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Don't Get Caught Up In Cloud Monitoring Hype

Dirk Paessler

The cloud monitoring market has been on fire in the early part of 2015, between acquisitions and a VC spending spree. The money is truly flying fast in Silicon Valley and beyond. But money isn’t everything, and while cloud monitoring has its place, it’s not a panacea.
 
It’s easy to get caught up in the hype-cycle, but cloud monitoring startups face some serious headwinds, including the fact that they are solving a problem many businesses simply don’t have. Many of these young companies have solved relatively easy problems – the ability to monitor cloud workloads. They have capitalized on a variety of trends in computing, notably the movement towards cloud applications and the Internet of Things. They have generated much publicity, achieving “next big thing” status, but in many ways they’re missing the point. Hardware matters, LAN matters, and both will continue to matter. No one is saying that moving to the cloud is a bad idea – on the contrary, it makes total sense in many cases, and cloud monitoring has a role. But, not everything can be displaced.

Networks can contain literally millions of switches, servers, firewalls and more – and a lot of that hardware is out of date. Knowing how to monitor everything on the network is critical – it’s more than just being able to connect to the APIs of a few leading cloud providers and call it a day. Businesses rely on hardware, and the simple fact of the matter is most hardware on the planet is old. Cloud monitoring is optimized to handle the latest and greatest, but when it comes down to it networking hardware is both business critical, and in many cases, quite dated.

One of the most talked about topics in monitoring is the Internet of Things, and it is here that cloud monitoring shows its weakness. One of the most exciting aspects of the Internet of Things is its potential to transform the industrial economy. While many focus on how IoT will empower consumers to control their thermostat and refrigerator remotely, the connected factory is truly transformational. And, the connected factory is a perfect illustration of why monitoring is not about cloud, but about a willingness to do a lot of dirty work.

The connected factory will not run on 21st century technology alone. In all industrial businesses, be it manufacturing or energy production, operations are dependent upon legacy hardware, including some systems that are homegrown. SCADA systems are a perfect example. These systems are the operational backbone of the business, and they are expensive to implement – many years have to go by before the costs are amortized. These systems will need to be connected, and it takes deep institutional knowledge and years of hardware experience to do it successfully. Monitoring providers need to offer a way for end users to work with old hardware, be it through custom designed sensors or an easy-to-use template.

Additionally, there are just some processes that require a LAN connection. Factories will never move all workloads to the cloud, it is just not possible. Machines must be connected by secure, LAN connections, over fiber, copper or Wi-Fi, with ultra-high bandwidth and reliability in the five-nines range. Cloud systems simply cannot offer that at present time. No factory owner is going to accept lower availability or connectivity problems that are out of his control. Cloud outages happen, but no one is ever going to walk off the factory floor because Amazon is down.

Network monitoring has required, and will continue to require, “boots on the ground”. Monitoring software needs to be able to communicate with everything, whether it’s AWS or a 25-year-old SCADA system, regardless of connection quality. IT departments need to be able to monitor everything from cloud applications to valves in an oil pipeline or a power station in a remote area. It takes many years of expertise to develop tools that can accomplish this, much more than it takes to link up with an API. Most of the internet is run off of very old servers and switches – understanding the places where monitoring has been is critical to its future.

Dirk Paessler is CEO and Founder of Paessler AG.

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Don't Get Caught Up In Cloud Monitoring Hype

Dirk Paessler

The cloud monitoring market has been on fire in the early part of 2015, between acquisitions and a VC spending spree. The money is truly flying fast in Silicon Valley and beyond. But money isn’t everything, and while cloud monitoring has its place, it’s not a panacea.
 
It’s easy to get caught up in the hype-cycle, but cloud monitoring startups face some serious headwinds, including the fact that they are solving a problem many businesses simply don’t have. Many of these young companies have solved relatively easy problems – the ability to monitor cloud workloads. They have capitalized on a variety of trends in computing, notably the movement towards cloud applications and the Internet of Things. They have generated much publicity, achieving “next big thing” status, but in many ways they’re missing the point. Hardware matters, LAN matters, and both will continue to matter. No one is saying that moving to the cloud is a bad idea – on the contrary, it makes total sense in many cases, and cloud monitoring has a role. But, not everything can be displaced.

Networks can contain literally millions of switches, servers, firewalls and more – and a lot of that hardware is out of date. Knowing how to monitor everything on the network is critical – it’s more than just being able to connect to the APIs of a few leading cloud providers and call it a day. Businesses rely on hardware, and the simple fact of the matter is most hardware on the planet is old. Cloud monitoring is optimized to handle the latest and greatest, but when it comes down to it networking hardware is both business critical, and in many cases, quite dated.

One of the most talked about topics in monitoring is the Internet of Things, and it is here that cloud monitoring shows its weakness. One of the most exciting aspects of the Internet of Things is its potential to transform the industrial economy. While many focus on how IoT will empower consumers to control their thermostat and refrigerator remotely, the connected factory is truly transformational. And, the connected factory is a perfect illustration of why monitoring is not about cloud, but about a willingness to do a lot of dirty work.

The connected factory will not run on 21st century technology alone. In all industrial businesses, be it manufacturing or energy production, operations are dependent upon legacy hardware, including some systems that are homegrown. SCADA systems are a perfect example. These systems are the operational backbone of the business, and they are expensive to implement – many years have to go by before the costs are amortized. These systems will need to be connected, and it takes deep institutional knowledge and years of hardware experience to do it successfully. Monitoring providers need to offer a way for end users to work with old hardware, be it through custom designed sensors or an easy-to-use template.

Additionally, there are just some processes that require a LAN connection. Factories will never move all workloads to the cloud, it is just not possible. Machines must be connected by secure, LAN connections, over fiber, copper or Wi-Fi, with ultra-high bandwidth and reliability in the five-nines range. Cloud systems simply cannot offer that at present time. No factory owner is going to accept lower availability or connectivity problems that are out of his control. Cloud outages happen, but no one is ever going to walk off the factory floor because Amazon is down.

Network monitoring has required, and will continue to require, “boots on the ground”. Monitoring software needs to be able to communicate with everything, whether it’s AWS or a 25-year-old SCADA system, regardless of connection quality. IT departments need to be able to monitor everything from cloud applications to valves in an oil pipeline or a power station in a remote area. It takes many years of expertise to develop tools that can accomplish this, much more than it takes to link up with an API. Most of the internet is run off of very old servers and switches – understanding the places where monitoring has been is critical to its future.

Dirk Paessler is CEO and Founder of Paessler AG.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...