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Catchpoint Opens Office in India

Catchpoint Systems announced the opening of its Bangalore office, its first office in India, and an expansion of its web and mobile performance monitoring points in India.

Catchpoint now has 13 backbone monitoring nodes in India, more than several competitors combined, in addition to three last-mile nodes. This expansion brings Catchpoint’s monitoring nodes presence to a total of 78 in the critical Asia-Pacific region, and 381 live nodes worldwide, including backbone, last mile, and wireless locations.

Catchpoint’s Bangalore office now has five employees, with plans to expand to 15 by the end of 2015. Bangalore staff will provide support to Catchpoint’s India-based customers, as well as those in the rest of the APAC and Middle East regions.

“Digital commerce in India is in its early stages, but experts agree it is set to explode,” comments Mehdi Daoudi, CEO and founder of Catchpoint Systems. “As Internet businesses gain a foothold there, the ability to ensure fast, reliable end-user experiences is paramount. Catchpoint’s web performance monitoring nodes in India will help these companies overcome web infrastructure complexity, gain customers and build business traction.”

According to the Internet and Mobile Association of India (IAMAI), today, India has 243 million internet users – more than the United States and second only to China. Gartner recently cited India as one of the fastest growing e-commerce markets in Asia-Pacific, increasing 60 to 70 percent a year. Mobile web adoption and social networking are also on the upswing. For example, Facebook recently announced it has crossed 100 million active users in India, only the second country after the United States to reach that milestone.

While internet growth in India is on the fast track, foreign companies targeting the region face significant challenges, including intense price competition and thin margins. In order to enhance their chances for success, companies must focus on delivering strong customer service and establishing trust, which can turn customers into repeat buyers and improve profitability. Strong web and mobile performance is a critical foundation of these efforts.

“Right now, many global internet companies view India as their next big gold rush, with companies like Flipkart, Jabong, Snapdeal, and others leading the way,” continues Daoudi. “Catchpoint has invested – and will continue to invest – in India, extending our commitment to helping our customers maximize major opportunities for business growth and revenues worldwide.”

Using Catchpoint’s web and mobile performance monitoring nodes in India, businesses can gain a realistic assessment of on-the-ground end-user web and mobile experiences, and isolate and fix problems across the region’s vast and developing web ecosystem.

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Catchpoint Opens Office in India

Catchpoint Systems announced the opening of its Bangalore office, its first office in India, and an expansion of its web and mobile performance monitoring points in India.

Catchpoint now has 13 backbone monitoring nodes in India, more than several competitors combined, in addition to three last-mile nodes. This expansion brings Catchpoint’s monitoring nodes presence to a total of 78 in the critical Asia-Pacific region, and 381 live nodes worldwide, including backbone, last mile, and wireless locations.

Catchpoint’s Bangalore office now has five employees, with plans to expand to 15 by the end of 2015. Bangalore staff will provide support to Catchpoint’s India-based customers, as well as those in the rest of the APAC and Middle East regions.

“Digital commerce in India is in its early stages, but experts agree it is set to explode,” comments Mehdi Daoudi, CEO and founder of Catchpoint Systems. “As Internet businesses gain a foothold there, the ability to ensure fast, reliable end-user experiences is paramount. Catchpoint’s web performance monitoring nodes in India will help these companies overcome web infrastructure complexity, gain customers and build business traction.”

According to the Internet and Mobile Association of India (IAMAI), today, India has 243 million internet users – more than the United States and second only to China. Gartner recently cited India as one of the fastest growing e-commerce markets in Asia-Pacific, increasing 60 to 70 percent a year. Mobile web adoption and social networking are also on the upswing. For example, Facebook recently announced it has crossed 100 million active users in India, only the second country after the United States to reach that milestone.

While internet growth in India is on the fast track, foreign companies targeting the region face significant challenges, including intense price competition and thin margins. In order to enhance their chances for success, companies must focus on delivering strong customer service and establishing trust, which can turn customers into repeat buyers and improve profitability. Strong web and mobile performance is a critical foundation of these efforts.

“Right now, many global internet companies view India as their next big gold rush, with companies like Flipkart, Jabong, Snapdeal, and others leading the way,” continues Daoudi. “Catchpoint has invested – and will continue to invest – in India, extending our commitment to helping our customers maximize major opportunities for business growth and revenues worldwide.”

Using Catchpoint’s web and mobile performance monitoring nodes in India, businesses can gain a realistic assessment of on-the-ground end-user web and mobile experiences, and isolate and fix problems across the region’s vast and developing web ecosystem.

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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 ...

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.