Honeycomb.io announced an extended partnership with Embrace, the user-focused observability platform.
Together, the two companies are extending the rigorous, data-driven practice that Honeycomb pioneered for foundational observability to mobile and web, giving engineering, site reliability, and platform teams a complete, correlated picture of system health. The strategic partnership makes understanding performance and reliability for every user and every screen part of the observability practice, bringing new depth and standardization to how teams measure end user impact.
Backend teams have had strong tooling for server health, latency, and distributed tracing for years, but no real window into what users experience on devices and browsers. Frontend and mobile developers, meanwhile, have been underserved by traditional observability tooling that cannot provide the depth and breadth of insights required, forcing them to seek disparate tools just to identify and resolve user-impacting issues. Organizations end up with no shared data, blind spots on root causes, and a disconnect between teams that should be collaborating to improve performance and deliver better user experiences and business outcomes.
Embrace was built on OpenTelemetry, approaching frontend performance the same way Honeycomb approaches foundational observability: with high-cardinality, context-rich data that ties technical signals directly to user impact. This shared foundation means performance data from mobile apps and web browsers can flow into, be queried with, and be understood by every engineering team across the stack, with no proprietary schema standing in the way.
This technical integration brings frontend session data, crash signals, network insights, Core Web Vitals, and real user context from mobile and web surfaced inside the Honeycomb platform. Key customers leveraging both products have been asking for exactly this kind of integration.
“We’ve always believed observability is a practice, not a product category,” said Matt Nelson, Chief Revenue Officer at Honeycomb. “Embrace has applied that same rigorous, data-driven approach to the layer where users experience software. Building on OpenTelemetry means the data speaks the same language and that’s what makes this a real integration, not a dashboard mashup. SRE and platform teams can finally see the whole system, not just the parts they already owned. And their mobile and web counterparts can address issues with the same data, in great detail.”
What This Means for Engineering Teams
With this partnership, engineering teams that use both Honeycomb and Embrace benefit from:
- End user visibility, across web and mobile: Real user data from Embrace, with aggregated insights from session timelines, crash signals, network insights, and user journey context are surfaced inside Honeycomb, giving SRE, reliability, and platform engineering teams a better understanding of what’s happening on the device and in production systems.
- Expanded RUM capabilities, purpose-built for frontend engineering teams: Organizations that rely on Honeycomb for backend and infrastructure observability can now extend that same practice to their web and mobile practitioners, giving those teams the most powerful RUM tooling by Embrace, fully connected to the systems and data their reliability colleagues use.
- Native data, not a bolt-on: Both platforms are built on OpenTelemetry, which means signals and telemetry arrive in Honeycomb as standard, enriched, composable data, not a proprietary feed that requires translation. The context that makes observability useful stays intact.
- Performance tied to user impact: Embrace’s approach ties technical performance signals directly to end user experience, surfacing how frontend degradation translates to real business impact. Now, that data lives alongside telemetry in Honeycomb.
“Performance and reliability are two sides of the same coin,” said Andrew Tunall, President and Chief Product Officer at Embrace. “We built Embrace on OpenTelemetry because we believe the future of understanding complex systems is open, composable, and context-rich. This partnership is a natural extension of that belief: when the data is standard and the philosophy is shared, the integration is real. At the end of the day, users don’t care whether the root cause of an issue is service behavior, a bug, or a rendering problem, they just want your product to work.”
Embrace is available in the AWS Marketplace alongside Honeycomb, giving joint customers flexibility in how they acquire and deploy both products.
The Latest
Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...
Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...
Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...
While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...
For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...
As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...
The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...
The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...
Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...
Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...