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AppNeta Launches High-Resolution DNS Performance Monitoring

AppNeta launched DNS monitoring as a core offering within the AppNeta Performance Manager.

The new capabilities are designed specifically to assess the performance of DNS from the perspective of the end user, not just from the view of the DNS server owner. Because DNS monitoring is fully integrated within AppNeta’s existing Experience testing functionality, users can derive the impact of DNS issues on end users without having to configure separate testing or incurring the additional costs they would with competing products.

AppNeta’s approach to DNS monitoring fits into any network architecture, especially those migrating to the cloud. With the increased use of Direct Internet Access, DNS responses may be delivered to enterprise locations through a diverse collection of servers – both internal and through an array of ISPs and DNS providers – which makes comprehensive monitoring essential.

AppNeta’s DNS monitoring capabilities deliver advanced visibility into DNS performance, providing a local perspective from wherever your users are. DNS performance and reliability data is gathered and analyzed continuously and retained for up to a year, giving IT the insight to spot issues and tune DNS configurations as necessary to ensure the best performance possible throughout the enterprise.

“When it comes to the end user experience of business critical applications, slow is the new down, and nowhere does that manifest itself more than with DNS performance,” said Matt Stevens, CEO of AppNeta. “Total DNS failure is easy to spot, but slow DNS performance insidiously steals valuable time and productivity from everyone. Our new class-leading DNS monitoring capabilities enable forward thinking IT teams to stay ahead of DNS-induced slowness on an app-by-app basis from the end-user’s perspective.”

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AppNeta Launches High-Resolution DNS Performance Monitoring

AppNeta launched DNS monitoring as a core offering within the AppNeta Performance Manager.

The new capabilities are designed specifically to assess the performance of DNS from the perspective of the end user, not just from the view of the DNS server owner. Because DNS monitoring is fully integrated within AppNeta’s existing Experience testing functionality, users can derive the impact of DNS issues on end users without having to configure separate testing or incurring the additional costs they would with competing products.

AppNeta’s approach to DNS monitoring fits into any network architecture, especially those migrating to the cloud. With the increased use of Direct Internet Access, DNS responses may be delivered to enterprise locations through a diverse collection of servers – both internal and through an array of ISPs and DNS providers – which makes comprehensive monitoring essential.

AppNeta’s DNS monitoring capabilities deliver advanced visibility into DNS performance, providing a local perspective from wherever your users are. DNS performance and reliability data is gathered and analyzed continuously and retained for up to a year, giving IT the insight to spot issues and tune DNS configurations as necessary to ensure the best performance possible throughout the enterprise.

“When it comes to the end user experience of business critical applications, slow is the new down, and nowhere does that manifest itself more than with DNS performance,” said Matt Stevens, CEO of AppNeta. “Total DNS failure is easy to spot, but slow DNS performance insidiously steals valuable time and productivity from everyone. Our new class-leading DNS monitoring capabilities enable forward thinking IT teams to stay ahead of DNS-induced slowness on an app-by-app basis from the end-user’s perspective.”

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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 ...

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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 ...

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