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5 Characteristics of Cloud Services that Impact Management Tools

Julie Craig

EMA sees cloud computing as a fundamental game-changer, which will likely have an impact equivalent to that of the Internet on ISVs and IT organizations alike.

When considering the cloud from the perspective of the application, it becomes clear that cloud-based applications must be supported with the same rigor as those hosted internally. Regardless of the delivery mechanism, IT organizations still have a responsibility to end-user customers for application quality, availability, and performance.

Assessing this responsibility in context to the five characteristics outlined below – the main factors EMA has identified that distinguish cloud-based deployments – can help clarify requirements for cloud-related enterprise management toolsets.

1. Convenient, On-Demand Access

Convenient, on-demand access implies application availability, basically an assurance that the cloud-based service is accessible when the customer needs it. It also implies that applications are designed with easy access in mind. For applications developed in-house to run on public or private cloud, ensuring on-demand access requires toolsets that support application quality throughout the application lifecycle. It also requires tools capable of monitoring and managing application performance and availability from the user perspective.

2. Shared Resource Pool

For either public or private clouds to deliver economies of scale, a shared resource pool is critical. The idea is that different customers will have different resource requirements at different times. A shared resource pool — particularly when combined with the next capability (rapid provisioning and release) — means that customers experiencing peak resource requirements have access to pooled resources because other customers are running at non-peak levels.

This point and the next presuppose an ability to precisely assess utilization trends against capacity. Developing this capability requires management solutions capable of assessing and tracking the capacity of physical and virtual resources in context with one another, and with real-time and trend-based utilization.

3. Rapid Provisioning and Release of Resources

Rapid provisioning and release of resources are critical capabilities, and methodologies for release are equally important as — if not more important than — for acquisition. Rapid provisioning presupposes the use of products capable of provisioning applications on demand based on preexisting models and templates. Products (and processes) that support and enforce the governance of provisioning and release functions are also critical.

4. Minimal Service Provider Interaction

The average corporate user requesting access to an internally-hosted platform or service interacts one or more times with IT. However, when the same user seeks access to a cloud service, he or she expects to access the service directly, without an intermediary contact.

This ease of access has been one of the factors contributing to the cloud wildfire, as departmental credit cards (versus budgeted line items) have become the new “coin of the realm” for public cloud services. However, this de-facto de-centralization is also raising governance, control, and security issues, which again drives requirements for new kinds of cloud-related service catalog and service portfolio management solutions.

5. Minimal Management Effort

Public and private clouds, of course, require different levels of management effort, but the responsibilities of IT organizations are similar in both cases.

For public clouds, management effort, though “minimal,” is still a consideration. The base services delivered by public cloud providers are managed by the vendor. This is true whether the product is Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS). The business customer still has a responsibility to choose the vendor that most closely matches business requirements and to monitor services to make sure they are delivered at contracted levels.

Private cloud requires significant management effort, typically by internal IT. It also requires toolsets that support all aspects of the application lifecycle from “cradle to grave.” In addition, since the majority of private clouds are built using virtualization, supporting them also requires toolsets that “understand” and have visibility to virtual environments.

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The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

5 Characteristics of Cloud Services that Impact Management Tools

Julie Craig

EMA sees cloud computing as a fundamental game-changer, which will likely have an impact equivalent to that of the Internet on ISVs and IT organizations alike.

When considering the cloud from the perspective of the application, it becomes clear that cloud-based applications must be supported with the same rigor as those hosted internally. Regardless of the delivery mechanism, IT organizations still have a responsibility to end-user customers for application quality, availability, and performance.

Assessing this responsibility in context to the five characteristics outlined below – the main factors EMA has identified that distinguish cloud-based deployments – can help clarify requirements for cloud-related enterprise management toolsets.

1. Convenient, On-Demand Access

Convenient, on-demand access implies application availability, basically an assurance that the cloud-based service is accessible when the customer needs it. It also implies that applications are designed with easy access in mind. For applications developed in-house to run on public or private cloud, ensuring on-demand access requires toolsets that support application quality throughout the application lifecycle. It also requires tools capable of monitoring and managing application performance and availability from the user perspective.

2. Shared Resource Pool

For either public or private clouds to deliver economies of scale, a shared resource pool is critical. The idea is that different customers will have different resource requirements at different times. A shared resource pool — particularly when combined with the next capability (rapid provisioning and release) — means that customers experiencing peak resource requirements have access to pooled resources because other customers are running at non-peak levels.

This point and the next presuppose an ability to precisely assess utilization trends against capacity. Developing this capability requires management solutions capable of assessing and tracking the capacity of physical and virtual resources in context with one another, and with real-time and trend-based utilization.

3. Rapid Provisioning and Release of Resources

Rapid provisioning and release of resources are critical capabilities, and methodologies for release are equally important as — if not more important than — for acquisition. Rapid provisioning presupposes the use of products capable of provisioning applications on demand based on preexisting models and templates. Products (and processes) that support and enforce the governance of provisioning and release functions are also critical.

4. Minimal Service Provider Interaction

The average corporate user requesting access to an internally-hosted platform or service interacts one or more times with IT. However, when the same user seeks access to a cloud service, he or she expects to access the service directly, without an intermediary contact.

This ease of access has been one of the factors contributing to the cloud wildfire, as departmental credit cards (versus budgeted line items) have become the new “coin of the realm” for public cloud services. However, this de-facto de-centralization is also raising governance, control, and security issues, which again drives requirements for new kinds of cloud-related service catalog and service portfolio management solutions.

5. Minimal Management Effort

Public and private clouds, of course, require different levels of management effort, but the responsibilities of IT organizations are similar in both cases.

For public clouds, management effort, though “minimal,” is still a consideration. The base services delivered by public cloud providers are managed by the vendor. This is true whether the product is Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS). The business customer still has a responsibility to choose the vendor that most closely matches business requirements and to monitor services to make sure they are delivered at contracted levels.

Private cloud requires significant management effort, typically by internal IT. It also requires toolsets that support all aspects of the application lifecycle from “cradle to grave.” In addition, since the majority of private clouds are built using virtualization, supporting them also requires toolsets that “understand” and have visibility to virtual environments.

Hot Topics

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...