ElastiFlow announced the General Availability (GA) of Mermin.
Purpose-built for DevOps and Site Reliability Engineering (SRE) professionals, Mermin provides the missing link in Kubernetes observability by delivering vendor-neutral OpenTelemetry (OTel) traces that correlate application performance with the underlying network layer.
"DevOps teams have been managing network complexity with one hand tied behind their back," says Sven Cowart, Co-Founder at ElastiFlow. "Mermin ends the guesswork by delivering OTel-native visibility that identifies, in seconds, whether a slow response is a deployment issue or a network bottleneck."
Mermin leverages lightweight, eBPF-powered technology to understand network traffic within Kubernetes clusters without requiring intrusive sidecars or manual code instrumentation. Key features include:
- Automated Kubernetes Enrichment: Automatically enriches flow traces with K8s metadata like pod and service names, and allows for custom tagging to always have valuable business context.
- OTel-Native Design: Mermin exports data as OTel traces using the flow semantic convention, seamlessly integrating with existing tools including Grafana, OpenSearch, and DataDog.
- Bidirectional Flow Analysis: Captures both directions of a conversation (client-to-server and server-to-client), allowing teams to understand the full nature of traffic, such as a small request followed by a large download
In an era when "every DevOps engineer is now a network expert," Mermin provides the required insights in an easily accessible and actionable way. By providing real-time, contextualized visibility, Mermin enables ops teams to take immediate action, optimize infrastructure, enhance security posture, control costs, and ship code faster.
"The network is often the 'dark matter' of Kubernetes," said Cowart. "With Mermin, we are making that matter visible, actionable, and integrated into the tools engineers already use and love."
The Latest
For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...
Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...
Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...
Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...
Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...
AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...
More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...
In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ...
Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...
2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...