PaaS use cases

PaaS can be beneficial, and one could argue critical, to the success of today’s enterprises. Take a company such as Lyft taxi service (an AWS customer). It is not uncommon for traffic to their app to go up by 50% to 100% during certain holidays. Accordingly, Lyft needs more servers during the holidays than on other days. If Lyft had an on-premises environment, they would have no choice but to bite the bullet and buy servers for the worst-case scenario when they have the highest traffic. But because they operate in a cloud environment, resources can spin up more when they have usage spikes, and it can bring those instances down when site traffic goes down. They don’t need as many compute’ resources.Here are some examples of PaaS use cases:

• Business Process Management (BPM): Many enterprises use PaaS to enable BPM platforms with other cloud services. BPM software can interoperate with other IT services. These combinations of services enable process management, implementation of business rules, and high-level business functionality.
• Business Analytics/Intelligence (BI): BI tools delivered via PaaS enable enterprises to visualize and analyze their data, allowing them to find customer patterns and business insights. This enables them to make better business decisions and more accurately predict customer demand, optimize pricing, and determine which products are their best sellers.
• Internet of Things (IoT): IoT is a key driver for PaaS solution adoption and will likely be even more important in the coming years. You have probably only scratched the surface for IoT applications enabled by a PaaS layer.
• Databases: A PaaS layer can deliver persistence services. A PaaS database layer can reduce the need for system administrators by providing a fully managed, scalable, and secure environment. You will visit the topic more deeply in a later chapter, but AWS offers a variety of traditional and NoSQL database offerings.
• API management and development: A common use case for PaaS is to develop, test, manage, and secure APIs and microservices.
• Master Data Management (MDM): MDM came about from the need of businesses to improve the quality, homogeneity, and consistency of their critical data assets. These critical data are customer, product, asset, and vendor data. MDM is used to define and manage these critical data. Additionally, it provides a single point of reference or a single source of truth for this data. MDM enables methods for ingesting, consolidating, comparing, aggregating, verifying, storing, and routing essential data across the enterprise while ensuring a common understanding, consistency, accuracy, and quality control. PaaS platforms have proven to be a boon for developing MDM applications, enabling them to process data quickly and efficiently.

Using PaaS is beneficial, sometimes even critical, in many applications. PaaS can streamline a workflow when several parties simultaneously work on the same task. PaaS is functional when customized applications need to be created. PaaS can reduce development and administration costs. Let’s look at some examples of AWS PaaS services.