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Achieving Optimum Application Performance with Intelligent Availability

Don Boxley

The thought of a dramatic decrease in application performance, let alone a system or application outage, sends shivers down even the hardiest IT professional's spine. That's because they know that in today's pace of business slow response time (or G-d forbid, just a few minutes of downtime) can equate to business loss both immediately and into the future, as well as potentially painful legal and/or regulations compliance consequences. There is no way around it. Availability has cemented itself as one of the most essential elements of any successful data center. However today, what many organizations are beginning to realize — sometimes the hard way — is that traditional methodologies and technologies for high availability (HA) have limits.

What's needed instead is a new approach that enables the dynamic transfer of workloads in IT environments based on optimizing the particular job at hand. Accomplishing this objective necessitates an inherent intelligence, flexibility, lack of downtime, and cost-effective methodology. What's required is intelligent availability, which builds upon some of the basic principles of high availability to provide the previously mentioned advantages — and more.

Intelligent availability is the future of availability and arguably the most critical component in the blueprint for creating business value through digital transformation.

Traditional High Availability

Historically, high availability (HA) has been defined quite simply as the continuous operation of applications and system components. Traditionally, this objective was accomplished in a variety of ways, accompanied by an assortment of drawbacks. One of the most common involves failovers, in which data and operations are transferred to those of a secondary system for scheduled downtime or unplanned failures.

Clustering methodologies are often leveraged with this approach to make resources between systems — including databases, servers, processors and others — available to one another. Clustering is applicable to VMs and physical servers and can help enable resilience for OS, host, and guest failures. Failovers involve a degree of redundancy, which entails maintaining HA by involving backups of system components. Redundant networking and storage options may be leveraged with VMs to encompass system components or data copies.

One of the most serious problems with many of these approaches is cost, especially as there are several instances in which HA is unnecessary. These pertain to the actual use and importance of servers, as well as additional factors pertaining to what virtualization techniques are used. Low priority servers that don't affect end users — such as those for testing — don't need HA, nor do those with recovery time objectives (RTO) significantly greater than their restore times.

Certain HA solutions, such as some of the more comprehensive hypervisor-based platforms, are indiscriminate in this regard. Therefore, users may end up paying for HA for components that don't need them. Also, traditional high availability approaches involve constant testing that can drain human and financial resources. Even worse, neglecting this duty can result in unplanned downtime. Also, arbitrarily implementing redundancy for system components broadens organization's data landscapes, resulting in more copies and potential weaknesses for security and data governance.

The Future: Digital Transformation

Many of these virtualization measures for HA are losing relevance because of digital transformation. To truly transform the way your organization conducts business with digitization technologies, you must deploy them strategically. Traditional HA methods simply do not allow for the fine-grained flexibility needed to optimize business value from digitization. Digital transformation means accounting for the varied computing environments of Linux and Windows operating systems alongside containers. It means integrating an assortment of legacy systems with newer ones specifically designed to handle the flood of big data and modern transactions systems.

Perhaps most importantly, it means aligning that infrastructure for business objectives in an adaptive way for changing domain or customer needs. Such flexibility is essential for optimizing IT processes around end user goals. The reality is most conventional methods of HA simply add to the infrastructural complexity of digital transformation, but don't address the primary need of adapting to evolving business requirements. In the face of digital transformation, organizations need to streamline their various IT systems around domain objectives, as opposed to doing the opposite, which simply decreases efficiency while increasing cost.

Enter Intelligent Availability

Intelligent availability is ideal for digital transformation because it enables workloads to always run on the best execution environment (BEV). It combines this advantage with the continuous operations of HA, but takes a fundamentally different approach in doing so. Intelligent availability takes the base idea of HA, to dedicate resources between systems to prevent downtime, and builds on it — extending it to moving them for maximizing competitive advantage. It allows organizations to move workloads between operating systems, servers, and physical and virtual environments with virtually no downtime.

The core of this approach is in the capacity of technologies that provide availability that includes intelligence to move workloads independent of one another, which is a fundamental limitation of traditional physical or virtualized approaches to workload management. By disengaging an array of system components (containers, application workloads, services and share files) without having to standardize on just one database or OS, these technologies transfer them to the environment which fits best from an IT goal and budgetary standpoint.

It's vital to remember that this judgment call is based on how to best achieve a defined business objective. Furthermore, these technologies provide this flexibility for individual instances to ensure negligible downtime and a smooth transition from one environment to another. The use cases for this instantaneous portability are abundant. Organizations can use these techniques for uninterrupted availability, integration with new or legacy systems, or the incorporation of additional data sources. Most importantly, they can do so with the assurance that the intelligent routing of the underlying technologies are selecting the optimal setting to execute workloads (i.e., BEV). Once suitably architected, the process takes no longer than a simple stop and start of a container or an application.

Intelligent Availability – the Intelligent Choice

Intelligent availability is important for a number of reasons. First, it creates all the advantages of HA, at a lower cost, and with a dramatically greater degree of efficiency. Next, it provides the agility required to capitalize on digital transformation, enabling organizations to quickly and easily move systems, applications, and workloads to where they can create the greatest competitive impact; and then when requirements change, move them back, or to someplace else.

As the saying goes, "The only constant is change." And in today's constantly changing business environment, intelligent availability delivers the agility required to not only survive, but to prevail.

