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Are Your Monitoring Systems Ready for the Cloud?

In a recent survey of 300 application developers, conducted by Boundary, we found that nearly 60 percent of participants had been affected by a Cloud outage. Around 72 percent of participants experienced significant costs from Cloud performance issues: thousands of dollars per incident and/or in excess of $100 per minute of downtime. This isn't stopping companies from moving to the Cloud, of course. The same survey found that 67% of developers say that their company is hosting “business-impacting” applications in the public Cloud.

Other surveys show similar concern around performance in the Cloud. The Cisco 2012 global Cloud computing survey indicated that Cloud application performance was one of the top three challenges for companies in migrating applications to the Cloud, after availability/reliability and device security.

It's easy to point the finger at the hosting companies. They're managing the infrastructure, so ultimately they must be responsible for performance, right? Not so fast.

Running services on the Internet is not foolproof. Whether due to weather, natural disasters, equipment failure and/or operator error, outages will occur. Large IaaS vendors, such as Google, Rackspace and Savvis, are operating highly interdependent, complex services based on dozens of data centers, broadband connections and thousands of servers around the world; 100 percent uptime is simply not possible. Plus, third-party providers can't see into your environment; they don't know what contingencies are playing out on your own network, third-party APIs and services that are being used or in the code that you wrote.

It's up to companies to fill in the gaps where their hosting partners will inevitably fail. And doing so requires a different type of monitoring capability than in years past. An industry luminary Michael Biddick, recently wrote about the need for a new generation of APM tools which can effectively monitor all components of the application and supporting infrastructure, including system and network performance. Next-generation APM systems must locate the underlying component causing the problem, he writes. Finally, APM systems working alone or with complementary products must suggest or take corrective action to resolve performance issues before they affect users.

This is sound advice. It's rare that one solution can accomplish all of these tasks. Most companies, including many of our customers, rely on multiple monitoring tools which work together and share information for quick identification of issues and resolution.

Importantly, these tools must be able to bring visibility across Cloud and hybrid Cloud environments. This dynamic, virtual infrastructure has proven difficult or even impossible for older legacy APM systems, designed for physical infrastructure, to manage.

As a result, systems, application and network groups often point fingers at one another, and waste time, while still not identifying which component is causing the issue.

If your company is using a legacy APM product and has invested a lot of money and time into it, you may be loathe to replace it. That's a valid consideration. It's worth talking to your vendor to determine how they can support your move to the Cloud. Will an update be coming soon to address Cloud monitoring? If not, can their product easily work with newer tools, to bridge the gap? But in general, new architectures demand new solutions.

Another trend is that APM tools are now offered as a service, just as the applications they monitor. This reduces the burden on IT to support yet another piece of software or appliance, and enables organizations to get up and running quickly on new monitoring systems as needed.

We are seeing a huge resurgence and growth in the APM market - causing a number of analysts to publish in-depth studies around market segmentation and needs. Companies want to monitor their IT infrastructures from an “application first” or top-down perspective, which is rendering traditional bottom-up tools as legacy. Something that everyone appears to agree on is that application monitoring is not a one-size-fits-all situation and customers should understand their requirements fully before selecting their partners. The good news is that with tools being offered as SaaS and on shorter-term subscription contracts, the cost of adoption and change has lowered dramatically.

We are seeing modern applications and Cloud computing drive huge growth in the new generation of solutions while traditional/legacy solutions are withering away. We are also seeing a clear distinction emerging between developer-focused solutions and operations-focused solutions, as follows:

Developer-focused solutions answer the question: “Where in the code is my problem area?” If the problem is not in the code, then of course these tools offer limited help.

Operations-focused solutions answer the question: “Where is my problem?” These tools must cover 100% of your environment but don’t go as deep in code analysis.

It’s a transitional time for the APM technology market. More than perhaps ever before, companies are realizing that to succeed in the massive change of placing IT services in the Cloud, an investment in comprehensive and always-on monitoring tools is a must. Otherwise, the Cloud can backfire. Users and managers will not quickly forget if their apps crash or sensitive data is lost forever. Selecting a next-gen APM tool today that is designed for monitoring modern, distributed, Web apps and services will help a company best prepare for a transition to the new enterprise computing environment underway right now.

ABOUT Gary Read

Gary Read, CEO and President of Boundary, previously served as CEO of Nimsoft, providers of the award-winning Cloud monitoring solution, where he grew the business from zero to over $100 million in bookings and 300 people. As CEO, Gary led all aspects of the company including product, marketing, sales, support, and finance, guiding Nimsoft to a successful acquisition by CA for $350 million. Nimsoft experienced significant worldwide growth, with approximately 1,000 customers in 36 countries. Prior to Nimsoft, Gary held executive positions at BMC Software, Riversoft, and Boole and Babbage.

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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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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.

