Top AWS Trends to Watch For

AWS, cloud computing, and remote servers are just some of the buzzwords of the present era. This blog introduces you to the terms cloud computing, AWS, and the latest AWS trends to watch out for this year. Read on.

Cloud computing can be defined as delivering online services (such as servers, databases, and software) to users. With cloud computing, one need not store data on a local machine. Data is stored on a remote server from where users can access it. Now, let us understand the term AWS. AWS stands for Amazon Web Service, an online platform that offers cost-effective and scalable cloud computing solutions. Post its launch in 2006, AWS has continued to dominate the cloud sector. Organizations are adopting cloud services aggressively and the demand for migration to AWS is only increasing. This is due to the excellent benefits that AWS offers, such as security, cost, scalability, time to market, and accelerated innovation.

Requirement For AWS Cloud Computing

At present, cloud computing is as essential to the world of IT as it is to the lifestyle of people. It has proved its mettle in various fields, such as internet banking and e-commerce. It was cloud computing that supported world commerce, globalization, and employees when the pandemic struck. Cloud computing will be a core priority for organizations pursuing an efficient plan, market stability, and cost savings in the coming years.

A recent survey states that the global cloud services industry will be close to $623 billion by 2023, with an increasing Compound Annual Growth Rate (CAGR) of 18%. Following are the trends that one should expect in the coming years with respect to the AWS cloud.

Joint-vendor cloud and multi-cloud collaborations will increase as vendors understand that they can work together to accelerate business releases and benefit from shared assets. The Microsoft-Oracle Interconnect partnership in June 2019 is an excellent example of a partnership that was an amalgamation of Oracle’s software development and Microsoft’s ML capabilities. A multi-cloud approach allows organizations to use various cloud systems from different vendors.

We will witness customers adopting a low-code approach for creating customer-facing data collection apps, web apps, automation use cases, and business workflow processes to fast-track digital transformation initiatives. This low-code platform allows IT professionals to focus on vital business and complex use cases instead of wasting time on trivial use cases. The AWS Amplify Studio enables acceleration of cloud-native application development with negligible or low code changes. Enterprises should compare such low code platforms against their business functionality for specific use cases, vendor lock-ins, and application maintenance costs.

As organizations migrate to the cloud, traditionally, the following two options were available:

1. Use easily accessible, pay-as-you-go public cloud solutions

2. Use customizable and flexible private cloud solutions.

A private cloud (where an organization has its own cloud) is required for security and regulatory reasons. Today, organizations such as Amazon, Microsoft, and IBM are increasing their production of “hybrid” models that assume the best-of-both-worlds approach. Data that needs to be frequently and quickly accessed is available on public AWS servers. Sensitive data can be stored on private servers where access is monitored. Another reason for the popularity of hybrid cloud is that most organizations have understood the benefits of cloud computing and are in search of additional use cases.

Cloud computing plays a crucial role in Artificial Intelligence (AI). Machine learning (ML) platforms need a huge data bandwidth and processing power for processing and training data. Most of the ‘everyday’ AI available to us, from Instagram filters to Google Search is present in the cloud. Technology that directs traffic from data centers to our devices and handles storage infrastructure is built on Machine Learning (ML). The evolution and development of both AI and the cloud are deeply interwoven. This facet will become more prominent from 2022 onwards. The leading trends in AI will be “creative” algorithms. Generative ML can create anything from art to synthetic data to train more AIs and language modeling. This will help increase machines’ accuracy to understand and mimic human languages. AWS will definitely play a crucial role to offer these services to users and building the infrastructure to deliver them.

Serverless cloud is quite a new concept that is gaining prominence in the market from providers including Microsoft (Azure Functions), Amazon (AWS Lambda), and IBM Cloud Functions. Also, known as “functions-as-a-service,” it means organizations are not tied to leasing servers or paying for specified amounts of bandwidth or storage. It offers a pay-as-you-go service where the infrastructure is available based on an application’s requirement. Of course, it is not really serverless as the servers are present. However, it adds another layer of abstraction between the user and the platform, meaning that the user does not have to worry about the technicalities and configurations. Serverless within cloud computing has an essential role to play in the broader trend across the cloud and the entire technical landscape of designing new user experiences that enable innovation.

Every enterprise has its unique regulatory, legacy technology, and governance challenges with respect to migrating workloads to the public cloud. Enterprises in the healthcare industries and financial services have strict regulation and privacy mandates; whereas enterprises in the energy sector focus more on distributed integration needs. AWS has exclusive value propositions to customize services to address specific needs of high-valued financial services, energy, and healthcare organizations to hasten cloud enablement. As each customer portfolio is unique, enterprises will begin to consider a hybrid approach as a traditional cloud migration strategy may not work.

Enterprises are moving to purposeful cloud databases that are built on open-source platforms. These databases are as good as commercial databases in terms of performances, tools, features, performances, and scale at lower Total Cost of Ownership (TCO). A public cloud provider such as AWS provides tools such as DMS and SCT to accelerate database migration of cloud-native databases. These cloud-native databases offer further cost savings by giving serverless options that decrease the infrastructure cost of sustaining databases on the cloud.

Innovation is key for accelerating business transformation and avoiding future disruptions. Enterprises are using a mix of Edge Computing, IoT, and Blockchain technologies for reinvention in the cloud. Various industry-specific use cases utilize IoT devices to send huge amounts of data to edge locations for analytics purposes close to the devices or users. These use cases mandate a blockchain consensus algorithm to offer the security to resolve the privacy and security issues linked to edge computing and to ensure that data is accessible from verified IoT devices. IoT, Edge Computing, and Blockchain capabilities offered by public cloud providers help enterprises capitalize on opportunities for growth and reinvention.

To continue to remain competitive and make the most of the available advantages, organizations need to make strategic decisions about cloud architecture, cloud computing, usage of public clouds, cloud migration, effective tooling, and cost management. As AWS continues to dominate the market, we need to be aware of what is in store for us.