LogicMonitor has acquired Airbrake, a developer-centric application error and performance monitoring company.
The acquisition will extend LogicMonitor’s award-winning ITIM platform into developer environments and will enable customers to gain visibility into continuous integration and deployment (CI/CD) workflows while reducing risk to ensure that every code release delivers a flawless customer experience.
“Our product vision has always been to equip enterprises and service providers with the industry’s most comprehensive, extensible and intelligent performance monitoring and observability platform to help them deliver exceptional customer experiences,” said Kevin McGibben, CEO of LogicMonitor. “LogicMonitor is committed to helping our customers and partners meet the challenges of today’s ever-changing technology landscape and gain visibility into the end-to-end technology performance that drives their organization, regardless of what tech stack their business is built on. Today’s acquisition of Airbrake marks the latest step in our journey towards unified observability.”
Airbrake was founded in 2008 and is based in the Bay Area. The company was created to solve problems of code and performance issues impacting production environments, and received a funding round in 2020 led by Elsewhere Partners. Hundreds of engineering teams at enterprises ranging from Ring, Adobe, SoundCloud to MyFitnessPal use Airbrake today. Airbrake’s cloud-based, agentless solution enables developers, QA, Engineering and DevOps teams to:
- Access on-demand application error and performance monitoring, plus automatic real-time user experience insights for fast-moving test, staging, and production environments.
- Detect errors in the early stages of development and fix them continuously throughout the code pipeline to increase speed of delivery while ensuring quality and reliability.
- Improve delivery of complex products while reducing risk with frictionless code deployments and automated analysis and troubleshooting for microservices-based applications.
- Gain deep code and user experience insights into a wide variety of web and mobile applications with coverage for 20+ front end and back end programming languages, including Node, Go, Python and Ruby on Rails.
- Keep code and user data secure with industry-leading protocols and protections.
“We’re very optimistic about what LogicMonitor’s acquisition of Airbrake means for customers. Having infrastructure monitoring, logs, and error and performance monitoring accessible within a single observability platform is the ideal solution for a global organization like ours,” said Oscar Garcia, SVP, Managed Services & Platform Automation, NTT. “LogicMonitor and Airbrake coming together will result in a platform that will give teams the ability to detect bugs and prioritize code fixes in the early stages of the software development life cycle, and will enable businesses to reduce outages and maintain the SaaS-based applications instrumental to today’s digital business operations.”
The Airbrake acquisition marks the second acquisition in just over a year for LogicMonitor, who also acquired Stockholm-based log analytics company Unomaly in January 2020.
The terms of the Airbrake transaction will not be disclosed.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...