Are Your Monitoring Systems Ready for the Cloud?

In a recent survey of 300 application developers, conducted by Boundary, we found that nearly 60 percent of participants had been affected by a Cloud outage. Around 72 percent of participants experienced significant costs from Cloud performance issues: thousands of dollars per incident and/or in excess of $100 per minute of downtime. This isn't stopping companies from moving to the Cloud, of course. The same survey found that 67% of developers say that their company is hosting “business-impacting” applications in the public Cloud.

Other surveys show similar concern around performance in the Cloud. The Cisco 2012 global Cloud computing survey indicated that Cloud application performance was one of the top three challenges for companies in migrating applications to the Cloud, after availability/reliability and device security.

It's easy to point the finger at the hosting companies. They're managing the infrastructure, so ultimately they must be responsible for performance, right? Not so fast.

Running services on the Internet is not foolproof. Whether due to weather, natural disasters, equipment failure and/or operator error, outages will occur. Large IaaS vendors, such as Google, Rackspace and Savvis, are operating highly interdependent, complex services based on dozens of data centers, broadband connections and thousands of servers around the world; 100 percent uptime is simply not possible. Plus, third-party providers can't see into your environment; they don't know what contingencies are playing out on your own network, third-party APIs and services that are being used or in the code that you wrote.

It's up to companies to fill in the gaps where their hosting partners will inevitably fail. And doing so requires a different type of monitoring capability than in years past. An industry luminary Michael Biddick, recently wrote about the need for a new generation of APM tools which can effectively monitor all components of the application and supporting infrastructure, including system and network performance. Next-generation APM systems must locate the underlying component causing the problem, he writes. Finally, APM systems working alone or with complementary products must suggest or take corrective action to resolve performance issues before they affect users.

This is sound advice. It's rare that one solution can accomplish all of these tasks. Most companies, including many of our customers, rely on multiple monitoring tools which work together and share information for quick identification of issues and resolution.

Importantly, these tools must be able to bring visibility across Cloud and hybrid Cloud environments. This dynamic, virtual infrastructure has proven difficult or even impossible for older legacy APM systems, designed for physical infrastructure, to manage.

As a result, systems, application and network groups often point fingers at one another, and waste time, while still not identifying which component is causing the issue.

If your company is using a legacy APM product and has invested a lot of money and time into it, you may be loathe to replace it. That's a valid consideration. It's worth talking to your vendor to determine how they can support your move to the Cloud. Will an update be coming soon to address Cloud monitoring? If not, can their product easily work with newer tools, to bridge the gap? But in general, new architectures demand new solutions.

Another trend is that APM tools are now offered as a service, just as the applications they monitor. This reduces the burden on IT to support yet another piece of software or appliance, and enables organizations to get up and running quickly on new monitoring systems as needed.

We are seeing a huge resurgence and growth in the APM market - causing a number of analysts to publish in-depth studies around market segmentation and needs. Companies want to monitor their IT infrastructures from an “application first” or top-down perspective, which is rendering traditional bottom-up tools as legacy. Something that everyone appears to agree on is that application monitoring is not a one-size-fits-all situation and customers should understand their requirements fully before selecting their partners. The good news is that with tools being offered as SaaS and on shorter-term subscription contracts, the cost of adoption and change has lowered dramatically.

We are seeing modern applications and Cloud computing drive huge growth in the new generation of solutions while traditional/legacy solutions are withering away. We are also seeing a clear distinction emerging between developer-focused solutions and operations-focused solutions, as follows:

Developer-focused solutions answer the question: “Where in the code is my problem area?” If the problem is not in the code, then of course these tools offer limited help.

Operations-focused solutions answer the question: “Where is my problem?” These tools must cover 100% of your environment but don’t go as deep in code analysis.

It’s a transitional time for the APM technology market. More than perhaps ever before, companies are realizing that to succeed in the massive change of placing IT services in the Cloud, an investment in comprehensive and always-on monitoring tools is a must. Otherwise, the Cloud can backfire. Users and managers will not quickly forget if their apps crash or sensitive data is lost forever. Selecting a next-gen APM tool today that is designed for monitoring modern, distributed, Web apps and services will help a company best prepare for a transition to the new enterprise computing environment underway right now.

ABOUT Gary Read

Gary Read, CEO and President of Boundary, previously served as CEO of Nimsoft, providers of the award-winning Cloud monitoring solution, where he grew the business from zero to over $100 million in bookings and 300 people. As CEO, Gary led all aspects of the company including product, marketing, sales, support, and finance, guiding Nimsoft to a successful acquisition by CA for $350 million. Nimsoft experienced significant worldwide growth, with approximately 1,000 customers in 36 countries. Prior to Nimsoft, Gary held executive positions at BMC Software, Riversoft, and Boole and Babbage.

Hot Topics

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.