What is cloud architecture? Design and implementation

How does cloud architecture work?

There are many ways to describe cloud architecture, but the best way to conceptualize a cloud is through its various layers. Complete cloud architecture is not a single concept. Resources and services are accessed using a client-server-style approach of request and response through the following:

1. Back end. As with normal client-server computing, almost all the resources and services are hosted on the back end -- or the server side -- where the cloud provider builds and operates its proprietary technology infrastructure. This is where the provider runs its servers, storage, virtualization frameworks, and management and monitoring applications.
2. Front end. The front end -- or the client side -- user interface is the mechanism where users access and interact with the cloud provider's back end. In most cases, this is a web portal established through a common browser enabling users to log in, provision new cloud architecture components for use, monitor the availability and performance of those components, handle billing and perform other user-side tasks.
3. Middleware. Front ends and back ends are typically connected through middleware that translates front-end requests into back-end tasks and similarly translates back-end actions into front-end responses. Cloud providers typically use one or more application programming interfaces as middleware. APIs establish a standardized and secure means of interaction. For example, when a user on a front-end browser creates a new storage resource on the cloud provider's back end, that action is facilitated through API middleware.
4. Network. Finally, the front end accesses the middleware and back end through a network involving the local area network and the full extent of the internet -- the wide area network. Although most cloud architectures can be invoked and operated with little network bandwidth and some latency, greater bandwidth and lower latency may be necessary for more intensive tasks, such as moving files from the local data center to a storage resource created in the cloud.

These four principal layers can be expressed in three major cloud architecture models:

1. Infrastructure as a service (IaaS). This is a flexible and granular cloud computing model. Users can provide and relate specific resources, services and applications to design a computing environment that best supports the cloud-deployed applications. Users directly control the architecture with IaaS.
2. Platform as a service (PaaS). This cloud computing model provides users with access to specific frameworks or tool sets intended to offer comprehensive capabilities directly from the cloud without the need to install or maintain those frameworks and tools in on-premises data centers. For example, busy software developers might use a DevOps PaaS with a comprehensive tool set that supports and manages a complete workflow.
3. Software as a service (SaaS). This cloud computing model offers users access to a specific application managed and maintained through a provider. For example, a business may use an accounting, human resources or design tool delivered as SaaS, rather than purchasing, installing and maintaining that tool locally.

In every major cloud architecture model, the primary elements of front end, middleware, back end and network are present. The only difference in each cloud model is the level of user control exerted over the provider's infrastructure.

Components of cloud architecture

A cloud architecture involves numerous components, including the following:

• Infrastructure or resources. This represents a cloud's hardware layer, which includes servers, storage, network gear, cabling and all other elements found in a traditional data center, such as hardware firewalls and load balancers. The global footprint occupied by cloud providers is marked with data center locations.
• Virtualization. Virtualization abstracts the physical hardware from services, applications and users to enable two major advantages over physical resources. First, virtualization enables greater hardware utilization, such as hosting multiple VMs on the same physical server -- and better efficiency. Second, virtualization enables resource aggregation and pooling, letting resources be provisioned and used wherever located within the cloud provider's physical infrastructure.
• Middleware. Middleware is fundamentally a software layer that enables users to interact with the cloud provider's resources, services and applications. APIs are the typical middleware for cloud environments, providing the standardized set of commands and capabilities used to interact with the cloud provider. Although other software, such as databases and communication applications, may be seen as middleware in traditional enterprise data centers, those elements are typically treated as services by cloud providers.
• Automation and orchestration. Provisioning and using a cloud can involve countless processes, policies and workflows -- all impossible to invoke manually. Automation and orchestration tools are critical components of a cloud infrastructure that can translate user commands into actionable events capable of handling any necessary actions on the back end. For example, automation tools can be critical for cloud tasks, such as autoscaling, where cloud resources are added or released based on demand.
• Management. Users demand extensive insight into the cloud infrastructure to ensure that provisioned resources are used and billed properly so that appropriate value is delivered to the user. Management tools offer insights into cloud capacity and performance, enabling users to track utilization, make and change deployments, move data, handle backups and implement disaster recovery (DR).
• Services. Clouds are often far more than virtualized hardware, and providers routinely offer a wide assortment of applications intended to deliver useful services to cloud users. For example, Kubernetes services can be vital for container users, provider-run databases can offer critical support for enterprise applications deployed to the cloud and machine learning services can help business users develop artificial intelligence platforms.

