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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Networks can contain literally millions of switches, servers, firewalls and more – and a lot of that hardware is out of date.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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

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AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...