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Achieving Optimum Application Performance with Intelligent Availability

Don Boxley

The thought of a dramatic decrease in application performance, let alone a system or application outage, sends shivers down even the hardiest IT professional's spine. That's because they know that in today's pace of business slow response time (or G-d forbid, just a few minutes of downtime) can equate to business loss both immediately and into the future, as well as potentially painful legal and/or regulations compliance consequences. There is no way around it. Availability has cemented itself as one of the most essential elements of any successful data center. However today, what many organizations are beginning to realize — sometimes the hard way — is that traditional methodologies and technologies for high availability (HA) have limits.

What's needed instead is a new approach that enables the dynamic transfer of workloads in IT environments based on optimizing the particular job at hand. Accomplishing this objective necessitates an inherent intelligence, flexibility, lack of downtime, and cost-effective methodology. What's required is intelligent availability, which builds upon some of the basic principles of high availability to provide the previously mentioned advantages — and more.

Intelligent availability is the future of availability and arguably the most critical component in the blueprint for creating business value through digital transformation.

Traditional High Availability

Historically, high availability (HA) has been defined quite simply as the continuous operation of applications and system components. Traditionally, this objective was accomplished in a variety of ways, accompanied by an assortment of drawbacks. One of the most common involves failovers, in which data and operations are transferred to those of a secondary system for scheduled downtime or unplanned failures.

Clustering methodologies are often leveraged with this approach to make resources between systems — including databases, servers, processors and others — available to one another. Clustering is applicable to VMs and physical servers and can help enable resilience for OS, host, and guest failures. Failovers involve a degree of redundancy, which entails maintaining HA by involving backups of system components. Redundant networking and storage options may be leveraged with VMs to encompass system components or data copies.

One of the most serious problems with many of these approaches is cost, especially as there are several instances in which HA is unnecessary. These pertain to the actual use and importance of servers, as well as additional factors pertaining to what virtualization techniques are used. Low priority servers that don't affect end users — such as those for testing — don't need HA, nor do those with recovery time objectives (RTO) significantly greater than their restore times.

Certain HA solutions, such as some of the more comprehensive hypervisor-based platforms, are indiscriminate in this regard. Therefore, users may end up paying for HA for components that don't need them. Also, traditional high availability approaches involve constant testing that can drain human and financial resources. Even worse, neglecting this duty can result in unplanned downtime. Also, arbitrarily implementing redundancy for system components broadens organization's data landscapes, resulting in more copies and potential weaknesses for security and data governance.

The Future: Digital Transformation

Many of these virtualization measures for HA are losing relevance because of digital transformation. To truly transform the way your organization conducts business with digitization technologies, you must deploy them strategically. Traditional HA methods simply do not allow for the fine-grained flexibility needed to optimize business value from digitization. Digital transformation means accounting for the varied computing environments of Linux and Windows operating systems alongside containers. It means integrating an assortment of legacy systems with newer ones specifically designed to handle the flood of big data and modern transactions systems.

Perhaps most importantly, it means aligning that infrastructure for business objectives in an adaptive way for changing domain or customer needs. Such flexibility is essential for optimizing IT processes around end user goals. The reality is most conventional methods of HA simply add to the infrastructural complexity of digital transformation, but don't address the primary need of adapting to evolving business requirements. In the face of digital transformation, organizations need to streamline their various IT systems around domain objectives, as opposed to doing the opposite, which simply decreases efficiency while increasing cost.

Enter Intelligent Availability

Intelligent availability is ideal for digital transformation because it enables workloads to always run on the best execution environment (BEV). It combines this advantage with the continuous operations of HA, but takes a fundamentally different approach in doing so. Intelligent availability takes the base idea of HA, to dedicate resources between systems to prevent downtime, and builds on it — extending it to moving them for maximizing competitive advantage. It allows organizations to move workloads between operating systems, servers, and physical and virtual environments with virtually no downtime.

The core of this approach is in the capacity of technologies that provide availability that includes intelligence to move workloads independent of one another, which is a fundamental limitation of traditional physical or virtualized approaches to workload management. By disengaging an array of system components (containers, application workloads, services and share files) without having to standardize on just one database or OS, these technologies transfer them to the environment which fits best from an IT goal and budgetary standpoint.

It's vital to remember that this judgment call is based on how to best achieve a defined business objective. Furthermore, these technologies provide this flexibility for individual instances to ensure negligible downtime and a smooth transition from one environment to another. The use cases for this instantaneous portability are abundant. Organizations can use these techniques for uninterrupted availability, integration with new or legacy systems, or the incorporation of additional data sources. Most importantly, they can do so with the assurance that the intelligent routing of the underlying technologies are selecting the optimal setting to execute workloads (i.e., BEV). Once suitably architected, the process takes no longer than a simple stop and start of a container or an application.

Intelligent Availability – the Intelligent Choice

Intelligent availability is important for a number of reasons. First, it creates all the advantages of HA, at a lower cost, and with a dramatically greater degree of efficiency. Next, it provides the agility required to capitalize on digital transformation, enabling organizations to quickly and easily move systems, applications, and workloads to where they can create the greatest competitive impact; and then when requirements change, move them back, or to someplace else.

As the saying goes, "The only constant is change." And in today's constantly changing business environment, intelligent availability delivers the agility required to not only survive, but to prevail.

The Latest

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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