SignalFx, provider of an advanced monitoring platform for modern applications, emerged from stealth and announced a $20 million Series B funding round led by Charles River Ventures with participation from existing investor Andreessen Horowitz, bringing the company's total financing to $28.5 million.
SignalFx will use the funds to significantly expand sales and marketing and to accelerate R&D focused on solving the monitoring problems of the $100 billion cloud software market.
Devdutt Yellurkar, General Partner at Charles River Ventures, will join the SignalFx Board of Directors which includes Ben Horowitz, Andreessen Horowitz Founder and Partner; SignalFx Founder and CEO Karthik Rau; and SignalFx Founder and CTO, Phillip Liu.
SignalFx also unveiled its advanced monitoring platform for modern applications. Built by inventors of cloud-scale monitoring technologies for today's Internet giants, SignalFx is a SaaS-based monitoring platform that uses SignalFlow streaming and historical analytics technology on operational metrics at any scale to provide an interactive, system-wide view of applications and infrastructure. The distributed and dynamic nature of modern applications has turned monitoring into an analytics problem — SignalFx enables development and operations teams to shift from component-level monitoring to detecting aggregate patterns and anomalies across their distributed applications in real time.
"Today's applications are often composed on many services and/or microservices that function with high levels of autonomy. Optimizing the availability and performance of today's applications is virtually impossible with traditional monitoring tools," said Stephen D. Hendrick, Principal Analyst for Development and Deployment Research at ESG. "This is why tools such as those from SignalFx that monitor and analyze application performance in real time are now a necessity."
SignalFx equips organizations of all sizes to make better decisions based on a data-driven approach to application design and operations. Designed to enable organizations to submit multi-dimensional metric data at any scale, SignalFx allows product teams to model and correlate key application and business metrics against underlying infrastructure behavior to answer critical questions about operations.
Developers, operations, DevOps and SRE teams can benefit from SignalFx application and infrastructure monitoring technology:
- Meaningful and actionable alerting: Traditional monitoring solutions set alerts using static thresholds on metrics collected from individual components, resulting in noisy alerts for distributed applications. SignalFlow streaming and historical analytics technology enables product teams to apply custom analytics pipelines on metrics collected from thousands or more sources to create meaningful aggregations (percentiles, moving averages, growth rates, etc.) within seconds of receiving data. These real-time aggregations can be compared against historical patterns to allow product teams to set alerts based on anomalous trends.
- Interactive, system-wide visibility: SignalFx delivers unparalleled self-service access to all of the application and infrastructure metrics most critical to the success of an application. Product teams can model and see the impact of metrics like customer usage on infrastructure performance and business KPIs. The real-time, interactive nature of SignalFlow technology enables organizations to ask and answer questions about their operations as events are still occurring in their environments.
- Cross-team communication: Applications with microservices architectures have several interdependencies and require a high level of coordination between teams. SignalFx provides a single source of context where teams may curate dashboards with key metrics to share and get insight into the operational characteristics of any service.
"Today's launch of SignalFx is just the beginning of our team's work to reinvent monitoring for modern applications," said Phillip Liu, Founder and CTO of SignalFx. "An analytics-based approach to monitoring is essential for modern applications — with SignalFx and SignalFlow technology, our customers can focus their efforts on interpreting operational metrics, discovering key patterns, and communicating insights with one another rather than building and supporting an undifferentiated metrics infrastructure. We plan to invest aggressively in our monitoring platform so that our customers can deliver well-built, reliably performing, rapidly improving applications time and time again."
"The move towards SaaS and cloud business models has introduced a major disruption in the world of downstream operations management products, with the monitoring category at the center of this disruption," said Devdutt Yellurkar, general partner at Charles River Ventures. "SignalFx is truly changing the game for monitoring modern applications with its breakthroughs in streaming analytics technology. The opportunities that lie ahead for the company are massive and as a board member, I'm looking forward to working with a talented and experienced team to lead the way to the future of application and systems monitoring technology."
"The developers and DevOps teams running modern applications need a monitoring platform that supports dynamic and distributed architectures," said Karthik Rau, Founder and CEO of SignalFx. "Our engineers have been instrumental in pioneering monitoring solutions for leading Internet giants and have unique insight into what it takes to address the analytics gaps required to solve today's monitoring problem."
The Latest
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 ...
Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...
Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...
Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...
If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...
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 ...