanix clusters and PureStorage FlashArrays. Numerous additional new features make working with Checkmk even easier and monitoring more efficient. For example, visual and functional upgrades make workflows more intuitive. To test configured notifications, events can now be simulated directly through the Checkmk interface, to ensure that everything works as expected in an emergency. Checkmk MSP, designed specifically for Managed Service Providers, now includes features previously reserved to Checkmk Cloud such as advanced monitoring of multi-cloud environments. Furthermore, Checkmk Cloud's agent capabilities increase the flexibility and efficiency of monitoring customer infrastructures. For example, MSPs can push monitoring data directly to their central Checkmk instance without the need for a remote site, saving time and effort when onboarding small customer environments. Auto-registration also minimizes effort by automatically adding new systems to monitoring.

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For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

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Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Checkmk 2.3 Released

Checkmk released Checkmk 2.3, which extends IT monitoring with synthetic monitoring. Administrators and DevOps teams can use Checkmk Synthetic Monitoring to simulate user interactions with applications in order to monitor the availability, performance, and functionality of those applications from the user's perspective. Checkmk thus helps to build a monitoring stack that includes critical user journeys as well as the IT infrastructure to immediately resolve or proactively prevent incidents. In addition, Checkmk continues to drive out-of-the-box monitoring for a wide range of workloads in hybrid and multi-cloud IT infrastructures. With the new release 2.3, IT service providers will also benefit from significantly enhanced cloud monitoring and even more automation. "For our customers, end-to-end visibility into their IT and rapid problem resolution are critical. They want to know immediately if a business-critical application is not working properly for end users, and whether the problem lies in the application or in the infrastructure. With Checkmk 2.3, we therefore seamlessly integrate application monitoring from the user's perspective into our Checkmk platform," said Jan Justus, CEO at Checkmk. Checkmk Synthetic Monitoring allows for automated testing of application functionality, performance, and availability in order to view a system’s health from the users’ point of view. By simulating user interactions with an application from different geographic locations and devices under real-world conditions, Checkmk Synthetic Monitoring helps to proactively identify and resolve issues in critical user journeys before they negatively impact customer satisfaction and business operations. It enables you to test modern web applications, REST APIs, network protocols, and even local Windows applications, regardless of whether they have an API or run in the browser. At the heart of Checkmk Synthetic Monitoring is the leading open-source-based test automation tool, Robot Framework. Even IT administrators without in-depth programming knowledge can create synthetic tests for a wide range of use cases, such as the online store ordering process or loading times of documents in legacy systems. Monitoring of web services: The HTTP check for web service availability and performance monitoring has been completely redesigned to enable the monitoring of websites, including their certificates. This, as well as more detailed notifications – such as for outdated TLS versions and expiring website certificates – makes it easier to ensure the stability of critical web services. In addition, Checkmk 2.3 not only checks certificates provided over HTTPS but also any application that provides a certificate over a TCP port, such as databases. This allows man-in-the-middle attacks to be detected efficiently and quickly throughout the network. Database monitoring: Now you can monitor all databases compatible with MS SQL queries with the redesigned MS SQL plug-in. The more powerful architecture enables monitoring of all local databases and in-depth monitoring of remote databases such as MS Azure SQL. The plug-in also supports a wide range of MS SQL setups and customized handling of long-running queries. Identify resource hogs: Developed in response to community requests, the top list dashboard dashlet helps IT teams keep track of their ten biggest pain points (hosts or services). For example, being able to view at a glance the systems with the highest resource usage in terms of CPU or disk space makes it easier to manage large IT environments. Numerous visualizations of network connections: For deeper insights into the network topology and quicker mean time to resolution (MTTR), Checkmk 2.3 offers different modes of visualizing network connections. Users can choose whether they want all hosts and their relationships to be displayed, or a combined view of hosts and interfaces, or just hosts and interfaces with problems. In addition to the many minor enhancements to its 2,000+ monitoring plug-ins, Checkmk 2.3 now supports monitoring of Redfish, Nutanix clusters and PureStorage FlashArrays. Numerous additional new features make working with Checkmk even easier and monitoring more efficient. For example, visual and functional upgrades make workflows more intuitive. To test configured notifications, events can now be simulated directly through the Checkmk interface, to ensure that everything works as expected in an emergency. Checkmk MSP, designed specifically for Managed Service Providers, now includes features previously reserved to Checkmk Cloud such as advanced monitoring of multi-cloud environments. Furthermore, Checkmk Cloud's agent capabilities increase the flexibility and efficiency of monitoring customer infrastructures. For example, MSPs can push monitoring data directly to their central Checkmk instance without the need for a remote site, saving time and effort when onboarding small customer environments. Auto-registration also minimizes effort by automatically adding new systems to monitoring.

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...