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Catchpoint Releases AppAssure

Catchpoint unveiled AppAssure, a new simplified offering designed to enhance the digital resilience of top-tier applications.

The new offering provides IT teams with a simple, quickly deployed, affordable solution to have a complete view of everything in the internet stack that impacts an application — dramatically improving the ability to protect uptime and user experience.

Some examples of critical applications ideal for AppAssure include:

■ E-commerce websites, SaaS applications and their mobile counterparts

■ Vendor ordering and management systems, EDI, and other supply-chain applications

■ Electronic Payment, credit card processing, banking and treasury apps

■ Operational applications: logistics, travel applications, fleet management

■ Hospital systems: HER, point of care systems, care management protocols, etc.

“The main reason why application teams are failing is because in today’s cloud-centric world where everything is distributed and service-oriented, these teams don’t have visibility into how the dozens of external dependencies across the internet are impacting their application,” said Mehdi Daoudi, co-founder and CEO of Catchpoint. “These teams are myopically focused on collecting ever more logs, traces, and events, while ignoring the internet stack which includes cloud providers, APIs, EDGE devices, ISPs, Site-to-site connectivity, CDNs, DNS, and dozens more. AppAssure is a game changer for these teams.”

AppAssure changes all this by providing a turnkey solution, quickly deployed to eliminate the guesswork of performance and resilience monitoring. It grants you access to all the power of Catchpoint IPM in an all-in-one cost-effective package that simplifies setup and management, ensuring your critical applications are resilient—without burdening your internal teams.

AppAssure incorporates unique AI-powered capabilities designed to ensure the resilience of your mission-critical applications. A few key benefits include:

Real-World User Experience Monitoring: Leverage thousands of last-mile, wireless, backbone, and cloud nodes across more than 100 countries to monitor applications from the user’s perspective.

Live Global Dashboard: Gain visibility into global internet and cloud service uptime and performance, covering ISPs, DNS, CDN, IaaS, PaaS, SaaS, SECaaS, Martech components, and more.

Comprehensive Metrics: Access detailed performance and availability data for any API, both internal and external.

Networking and Routing Insights: Monitor the entire path from the user, through the backbone, to your servers and internal network. Includes real-time BGP monitoring from front-end to origin to backend servers.

Visual, Interactive Application Map: View current and historical performance and availability with an interactive, real-time map of your Internet Stack, enabling detailed drilldowns.

Complete Dashboards and Alerts: Utilize a full suite of dashboards, alerts, and reports to keep track of performance, what requires immediate attention, and SLA tracking.

Seamless Integrations: Integrate with APM systems, CI/CD pipelines, alerting systems, Open Telemetry, or export raw data to other operational intelligence platforms.

Expert Support: Benefit from initial setup, configuration, and training by an experienced internet resilience team.

It’s a full-service solution delivering instant insights and business value:

Resilience: Uncover opportunities to enhance performance and availability.

SLO and SLA Compliance: Track Service Level Objectives and monitor vendor SLAs for increased accountability. Monitor XLOs (Experience-Level Objectives)

Rapid Issue Resolution: Reduce Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR), minimizing disruptions and the need for War Rooms.

Team Alignment: Reduce finger-pointing and streamline responses to outages, minimizing business impact. Invest resources in fixing the problem, not in finding the problem.

Fully Managed Service: No installations or training required, ensuring a hassle-free experience. A fully-managed Monitoring-as-a-Service model is also available.

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 ...

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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 ...

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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.

Catchpoint Releases AppAssure

Catchpoint unveiled AppAssure, a new simplified offering designed to enhance the digital resilience of top-tier applications.

The new offering provides IT teams with a simple, quickly deployed, affordable solution to have a complete view of everything in the internet stack that impacts an application — dramatically improving the ability to protect uptime and user experience.

Some examples of critical applications ideal for AppAssure include:

■ E-commerce websites, SaaS applications and their mobile counterparts

■ Vendor ordering and management systems, EDI, and other supply-chain applications

■ Electronic Payment, credit card processing, banking and treasury apps

■ Operational applications: logistics, travel applications, fleet management

■ Hospital systems: HER, point of care systems, care management protocols, etc.

“The main reason why application teams are failing is because in today’s cloud-centric world where everything is distributed and service-oriented, these teams don’t have visibility into how the dozens of external dependencies across the internet are impacting their application,” said Mehdi Daoudi, co-founder and CEO of Catchpoint. “These teams are myopically focused on collecting ever more logs, traces, and events, while ignoring the internet stack which includes cloud providers, APIs, EDGE devices, ISPs, Site-to-site connectivity, CDNs, DNS, and dozens more. AppAssure is a game changer for these teams.”

AppAssure changes all this by providing a turnkey solution, quickly deployed to eliminate the guesswork of performance and resilience monitoring. It grants you access to all the power of Catchpoint IPM in an all-in-one cost-effective package that simplifies setup and management, ensuring your critical applications are resilient—without burdening your internal teams.

AppAssure incorporates unique AI-powered capabilities designed to ensure the resilience of your mission-critical applications. A few key benefits include:

Real-World User Experience Monitoring: Leverage thousands of last-mile, wireless, backbone, and cloud nodes across more than 100 countries to monitor applications from the user’s perspective.

Live Global Dashboard: Gain visibility into global internet and cloud service uptime and performance, covering ISPs, DNS, CDN, IaaS, PaaS, SaaS, SECaaS, Martech components, and more.

Comprehensive Metrics: Access detailed performance and availability data for any API, both internal and external.

Networking and Routing Insights: Monitor the entire path from the user, through the backbone, to your servers and internal network. Includes real-time BGP monitoring from front-end to origin to backend servers.

Visual, Interactive Application Map: View current and historical performance and availability with an interactive, real-time map of your Internet Stack, enabling detailed drilldowns.

Complete Dashboards and Alerts: Utilize a full suite of dashboards, alerts, and reports to keep track of performance, what requires immediate attention, and SLA tracking.

Seamless Integrations: Integrate with APM systems, CI/CD pipelines, alerting systems, Open Telemetry, or export raw data to other operational intelligence platforms.

Expert Support: Benefit from initial setup, configuration, and training by an experienced internet resilience team.

It’s a full-service solution delivering instant insights and business value:

Resilience: Uncover opportunities to enhance performance and availability.

SLO and SLA Compliance: Track Service Level Objectives and monitor vendor SLAs for increased accountability. Monitor XLOs (Experience-Level Objectives)

Rapid Issue Resolution: Reduce Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR), minimizing disruptions and the need for War Rooms.

Team Alignment: Reduce finger-pointing and streamline responses to outages, minimizing business impact. Invest resources in fixing the problem, not in finding the problem.

Fully Managed Service: No installations or training required, ensuring a hassle-free experience. A fully-managed Monitoring-as-a-Service model is also available.

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.