Achieving Optimum Application Performance with Intelligent Availability
May 31, 2018

Don Boxley
DH2i

Share this

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.

Don Boxley is CEO and Co-Founder of DH2i
Share this

The Latest

May 21, 2019

Findings of the Digital Employee Experience survey from VMware show correlation between enabling employees with a positive digital experience (i.e., device choice/flexibility, seamless access to apps, remote work capabilities) and an organization's competitive position, revenue growth and employee sentiment ...

May 20, 2019

In today's competitive landscape, businesses must have the ability and process in place to face new challenges and find ways to successfully tackle them in a proactive manner. For years, this has been placed on the shoulders of DevOps teams within IT departments. But, as automation takes over manual intervention to increase speed and efficiency, these teams are facing what we know as IT digitization. How has this changed the way companies function over the years, and what do we have to look forward to in the coming years? ...

May 16, 2019

Although the vast majority of IT organizations have implemented a broad variety of systems and tools to modernize, simplify and streamline data center operations, many are still burdened by inefficiencies, security risks and performance gaps in their IT infrastructure as well as the excessive time it takes to manage legacy infrastructure, according to the State of IT Transformation, a report from Datrium ...

May 15, 2019

When it comes to network visibility, there are a lot of discussions about packet broker technology and the various features these solutions provide to network architects and IT managers. Packet brokers allow organizations to aggregate the data required for a variety of monitoring solutions including network performance monitoring and diagnostic (NPMD) platforms and unified threat management (UTM) appliances. But, when it comes to ensuring these solutions provide the insights required by NetOps and security teams, IT can spend an exorbitant amount of time dealing with issues around adds, moves and changes. This can have a dramatic impact on budgets and tool availability. Why does this happen? ...

May 14, 2019

Data may be pouring into enterprises but IT professionals still find most of it stuck in siloed departments and weeks away from being able to drive any valued action. Coupled with the ongoing concerns over security responsiveness, IT teams have to push aside other important performance-oriented data in order to ensure security data, at least, gets prominent attention. A new survey by Ivanti shows the disconnect between enterprise departments struggling to improve operations like automation while being challenged with a siloed structure and a data onslaught ...

May 13, 2019

A subtle, deliberate shift has occurred within the software industry which, at present, only the most innovative organizations have seized upon for competitive advantage. Although primarily driven by Artificial Intelligence (AI), this transformation strikes at the core of the most pervasive IT resources including cloud computing and predictive analytics ...

May 09, 2019

When asked who is mandated with developing and delivering their organization's digital competencies, 51% of respondents say their IT departments have a leadership role. The critical question is whether IT departments are prepared to take on a leadership role in which collaborating with other functions and disseminating knowledge and digital performance data are requirements ...

May 08, 2019

The Economist Intelligence Unit just released a new study commissioned by Riverbed that explores nine digital competencies that help organizations improve their digital performance and, ultimately, achieve their objectives. Here's a brief summary of 7 key research findings you'll find covered in detail in the report ...

May 07, 2019

Today, the overall customer scenario has digitally transformed and practically there is no limitation to the ways in which the target customers can be reached. These opportunities are throwing multiple challenges for brands and enterprises, and one of the prominent ones is to ensure Omni Channel experience for customers ...

May 06, 2019

Most businesses (92 percent of respondents) see the potential value of data and 36 percent are already monetizing their data, according to the Global Data Protection Index from Dell EMC. While this acknowledgement is positive, however, most respondents are struggling to properly protect their data ...