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Corvil Launches App Agent

Corvil launched App Agent, a new solution designed to deliver added visibility into applications with low overhead and nanosecond granularity for event timestamping.

This solution extends Corvil’s real-time analytics capability into application internals, allowing companies to drill down and track performance and latency of transactions through various events contained entirely within a software process. This capability allows companies to gain visibility to when application decisions are made and when data is sent and received - transparency that is increasingly important for digital and algorithmic businesses of all kinds and required by the increasing regulatory climate in which they operate.

Accurate event identification and timestamping at a granular level is critical in understanding sequencing of events as required for MiFID II, performance management and optimization, and fluctuations to understand potential malicious or anomalous activity. Being able to provide this level of visibility without increasing application overhead and reducing overall performance or user experience is unique to Corvil. The App Agent efficiently offloads the work of event timestamping and publishing, keeping code lean and fast, with an overhead impact to less than 10 nanoseconds. Designed for the most demanding and volatile environments, the App Agent can sustain over 200,000 events per second and can buffer data to support higher bursts. With the App Agent, customers can immediately identify performance bottlenecks within application functions and latency hotspots, allowing them to optimize applications and monitor operational performance.

"The Corvil App Agent is an important extension of our capability providing low-overhead visibility and transparency to the performance of application internals. Now, our customers can have a precise view of all events that happen both between machines and within machines from one single analytics platform." says Donal Byrne, CEO of Corvil.

Corvil App Agent is provided as a software library with a simple API that supports multiple languages and makes custom integrations easy with minimal dependencies.

The App Agent can facilitate solutions to complex problems like:

- Providing end-to-end transaction transparency, within applications, to identify bottlenecks or performance fluctuations.

- Measuring accurate latency within software only systems such as delivery of market-data to a client application via a software callback.

- Compliance reporting (e.g., MiFID II) in low latency environments. App Agent ensures application overhead is kept to the absolute minimum, even when software events need to be logged.

- Adding reliable microsecond performance results to application development and test processes.

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For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

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I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

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For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

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Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

Corvil Launches App Agent

Corvil launched App Agent, a new solution designed to deliver added visibility into applications with low overhead and nanosecond granularity for event timestamping.

This solution extends Corvil’s real-time analytics capability into application internals, allowing companies to drill down and track performance and latency of transactions through various events contained entirely within a software process. This capability allows companies to gain visibility to when application decisions are made and when data is sent and received - transparency that is increasingly important for digital and algorithmic businesses of all kinds and required by the increasing regulatory climate in which they operate.

Accurate event identification and timestamping at a granular level is critical in understanding sequencing of events as required for MiFID II, performance management and optimization, and fluctuations to understand potential malicious or anomalous activity. Being able to provide this level of visibility without increasing application overhead and reducing overall performance or user experience is unique to Corvil. The App Agent efficiently offloads the work of event timestamping and publishing, keeping code lean and fast, with an overhead impact to less than 10 nanoseconds. Designed for the most demanding and volatile environments, the App Agent can sustain over 200,000 events per second and can buffer data to support higher bursts. With the App Agent, customers can immediately identify performance bottlenecks within application functions and latency hotspots, allowing them to optimize applications and monitor operational performance.

"The Corvil App Agent is an important extension of our capability providing low-overhead visibility and transparency to the performance of application internals. Now, our customers can have a precise view of all events that happen both between machines and within machines from one single analytics platform." says Donal Byrne, CEO of Corvil.

Corvil App Agent is provided as a software library with a simple API that supports multiple languages and makes custom integrations easy with minimal dependencies.

The App Agent can facilitate solutions to complex problems like:

- Providing end-to-end transaction transparency, within applications, to identify bottlenecks or performance fluctuations.

- Measuring accurate latency within software only systems such as delivery of market-data to a client application via a software callback.

- Compliance reporting (e.g., MiFID II) in low latency environments. App Agent ensures application overhead is kept to the absolute minimum, even when software events need to be logged.

- Adding reliable microsecond performance results to application development and test processes.

The Latest

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...