Ultimately, if we refer to the enterprise model as a cloud-like delivery model or as a private cloud, that doesn’t change the fact that enterprises have significant drivers to introduce it in their data centers in order to:
• Support business agility and respond quicker to business needs when hosting enterprise workloads, which characteristics (I/O and CPU bound, infrastructure-level resiliency) may be better supported by custom-tailored system infrastructures in private data centers
• Ensure compliancy with stringent corporate security policies and keep sensitive data on-premise
• Speed up infrastructure resource provisioning and application deployment
• Have full control over problem resolution
• Decrease overall complexity of managing enterprise data centers.
According to a Forrester survey, 55 percent of North American and European enterprises plan to prioritize building an internal private cloud in 2014 (see “Four Common Approaches to Private Cloud” under “Resources” at the end of this article). Given the real demand for a cloud-like delivery model in private data centers, it would be helpful to clear the ambiguity around “private cloud” and have a working definition of private cloud architecture that reflects the current realities and focuses on addressing current enterprise pain points:
• Accommodating workloads with different QoS characteristics:
o Traditional workloads that require high availability on the infrastructure level
o Scale-out, distributed workloads that require elasticity but don’t rely on the underlying infrastructure for high availability.
• On-demand, self-service access to pools of infrastructure resources for enterprise users while supporting multitenancy. There are opinions that private clouds are “single-tenant,” but most enterprise insiders would tell you that enterprises are very much multitenant environments and require a high degree of isolation between workloads due to both technical and organizational reasons.
Two Architectural Models for Private Cloud Infrastructures
Many existing enterprise private cloud strategies appear to be extensions or a natural evolution of virtualization strategies. After all, it’s normal to want to use existing virtualization platforms, making the most of investments and supporting the traditional workloads that currently prevail in enterprise portfolios. However, traditional DR solutions for business continuity typically require deploying data and applications across multiple data centers using an active-active or, more often, an active-passive standby approach. Additionally, hardware estimations are normally done for peak usage. Unfortunately, this strategy usually results in numerous resources sitting idle. Focusing just on establishing and maintaining redundant enterprise hardware across multiple data centers to support traditional enterprise workloads may be a costly, complex and unfulfilling proposition.
Times are changing. Newer, distributed types of scale-out workloads, such as web and mobile applications and NoSQL, have started to make their way into enterprise portfolios. For many enterprises, it may be prudent to balance and augment cloud strategies using a workload-centric approach.
The workload-centric approach will likely lead private cloud owners to consider different high-availability strategies, including an approach where the uptime metrics are met through replication and failure mitigation provided by the software capable of accommodating infrastructure failures.
IBM’s eXtreme Scale, which offers in-memory caching, is an example of an elastic, middleware-layer product that’s architected for software-level fault tolerance (see the earlier referenced article). In other words, enterprises may want to take a page from the book of the dominant cloud providers such as AWS and develop a more fine-grained approach to resiliency and high availability, embracing distributed, scale-out types of workloads (see Figure 1).