Cloud Data Centers And Cost Modeling: A Complete Guide To Planning, Designing And Building A Cloud D

Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge. The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous. In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making.

Cloud Data Centers And Cost Modeling: A Complete Guide To Planning, Designing And Building A Cloud D

In order to set up the cloud paradigm for cost modeling, we need a right definition of cloud computing to guide our diversified considerations and innovative thinking about cost modeling. One of practical approaches is to ask three basic questions:

Virtualization enables cloud providers to make maximum use of their data center resources. Not surprisingly, many corporations have adopted the cloud delivery model for their on-premises infrastructure so they can realize maximum utilization and cost savings vs. traditional IT infrastructure and offer the same self-service and agility to their end-users.

Disaster recovery and business continuity have always been a natural for cloud because cloud provides cost-effective redundancy to protect data against system failures and the physical distance required to recover data and applications in the event of a local outage or disaster. All of the major public cloud providers offer Disaster-Recovery-as-a-Service (DRaaS).

Private cloud services are delivered from a business's data center to internal users. With a private cloud, an organization builds and maintains its own underlying cloud infrastructure. This model offers the versatility and convenience of the cloud, while preserving the management, control and security common to local data centers. Internal users might or might not be billed for services through IT chargeback. Common private cloud technologies and vendors include VMware and OpenStack.

Generally, when contemplating cloud adoption, many enterprises have been mainly focused on new cloud-native applications -- that is, designing and building applications specifically intended to use cloud services. They haven't been willing to move their most mission-critical apps into the public cloud. However, these enterprises are now beginning to realize that the cloud is ready for the enterprise if they select the right cloud platforms, i.e., those that have a history of serving the needs of the enterprise.

Many vendors and cloud providers offer Backup as a Service (BaaS) solutions, where you can push local data to a public or private cloud and in case of disaster, recover data back from the cloud. BaaS solutions are easy to use and have the strong advantage that data is saved in a remote location. However, if using a public cloud, you need to ensure compliance with relevant regulations and standards, and consider that over time, data storage costs in the cloud will be much higher than the cost of deploying similar storage on-premises.

When using cloud providers, you have access to a variety of storage services. Cloud providers charge a flat price per Gigabyte, but costs can start to add up for frequent access. There are multiple tools that let you backup data to S3 automatically, both from within the cloud and from on-premise machines.

Overlapping with PaaS, serverless computing focuses on building app functionality without spending time continually managing the servers and infrastructure required to do so. The cloud provider handles the setup, capacity planning, and server management for you. Serverless architectures are highly scalable and event-driven, only using resources when a specific function or trigger occurs.

Modern data centers are very different than they were just a short time ago. Infrastructure has shifted from traditional on-premises physical servers to virtual networks that support applications and workloads across pools of physical infrastructure and into a multicloud environment.

In this era, data exists and is connected across multiple data centers, the edge, and public and private clouds. The data center must be able to communicate across these multiple sites, both on-premises and in the cloud. Even the public cloud is a collection of data centers. When applications are hosted in the cloud, they are using data center resources from the cloud provider.

Organizations can choose to build and maintain their own hybrid cloud data centers, lease space within colocation facilities (colos), consume shared compute and storage services, or use public cloud-based services. The net effect is that applications today no longer reside in just one place. They operate in multiple public and private clouds, managed offerings, and traditional environments. In this multicloud era, the data center has become vast and complex, geared to drive the ultimate user experience.

One of the first steps to consider before migrating data to the cloud is to determine the use case that the public cloud will serve. Will it be used for disaster recovery? DevOps? Hosting enterprise workloads by completely shifting to the cloud? Or will a hybrid approach work best for your deployment.

SaaS is the largest chunk of cloud spending simply because the variety of applications delivered via SaaS is huge, from CRM such as Salesforce, through to Microsoft's Office 365. And while the whole market is growing at a furious rate, it's the IaaS and PaaS segments that have consistently grown at much faster rates, according to analyst IDC: "This highlights the increasing reliance of enterprises on a cloud foundation built on cloud infrastructure, software-defined data, compute and governance solutions as a Service, and cloud-native platforms for application deployment for enterprise IT internal applications." IDC predicts that IaaS and PaaS will continue growing at a higher rate than the overall cloud market "as resilience, flexibility, and agility guide IT platform decisions".

For startups that plan to run all their systems in the cloud, getting started is pretty simple. But the majority of companies, it is not so simple: with existing applications and data, they need to work out which systems are best left running as they are, and which to start moving to cloud infrastructure. This is a potentially risky and expensive move, and migrating to the cloud could cost companies more if they underestimate the scale of such projects.

Secondly, there is the issue of data sovereignty. Many companies, particularly in Europe, have to worry about where their data is being processed and stored. European companies are worried that, for example, if their customer data is being stored in data centres in the US or (owned by US companies), it could be accessed by US law enforcement. As a result, the big cloud vendors have been building out a regional data centre network so that organizations can keep their data in their own region.

Google uses a similar model, dividing its cloud-computing resources into regions that are then subdivided into zones, which include one or more datacenters from which customers can run their services. It currently over eight zones: Google recommends customers deploy applications across multiple zones and regions to help protect against unexpected failures.

Cloud computing is reaching the point where it is likely to account for more of enterprise tech spending than the traditional forms of delivering applications and services in-house that have been around for decades. However, use of the cloud is only likely to climb as organisations get more comfortable with the idea of their data being somewhere other than a server in the basement. And now cloud-computing vendors are increasingly pushing cloud computing as an agent of digital transformation instead of focusing simply on cost. Moving to the cloud can help companies rethink business processes and accelerate business change, goes the argument, by helping to break down data any organisational silos. Some companies that need to boost momentum around their digital transformation programmes might find this argument appealing; others may find enthusiasm for the cloud waning as the costs of making the switch add up.

Private cloud is customizable to meet the unique business and security needs of the organization. With greater visibility and control into the infrastructure, organizations can operate compliance-sensitive IT workloads without compromising on the security and performance previously only achieved with dedicated on-premise data centers.

In contrast to these supported HA options, the following diagram illustrates unsupported or ill-advised component architectures spanning geographically distant data centers or cloud regions. These diagrams provide neither effective HA nor DR due to the distance and latency between components. Platform stability issues can also result due to latency concerns in such a deployment. Furthermore, the stretching of administrative boundaries between sites does not align to DR principals. We have seen similar conceptual designs by customers in the past.