Cloud scalability concerns the ability of a cloud system to scale, and the cost and performance implications of doing so. As any cloud system is made up of a multitude of components, cloud scalability raises two questions:
- Is there a maximum size of any part of the system?
- If the size of a system is doubled, for example, does that mean the cost of running it (technical or otherwise) doubles, less than doubles, or more than doubles?
Scalability issues thus result in a maximum size and an optimum size (where the cost of providing service is lowest).
As part of our on-going commitment to share our knowledge of the cloud, here are two resources to help you with cloud scale.
Compute Infrastructure
Understanding issues and limitations regarding hardware, power, density, single vs. multi-tenancy, on-going management helps to develop compute infrastructure that can scale. Part one suggests how service providers can overcome these obstacles to get to market quickly and successfully. Download “A Guide to Cloud Compute Scalability” on compute scalability.
Scaling Network Resources
Provisioning of networks in a cloud environment presents different challenges to those experienced in an enterprise environment.
Two of the key differences between cloud computing and enterprise computing are scale and homogeneity. A cloud environment is normally provisioned at larger scale than an enterprise environment. Even in large enterprises, individual IT environments are likely to be smaller than cloud deployments, and though (in the nature of networks) there will be connectivity between each part, departmental or functional divisions are likely to be reflected in logical, topological or management boundaries in the networks deployed. Put simply, it would be not be unusual for different parts of the business to have different hardware, under different management. Resources are manually configured, and thus each network configuration for each component may be different, tuned to the exact requirements of the workload. In a cloud environment, the operator gains economies of scale by automatically provisioning a large number of resources in a small number of configurations, and the need to provision and (perhaps more significantly in terms of cost) maintain a wide variety of diverse configurations is reduced.
Typically at a network level this results in a wider and flatter network topology. For the network engineer, at least superficially, the network is likely to be more boring. However, looking beyond the superficial, the challenges are simply likely to be different: rather than facing a series of unique challenges based on arcane features of the network environment involved, challenges are likely to revolve around ensuring scalability of simple functions. Read A Guide to Network Scalability which goes into more scene setting details, discusses the characteristics that produce scalability challenges, and offers Flexiant’s approach to network scalability.
