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Sentry Raises $40 Million in Funding

Sentry raised $40 million in Series C funding, led by its first capital investor, Accel, with participation from existing investor New Enterprise Associates, Inc. (NEA).

This round of funding will accelerate product development and marketing efforts and will grow Sentry’s team to meet widespread customer demand for more modern application monitoring.

Sentry’s cloud-hosted services are used to proactively identify, triage and prioritize software errors for more than 50,000 organizations worldwide — and many of the world’s best-known companies — including Airbnb, Dropbox, Microsoft, PayPal, Peloton, Pinterest, Square, Symantec and Uber.

“Now that cloud is the de facto standard back-end server infrastructure, the next wave of innovation and efficiency for organizations is in front-end devices, where code meets consumers in application experiences on Single Page Applications, desktops, and mobile and IoT devices,” said David Cramer, co-founder and CEO of Sentry. “It’s time to replace legacy application performance monitoring solutions that were not designed for—and often don’t work at all for—the complexity and constant change of DevOps and high-velocity application development.”

Sentry is designed for modern software running on devices not controlled by application developers. The open-source, agentless error tracking platform goes beyond system alerts and pinpoints exact errors with the depth and detail developers need to accurately see and fix crashes in real time. This enables companies to confidently embrace DevOps and other rapid innovations that continuously release and iterate applications, boosting efficiency and improving user experiences.

“Sentry’s leadership has proven year after year that it can identify emerging technology trends and, crucially, bring products to market that developers need and are willing to pay for,” said Daniel Levine, partner, Accel, which also has invested in Slack, Atlassian, CrowdStrike, Qualtrics, PagerDuty and Dropbox. “We've watched Sentry achieve, and sustain, its market leadership in error monitoring, and we are excited to support the team as they reinvent APM and shake up the market to give customers critical tools for the app-oriented decade ahead.”

Sentry also extended support for native applications, which allows developers for mobile, gaming, IoT and other embedded applications to debug faster with the power of alerts, context and root-cause analysis. Sentry for Native enables developers to move feedback into the development cycle by capturing every single exception and crash users encounter, while also surfacing meaningful trends to help prioritize issues and uncovering potential issue impact.

Using Sentry developers can identify, triage and prioritize errors in all major programming languages and frameworks and integrates with popular apps and services.

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Sentry Raises $40 Million in Funding

Sentry raised $40 million in Series C funding, led by its first capital investor, Accel, with participation from existing investor New Enterprise Associates, Inc. (NEA).

This round of funding will accelerate product development and marketing efforts and will grow Sentry’s team to meet widespread customer demand for more modern application monitoring.

Sentry’s cloud-hosted services are used to proactively identify, triage and prioritize software errors for more than 50,000 organizations worldwide — and many of the world’s best-known companies — including Airbnb, Dropbox, Microsoft, PayPal, Peloton, Pinterest, Square, Symantec and Uber.

“Now that cloud is the de facto standard back-end server infrastructure, the next wave of innovation and efficiency for organizations is in front-end devices, where code meets consumers in application experiences on Single Page Applications, desktops, and mobile and IoT devices,” said David Cramer, co-founder and CEO of Sentry. “It’s time to replace legacy application performance monitoring solutions that were not designed for—and often don’t work at all for—the complexity and constant change of DevOps and high-velocity application development.”

Sentry is designed for modern software running on devices not controlled by application developers. The open-source, agentless error tracking platform goes beyond system alerts and pinpoints exact errors with the depth and detail developers need to accurately see and fix crashes in real time. This enables companies to confidently embrace DevOps and other rapid innovations that continuously release and iterate applications, boosting efficiency and improving user experiences.

“Sentry’s leadership has proven year after year that it can identify emerging technology trends and, crucially, bring products to market that developers need and are willing to pay for,” said Daniel Levine, partner, Accel, which also has invested in Slack, Atlassian, CrowdStrike, Qualtrics, PagerDuty and Dropbox. “We've watched Sentry achieve, and sustain, its market leadership in error monitoring, and we are excited to support the team as they reinvent APM and shake up the market to give customers critical tools for the app-oriented decade ahead.”

Sentry also extended support for native applications, which allows developers for mobile, gaming, IoT and other embedded applications to debug faster with the power of alerts, context and root-cause analysis. Sentry for Native enables developers to move feedback into the development cycle by capturing every single exception and crash users encounter, while also surfacing meaningful trends to help prioritize issues and uncovering potential issue impact.

Using Sentry developers can identify, triage and prioritize errors in all major programming languages and frameworks and integrates with popular apps and services.

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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 ...