Types of cloud architecture

Four principal cloud architecture models can serve businesses:

1. Public cloud. This is the most common and accepted cloud architecture model and is typically the default consideration for cloud computing. The cloud provider owns and operates the resources and services, offering them commercially to users who share the provider's common infrastructure in a multi-tenant environment. Public cloud offers global availability, high scalability and a manageable pay-as-you-go cloud computing cost structure.
2. Private cloud. This cloud architecture model focuses on delivering resources and services that are owned and operated by the business itself, rather than a third-party provider, while still being delivered in the same manner as a public cloud. This offers better security and customization than the public cloud, but it requires all the financial and technical commitment needed for a traditional on-premises data center. This kind of financial and technical investment also makes private cloud resources and services finite and harder to scale than public clouds.
3. Hybrid cloud. A hybrid cloud architecture establishes a connection between a public and private cloud. When architected properly, a hybrid cloud can blend the scalability and scope of a public cloud with the security and control of a private cloud -- enabling workloads and data to be moved between the two clouds. Hybrid clouds also require all the work and technical savvy needed for a private cloud, as well as the extensive expertise needed to use a public cloud, resulting in a significant effort for the business.
4. Multi-cloud. Clouds are far from standardized or uniform. Each public cloud has certain specialties and types of resources and services that other public clouds might not provide. A multi-cloud architecture enables users to utilize the resources and services of two or more public clouds at the same time. This enables more flexibility, can improve resilience and might reduce the potential for cloud provider lock-in. However, users must have extensive expertise in using all the clouds in the multi-cloud architecture, which demands more knowledge and staff skills than a single public cloud.

Cloud architecture benefits

Cloud architecture is all about defining and planning -- knowing what is needed and understanding how to connect, configure and operate those elements optimally. As with any strategic planning, the business can reap significant benefits, including the following:

• Deployment. Establishing a formal cloud architecture enables new deployments to be implemented much faster and with greater confidence. Users need not struggle with experimentation and optimization to find the right elements and configurations -- that work is already done.
• Performance. A well-planned cloud architecture can deliver the performance and resilience needed to operate a workload for the business. Elements, such as VM types and storage components, are already selected in the architecture, along with additional elements, such as monitoring components (instrumentation), needed to ensure proper ongoing performance.
• Security. Many security flaws are caused by a lack of planning, as users struggle to implement an ad hoc architecture and deployment. A formalized cloud architecture enables architects to plan security and access control measures, such as IAM, that will strengthen security for the workload and its data.
• Cost. An established cloud architecture can provide the business with a known or predictable cost for the deployment because requisite resources, services and applications are already understood. This also positions the business to implement optimizations and take advantage of cost-saving measures, such as volume and committed use discounts.
• Management. Building a well-considered cloud architecture plan is a perfect opportunity to include monitoring and management tools that let the business oversee the performance and availability of each workload and watch utilization to drive scale and prevent cloud sprawl.
• Uniformity. Creating a baseline cloud architecture brings uniformity. Each deployment provides known capabilities -- the business knows what it's getting and how it works. This is better for business governance, regulatory compliance and faster workload troubleshooting.

Cloud architecture best practices

There is no single best cloud architecture or design approach, but the benefits of a well-designed baseline architecture can bring important benefits to the business. Regardless of the architectural plan or the methodology used to achieve it, several best practices can help to drive the effort, including the following:

• Plan. An architecture plan is rarely finalized on paper -- it's often the result of detailed testing and experimentation in the cloud. An architecture should take full capacity and performance needs into account, providing enough resources and services to accommodate the workload's maximum demands or handling appropriate scaling to meet increased demands. This avoids bottlenecks and performance impairments in production.
• Consider continuance. A cloud architecture plan should make provisions for common protections, such as data backups and restoration, VM workload migrations, scalability, DR and resilience. Adding appropriate monitoring and management components is a vital part of this effort.
• Emphasize security. Design the cloud architecture with careful attention to workload and data security at various levels, including data encryption, zero-trust access, extensive patch or update testing, strong access control and well-developed policies. Security should also include response, reporting and remediation policies -- what to do if a breach occurs.
• Enhance performance. Cloud architecture should include all the instrumentation needed to monitor and report on performance. This enables rapid remediation when performance falters and provides a basis for making architectural improvements over time.
• Design for value. It's easy to fret over cloud costs, but the emphasis should be on value rather than bottom-line cloud costs. Control costs through automation, committed use and other tactics, but focus on value rather than cost.
• Revisit the plan. Cloud architecture is not a one-time effort. The architectural design should be revisited regularly and reevaluated against evolving business needs and new cloud technologies or services.

Finding examples of cloud architecture

There are countless examples of cloud architecture, and many businesses can struggle with the nuances of cloud architecture design -- especially when experienced cloud architects are not available. One resource that can help ease the challenges of cloud architectural design is the use of reference architectures.

Cloud service providers, such as AWS, Microsoft and Google, are ready sources of well-validated reference architectures and best implementations that can cover a wide range of workload types and technologies, such as the internet of things, serverless computing and containers. Useful reference libraries include the following:

• AWS Architecture Center.
• Google Cloud Architecture Center.
• Azure Architecture Center.

Users can browse through hundreds of reference architectures that address popular use cases and workload types across various industries and technology areas. Once suitable reference architectures are identified, users can modify and optimize those references to produce an architecture for their industry and workload type -- saving countless hours of experimentation and trial and error.