BlazeMeter announced integration with New Relic Insights, entering the next phase of its multi-level partnership with New Relic. This integration enables customers to have an active, real-time querying conversation with their own performance testing data by utilizing the analysis power of New Relic Insights.
The integration of New Relic Insights, a real-time analytics platform that empowers users to make fast and informed decisions about their software, now allows BlazeMeter customers to gather and visualize their load test data on New Relic’s dynamic, customizable dashboards—giving them unparalleled insights into their system architecture and performance metrics. With Insights, joint customers can analyze their test environment data in new and exciting ways.
“In the past, access to big data solutions was complicated, time-consuming and expensive. New Relic Insights works to change this—it collects, stores and analyzes billions of data points and displays them in real-time. Users can now have an active conversation with the software, querying the KPIs that matter to them and receiving instant answers,” said Bill Lapcevic, VP of Business Development at New Relic. “Successful performance testing goes hand-in-hand with sophisticated analytics and we are delighted to broaden our partnership with BlazeMeter with this new integration.”
Joint BlazeMeter and New Relic customers can now automatically feed data into New Relic Insights and make correlations with test environment data in new ways. They can, for example, view multiple test runs, segment test metrics, get a ‘birds eye’ aggregate view or drill down into deeper granularity. Users can also query the data and receive answers in seconds, enabling them to make better data-driven decisions.
“Testing makes it easy to trigger a symptom, but you need monitoring to identify the root problem in the first place. Together, BlazeMeter and New Relic provide their customers a full 360-degree view of their systems,” said Alon Girmonsky, Founder and CEO of BlazeMeter. “Data analysis is most valuable when you can understand and act upon it instantly. With the Insights integration, our customers can dynamically define the KPIs they want to analyze, query the application and instantly understand the specific quirks of their system.”
The integration between BlazeMeter and New Relic also expands the value proposition to both companies’ customers. The Insights integration is the third connection from BlazeMeter’s partnership with New Relic, following the New Relic Connect Partner and Platform Partner announcements. BlazeMeter has been a New Relic partner since January 2013. The components from the New Relic partnership make it easier for users to monitor end-user experience and KPIs while load testing.
The Latest
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 ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...