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Cloud Ahead – Managing Change in the New Normal

Employees are no longer bound to a physical desk in the office due to moving to the cloud
Dennis Damen
Login VSI

The cloud has recently proven to be a vital tool for many organizations to deal with the COVID-19 pandemic by enabling employees to work from home. To me, COVID-19 has clearly shown that work doesn't need to happen at the office. It has strengthened our belief that working from home is going to be the norm for many.

The move to the cloud introduces many technical challenges, even though we're taking away some of the complexity of maintaining an extensive IT infrastructure. But we're also adding a new layer of complexity to an already complex IT landscape. Besides the technical shift, we'll also see a change in responsibility and accountability.

The Desktop is Not the Hard Part

Imagine moving your desktops over to the Windows Virtual Desktop (WVD) or Citrix Cloud. All of a sudden, Microsoft or Citrix are responsible for delivering the desktop that runs your applications to support your business. How far does the responsibility of the vendor reach? Is it just the infrastructure, or are they also responsible for the applications' availability and performance? Am I — as an IT director — still accountable, and how can I provide insights about this?

At the same time, we see an ever-increasing rate of change. To be able to handle this increased rate of growth, an organization shouldn't merely lift and shift their workloads to the cloud. Instead, they should also review and modernize their operations. Agile and DevOps have been around for quite some time in the realm of software development. We believe organizations should also incorporate these concepts into their IT management processes so they can facilitate change instead of controlling it.

Modernize Change Management

Guaranteeing the availability and user experience of the digital workplace and, thus, with employees' productivity and the continuity of the company should be the highest priority. On the one hand, by supporting the change management process with data about the impact a change will have on production systems and automating change in the digital workplace. On the other hand, by continuously testing production environments, including desktop applications (whether in the Cloud) for availability and performance  and reporting on this clearly and simply.

Towards the future, we want to give substance to our "DevOps for Desktops" concept in which we want to plot the thinking of DevOps onto the digital workplace. Our vision is that deep integration of our automation and test platforms enables the customer to implement changes faster and with higher quality, both on-premises and in the cloud.

Dennis Damen is Sr. Product Manager at Login VSI

Hot Topics

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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 ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

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 ...

Cloud Ahead – Managing Change in the New Normal

Employees are no longer bound to a physical desk in the office due to moving to the cloud
Dennis Damen
Login VSI

The cloud has recently proven to be a vital tool for many organizations to deal with the COVID-19 pandemic by enabling employees to work from home. To me, COVID-19 has clearly shown that work doesn't need to happen at the office. It has strengthened our belief that working from home is going to be the norm for many.

The move to the cloud introduces many technical challenges, even though we're taking away some of the complexity of maintaining an extensive IT infrastructure. But we're also adding a new layer of complexity to an already complex IT landscape. Besides the technical shift, we'll also see a change in responsibility and accountability.

The Desktop is Not the Hard Part

Imagine moving your desktops over to the Windows Virtual Desktop (WVD) or Citrix Cloud. All of a sudden, Microsoft or Citrix are responsible for delivering the desktop that runs your applications to support your business. How far does the responsibility of the vendor reach? Is it just the infrastructure, or are they also responsible for the applications' availability and performance? Am I — as an IT director — still accountable, and how can I provide insights about this?

At the same time, we see an ever-increasing rate of change. To be able to handle this increased rate of growth, an organization shouldn't merely lift and shift their workloads to the cloud. Instead, they should also review and modernize their operations. Agile and DevOps have been around for quite some time in the realm of software development. We believe organizations should also incorporate these concepts into their IT management processes so they can facilitate change instead of controlling it.

Modernize Change Management

Guaranteeing the availability and user experience of the digital workplace and, thus, with employees' productivity and the continuity of the company should be the highest priority. On the one hand, by supporting the change management process with data about the impact a change will have on production systems and automating change in the digital workplace. On the other hand, by continuously testing production environments, including desktop applications (whether in the Cloud) for availability and performance  and reporting on this clearly and simply.

Towards the future, we want to give substance to our "DevOps for Desktops" concept in which we want to plot the thinking of DevOps onto the digital workplace. Our vision is that deep integration of our automation and test platforms enables the customer to implement changes faster and with higher quality, both on-premises and in the cloud.

Dennis Damen is Sr. Product Manager at Login VSI

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 ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

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 ...