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SignalFx Raises $45 Million in Series D Funding

SignalFx announced $45 million in Series D funding led by General Catalyst with participation from existing investors Andreessen Horowitz and Charles River Ventures. This round brings total funding for SignalFx to $103.5 million since its founding in 2013.

As the only platform delivering a consolidated real-time view of infrastructure, services, applications, containers, and functions, SignalFx has gained the trust of the world’s leading brands across a range of industry verticals from hi-tech, financial services, media and telecommunications, to retail, healthcare, manufacturing, and consumer products. A few notable customers include athenahealth, Ellie Mae, HubSpot, Kayak, Shutterfly, Square, and Yelp.

“We are enormously excited to welcome General Catalyst to our team,” says Karthik Rau, CEO and co-founder of SignalFx. “Our industry is at a critical inflection point as the vast majority of existing systems management solutions are ill equipped to handle the software architectures and delivery models that every company now aspires towards. In the past three years, we’ve been privileged to partner with over a hundred enterprises across many industry verticals to accelerate their journey to cloud-native. With the additional Series D funding, we plan to accelerate our efforts across both product development and go-to-market to enable thousands more to make the journey to cloud-native as seamless as possible.”

In conjunction with the funding, SignalFx announced the appointment of Dr. Stephen Herrod, general partner at General Catalyst and former CTO of VMware, to the Company’s board of directors. He joins Ben Horowitz, general partner at Andreessen Horowitz, Devdutt Yellurkar, general partner at Charles River Ventures, and SignalFx co-founders Phil Liu, and co-founder/CEO Karthik Rau.

Prior to its current funding, SignalFx raised $58.5 million in its Series A, B and C rounds from Andreessen Horowitz and Charles River Ventures.

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SignalFx Raises $45 Million in Series D Funding

SignalFx announced $45 million in Series D funding led by General Catalyst with participation from existing investors Andreessen Horowitz and Charles River Ventures. This round brings total funding for SignalFx to $103.5 million since its founding in 2013.

As the only platform delivering a consolidated real-time view of infrastructure, services, applications, containers, and functions, SignalFx has gained the trust of the world’s leading brands across a range of industry verticals from hi-tech, financial services, media and telecommunications, to retail, healthcare, manufacturing, and consumer products. A few notable customers include athenahealth, Ellie Mae, HubSpot, Kayak, Shutterfly, Square, and Yelp.

“We are enormously excited to welcome General Catalyst to our team,” says Karthik Rau, CEO and co-founder of SignalFx. “Our industry is at a critical inflection point as the vast majority of existing systems management solutions are ill equipped to handle the software architectures and delivery models that every company now aspires towards. In the past three years, we’ve been privileged to partner with over a hundred enterprises across many industry verticals to accelerate their journey to cloud-native. With the additional Series D funding, we plan to accelerate our efforts across both product development and go-to-market to enable thousands more to make the journey to cloud-native as seamless as possible.”

In conjunction with the funding, SignalFx announced the appointment of Dr. Stephen Herrod, general partner at General Catalyst and former CTO of VMware, to the Company’s board of directors. He joins Ben Horowitz, general partner at Andreessen Horowitz, Devdutt Yellurkar, general partner at Charles River Ventures, and SignalFx co-founders Phil Liu, and co-founder/CEO Karthik Rau.

Prior to its current funding, SignalFx raised $58.5 million in its Series A, B and C rounds from Andreessen Horowitz and Charles River Ventures.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...