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Aviatrix Network Insights API Released

Aviatrix® announced general availability of the new Aviatrix Network Insights API added to its management interface, Aviatrix CoPilot.

Aviatrix's approach grants control over the cloud data plane, offering a vantage point for monitoring network traffic and performance. With Aviatrix Network Insights API, businesses are now able to access and leverage that insight through their existing observability tools.

At the request of customers who also use application monitoring platforms for their cloud operations, incident management, and app development teams, Aviatrix now adds support for OpenMetrics standards. More than 40 observability vendors now support Prometheus and OpenMetrics. As a first step, Aviatrix is providing a Prometheus endpoint collector.

The traffic insights in Aviatrix CoPilot – previously available in a UI as well as through cloud service provider tools including AWS CloudWatch and Azure Log Analytics – need to be callable by New Relic and other observability tools. Cost constrained customers cannot keep adding staff, but instead seek to gain greater productivity and cost efficiency by enabling small, centralized teams to support hundreds of application workloads and sustain the right level of performance and availability. Aviatrix's launch of Aviatrix Network Insights API marks a significant advancement in cloud network application management, offering cloud administrators a powerful tool for seamlessly accessing network data to third-party analytics and visualization platforms.

Aviatrix Network Insights API provides fine-grained access to a broader set of advanced telemetry and network metrics not provided by cloud APIs. Designed for seamless integration with popular platforms like New Relic and Grafana, Network Insights API facilitates publishing the specific network characteristics a network operations team wants to see, providing deeper understanding of network performance and security for a workload at a given point in time. Network Insights API provides simplified access to over a dozen network performance characteristics, including packet drop rates, bandwidth limit exceptions, and packet-per-second limit exceptions. The new API also gives border gateway protocol (BGP) status updates on the core routing protocol run by Aviatrix on the cloud provider, one of the primary indicators for root cause diagnosing an application failure. Instead of providing a full view of all network resources in CoPilot, the network or cloud operations team responsible for a set of critical applications can more easily isolate insight on the routes, VPCs, and traffic of a given account associated to a given workload.

"We took input in from more than 50 top Aviatrix customers over the last year, spanning financial services institutions, health and life sciences leaders, retail organizations, and government agencies across a multitude of countries. The common request was to show critical network metrics tied to specific applications and to deliver that detailed network traffic flow in the application observability tools already in use," said Josh Cridlebaugh, Principal Product Manager at Aviatrix. "In addition to enrichening these valuable tools – because Aviatrix deploys in AWS, Azure, GCP, OCI, and backbone networks provided by companies like Equinix – the visibility into traffic and availability that Aviatrix delivers is both unique and indispensable to those companies who use two or more cloud providers. That's 85% of all organizations, according to Pluralsight. By offering real-time access to detailed network telemetry, Network Insights API enables our customers' cloud administrators to improve their network management and security strategies while simultaneously helping application development and DevOps teams diagnose network related application issues. This improved observability will yield greater operational excellence and present additional opportunities for cost optimization."

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

Aviatrix Network Insights API Released

Aviatrix® announced general availability of the new Aviatrix Network Insights API added to its management interface, Aviatrix CoPilot.

Aviatrix's approach grants control over the cloud data plane, offering a vantage point for monitoring network traffic and performance. With Aviatrix Network Insights API, businesses are now able to access and leverage that insight through their existing observability tools.

At the request of customers who also use application monitoring platforms for their cloud operations, incident management, and app development teams, Aviatrix now adds support for OpenMetrics standards. More than 40 observability vendors now support Prometheus and OpenMetrics. As a first step, Aviatrix is providing a Prometheus endpoint collector.

The traffic insights in Aviatrix CoPilot – previously available in a UI as well as through cloud service provider tools including AWS CloudWatch and Azure Log Analytics – need to be callable by New Relic and other observability tools. Cost constrained customers cannot keep adding staff, but instead seek to gain greater productivity and cost efficiency by enabling small, centralized teams to support hundreds of application workloads and sustain the right level of performance and availability. Aviatrix's launch of Aviatrix Network Insights API marks a significant advancement in cloud network application management, offering cloud administrators a powerful tool for seamlessly accessing network data to third-party analytics and visualization platforms.

Aviatrix Network Insights API provides fine-grained access to a broader set of advanced telemetry and network metrics not provided by cloud APIs. Designed for seamless integration with popular platforms like New Relic and Grafana, Network Insights API facilitates publishing the specific network characteristics a network operations team wants to see, providing deeper understanding of network performance and security for a workload at a given point in time. Network Insights API provides simplified access to over a dozen network performance characteristics, including packet drop rates, bandwidth limit exceptions, and packet-per-second limit exceptions. The new API also gives border gateway protocol (BGP) status updates on the core routing protocol run by Aviatrix on the cloud provider, one of the primary indicators for root cause diagnosing an application failure. Instead of providing a full view of all network resources in CoPilot, the network or cloud operations team responsible for a set of critical applications can more easily isolate insight on the routes, VPCs, and traffic of a given account associated to a given workload.

"We took input in from more than 50 top Aviatrix customers over the last year, spanning financial services institutions, health and life sciences leaders, retail organizations, and government agencies across a multitude of countries. The common request was to show critical network metrics tied to specific applications and to deliver that detailed network traffic flow in the application observability tools already in use," said Josh Cridlebaugh, Principal Product Manager at Aviatrix. "In addition to enrichening these valuable tools – because Aviatrix deploys in AWS, Azure, GCP, OCI, and backbone networks provided by companies like Equinix – the visibility into traffic and availability that Aviatrix delivers is both unique and indispensable to those companies who use two or more cloud providers. That's 85% of all organizations, according to Pluralsight. By offering real-time access to detailed network telemetry, Network Insights API enables our customers' cloud administrators to improve their network management and security strategies while simultaneously helping application development and DevOps teams diagnose network related application issues. This improved observability will yield greater operational excellence and present additional opportunities for cost optimization."

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.