A simple three-tier architecture consists of a web tier, an application or business tier, and the data tier. These tiers are ordinarily implemented using web servers, application servers, and databases, respectively.

The following figure illustrates tiered architecture on the cloud. This architecture supports auto scaling and load balancing of web servers and application servers. Further, it also implements a master-slave database model across two different zones or data centers (connected with high speed links). The master database is synchronously replicated to the slave. Overall, the architecture represents a simple way to achieve a highly scalable and highly available application in a cloud environment.

Cloud applications can be deployed at multiple locations. Typically, using AWS terminology, these locations are regions (that...

The major benefit of multi-tenancy is cost savings due to shared infrastructure and operational efficiency of managing a single instance of the application across multiple customers or tenants. However, multi-tenancy introduces complexity, and issues can arise when a tenant's action or usage can affect the performance and availability of the application for other tenants on the shared infrastructure. In addition, security, customization, upgrades, recovery, and so on, requirements of one tenant can create issues for other tenants and/or introduce further complexity.

Additionally, customers are concerned about their business-critical data residing on public cloud infrastructure (in the hands of a third-party SaaS application provider). It is of vital importance to ensure that the data architecture is robust and secure to satisfy the security standards...

In this section, we will cover key guiding principles that are useful while designing cloud-based applications. More specifically, we will introduce designing for scale, automated infrastructure, failures, parallel processing, performance, and eventual consistency.

Traditionally, designing for scale meant carefully sizing your infrastructure for peak usage and then adding a factor to handle variability in load. At some point, when you reached a certain threshold on CPU, memory, disk (capacity and throughput) or network bandwidth, you would repeat the exercise for handling increased loads and initiate a lengthy procurement and provisioning process. Depending...

In this section, we will describe common architecture patterns and deployment of some of the main processing models being used for batch processing, streaming applications, and machine learning pipelines. The underlying architecture for these processing models are required to support ingesting very large volumes of various types of data arriving at high velocities at one end, while making the output data available for use by analytical tools, reporting and modeling software, at the other.

The software platforms supporting such applications have the necessary features and support the key mechanisms required to access data across a diverse set of data sources and formats, and prepare it for downstream applications, either as low-latency streaming data or high-throughput historical data stores. For example, Apache Spark...

Costs are central to designing for the cloud. Selecting the most appropriate options from a wide variety of tunable parameters available for each of the services can make this a challenging task. Typically, if you understand the costing for your compute nodes and database services well, then you would have largely accounted for a big chunk of your expected bill. Using an 80:20 principle can help you get to ballpark cost estimates, quickly. Typically, if you understand the costing for your compute nodes and database services well, then you would have largely accounted for a big chunk of your expected bill.

Most cloud service providers make online calculators available to arrive at the ballpark figures for your infrastructure. The following is a sample screenshot for provisioning AWS EC2 instances (compute nodes) in a calculator provided by...

In this section, we go through the specifications of a typical e-commerce website which we will develop and deploy on AWS infrastructure. We will leverage the AWS infrastructure to reduce project timeline and also show you the specific AWS code needed to support your non-functional requirements. However, this application is meant for illustrative purposes and is not a production grade application.

The codebase for this application will be in Java and the framework used will be Spring 4.x along with MySQL as the database. We will not delve into the detailed design or the specifications as it is not in the scope of the book, nor shall we develop all the functional use cases defined in the specifications. We will, however, dive deep into the non-functional specifications as they tend to leverage the cloud services more.

Suppose electronics retailer...

In this chapter, we explained the differences in design and implementation of cloud-based applications. We reviewed some of the architectural best practices in the cloud context. More specifically, we described multitiered, loosely coupled, and service oriented scalable designs and their realizations on the cloud platform. We also went through the design consideration and implementation approaches to multi-tenancy, and explored some of the architectural patterns being used for streaming and machine learning applications. Finally, we created a simple application that we intend to expand and elaborate in the coming chapters to illustrate AWS concepts in detail.

After covering the cloud architectural principles in this chapter, we will get a lot more specific in our coverage of cloud computing in the next chapter. We will cover AWS specific cloud services, the AWS costing...