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Embrace Acquires SpeedCurve

Embrace announced its acquisition of SpeedCurve. 

The acquisition brings together expert teams with a shared mission to advance modern observability and give engineers full visibility into how technical performance impacts real users.

By combining Embrace's OpenTelemetry-based observability platform with SpeedCurve's deep web performance insights and synthetics, teams can deliver faster, more reliable experiences across every screen.

Embrace and SpeedCurve believe reliability starts where users begin. Together, they bring the context teams need to understand how every millisecond and every render impact real users and revenue. Integrating SpeedCurve adds web performance capabilities to Embrace's rapidly evolving web and mobile RUM products.

"The SpeedCurve team wrote the book on web performance and user engagement. Their expertise and credibility are unmatched," said Andrew Tunall, President and Chief Product Officer at Embrace. "Together, we're helping the world's most user-oriented companies deliver faster, more reliable digital experiences and bringing performance into the modern observability arena."

The combined products go deep in their domains yet integrate seamlessly with existing stacks via OpenTelemetry. Embrace already collaborates with leading observability providers such as Grafana Labs, Chronosphere, and Elastic, enabling teams to build best-in-class, composable RUM workflows based on OTel. Now, frontend teams will get deeper insights to easily find and fix the problems impacting web performance, and platform teams benefit from user-focused metrics that tie experience to reliability and business metrics.

"For more than a decade, SpeedCurve has helped the web get faster and more human by connecting performance data to real user experience," said Mark Zeman, Founder at SpeedCurve. "Embrace shares this purpose: to make performance something every engineer can own. Combining advanced web insights with the power of Embrace's user-focused observability platform ushers in a new era of reliability."

Embrace will offer customers immediate access to SpeedCurve's synthetic monitoring. Customers using SpeedCurve today don't need to do anything; the product and platform will continue to be fully supported, and users will get early access to innovative web RUM capabilities the companies are building together.

The Latest

For decades, traditional observability tools have forced IT professionals to sift through endless dashboards, turning a flood of alerts into actionable insight and driving widespread burnout. While enterprises adopted AI to eliminate this friction, most still deploy it reactively rather than proactively ... As systems become more complex and IT moves to the center of business strategy, a reactive posture is unsustainable ...

Ask an operations team what they monitor and you will hear a familiar list: latency, errors, throughput, uptime. Those signals still matter for AI, but they no longer answer the most important question. As Krishna Sai, CTO of SolarWinds, puts it: "Traditional observability tells you a system is running. AI observability tells you whether it's still reasoning soundly. Those are completely different questions" ...

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

Embrace Acquires SpeedCurve

Embrace announced its acquisition of SpeedCurve. 

The acquisition brings together expert teams with a shared mission to advance modern observability and give engineers full visibility into how technical performance impacts real users.

By combining Embrace's OpenTelemetry-based observability platform with SpeedCurve's deep web performance insights and synthetics, teams can deliver faster, more reliable experiences across every screen.

Embrace and SpeedCurve believe reliability starts where users begin. Together, they bring the context teams need to understand how every millisecond and every render impact real users and revenue. Integrating SpeedCurve adds web performance capabilities to Embrace's rapidly evolving web and mobile RUM products.

"The SpeedCurve team wrote the book on web performance and user engagement. Their expertise and credibility are unmatched," said Andrew Tunall, President and Chief Product Officer at Embrace. "Together, we're helping the world's most user-oriented companies deliver faster, more reliable digital experiences and bringing performance into the modern observability arena."

The combined products go deep in their domains yet integrate seamlessly with existing stacks via OpenTelemetry. Embrace already collaborates with leading observability providers such as Grafana Labs, Chronosphere, and Elastic, enabling teams to build best-in-class, composable RUM workflows based on OTel. Now, frontend teams will get deeper insights to easily find and fix the problems impacting web performance, and platform teams benefit from user-focused metrics that tie experience to reliability and business metrics.

"For more than a decade, SpeedCurve has helped the web get faster and more human by connecting performance data to real user experience," said Mark Zeman, Founder at SpeedCurve. "Embrace shares this purpose: to make performance something every engineer can own. Combining advanced web insights with the power of Embrace's user-focused observability platform ushers in a new era of reliability."

Embrace will offer customers immediate access to SpeedCurve's synthetic monitoring. Customers using SpeedCurve today don't need to do anything; the product and platform will continue to be fully supported, and users will get early access to innovative web RUM capabilities the companies are building together.

The Latest

For decades, traditional observability tools have forced IT professionals to sift through endless dashboards, turning a flood of alerts into actionable insight and driving widespread burnout. While enterprises adopted AI to eliminate this friction, most still deploy it reactively rather than proactively ... As systems become more complex and IT moves to the center of business strategy, a reactive posture is unsustainable ...

Ask an operations team what they monitor and you will hear a familiar list: latency, errors, throughput, uptime. Those signals still matter for AI, but they no longer answer the most important question. As Krishna Sai, CTO of SolarWinds, puts it: "Traditional observability tells you a system is running. AI observability tells you whether it's still reasoning soundly. Those are completely different questions" ...

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...