Skip to main content

LogicMonitor Acquires Dexda

LogicMonitor acquired Dexda, a big data and machine learning predictive fault identification company.

The acquisition contributes to LogicMonitor’s vision of establishing a global AIOps (Artificial Intelligence for IT Operations) Center of Excellence and accelerates artificial intelligence (AI) and machine learning (ML) enhancements across LogicMonitor’s product portfolio.

“Today’s complex, hybrid IT environments create data at an exploding pace and scale that’s too vast to be analyzed manually. Applying AI and ML to siloed infrastructure and application performance data — be it machine or services alerts or events — allows companies to automatically extract real-time insights to drive better business outcomes,” said Kevin McGibben, CEO of LogicMonitor. “Acquiring Dexda will further enhance LogicMonitor’s ability to generate automated, full-stack insights across the critical technologies modern companies depend on to deliver extraordinary employee and customer experiences.”

Dexda was founded in 2017 and is based in London. The company combines the power of big data and ML to deliver alarm management, AIOps capabilities and intelligent predictive fault detection for technology assets. Dexda’s unique cloud-based solution automates the complex process of predicting and preventing costly asset failures before they occur. Dexda’s disruptive technology finds and manages incidents quickly, linking seamlessly with service desks to provide IT operators and engineers with critical information.

“At Dexda, our vision has always been to use AI and ML to transform asset data into insights that power business growth, and LogicMonitor absolutely shares this vision,” said Patrick O’Connor, CEO and Founder of Dexda. “We’re excited to see the ways in which the Dexda team’s data science and AIOps expertise will further enhance LogicMonitor’s award-winning infrastructure monitoring and observability platform.”

The Dexda acquisition marks the second acquisition this year for LogicMonitor. The company also acquired Bay Area-based application error and performance monitoring company Airbrake in February 2021. The terms of the Dexda transaction will not be disclosed.

The Latest

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 ...

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 ...

LogicMonitor Acquires Dexda

LogicMonitor acquired Dexda, a big data and machine learning predictive fault identification company.

The acquisition contributes to LogicMonitor’s vision of establishing a global AIOps (Artificial Intelligence for IT Operations) Center of Excellence and accelerates artificial intelligence (AI) and machine learning (ML) enhancements across LogicMonitor’s product portfolio.

“Today’s complex, hybrid IT environments create data at an exploding pace and scale that’s too vast to be analyzed manually. Applying AI and ML to siloed infrastructure and application performance data — be it machine or services alerts or events — allows companies to automatically extract real-time insights to drive better business outcomes,” said Kevin McGibben, CEO of LogicMonitor. “Acquiring Dexda will further enhance LogicMonitor’s ability to generate automated, full-stack insights across the critical technologies modern companies depend on to deliver extraordinary employee and customer experiences.”

Dexda was founded in 2017 and is based in London. The company combines the power of big data and ML to deliver alarm management, AIOps capabilities and intelligent predictive fault detection for technology assets. Dexda’s unique cloud-based solution automates the complex process of predicting and preventing costly asset failures before they occur. Dexda’s disruptive technology finds and manages incidents quickly, linking seamlessly with service desks to provide IT operators and engineers with critical information.

“At Dexda, our vision has always been to use AI and ML to transform asset data into insights that power business growth, and LogicMonitor absolutely shares this vision,” said Patrick O’Connor, CEO and Founder of Dexda. “We’re excited to see the ways in which the Dexda team’s data science and AIOps expertise will further enhance LogicMonitor’s award-winning infrastructure monitoring and observability platform.”

The Dexda acquisition marks the second acquisition this year for LogicMonitor. The company also acquired Bay Area-based application error and performance monitoring company Airbrake in February 2021. The terms of the Dexda transaction will not be disclosed.

The Latest

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 ...

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 ...