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Cloud Computing Technology Trends 2021

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As technology evolves rapidly, businesses escalate and new practices are born. Over the past year, there have been a number of new trends appearing.

In this blog, we will highlight some of the key developments in the world of cloud computing – some of which your startup may already be using; others which may be new discoveries you incorporate in the future.

Hybrid Cloud & Multicloud

“IT environments are becoming fundamentally hybrid and multicloud in nature,” says Willie Tejada, IBM Chief Developer Advocate. He continues: “As a developer, you’re being asked to connect and coordinate business processes that run in different parts of the environment. You’re also responsible for building new services and modernizing existing applications to take advantage of cloud-native technologies like containers and Kubernetes.”

The adoption of Multicloud has become increasingly popular over the years due it its key benefits of avoiding vendor lock-in and its ability to reduce costs. Developing an application that works across cloud providers requires a platform that abstracts cloud functionality in portable containers such as Kubernetes or Red Hat OpenShift on IBM Cloud for a secured environment.

IBM’s focus on the Hybrid Cloud is about connecting the public cloud with the private cloud – and bringing together benefits around control, security, cost and speed.

As to whether you can combine Hybrid Cloud and Multicloud – there are different approaches to achieve this, including using public cloud from one cloud provider and private cloud from another one. In this way, your Hybrid Cloud becomes Multicloud.

Read: For your journey to Hybrid Cloud, finding the right hybrid integration platform is critical

You can learn more about Multicloud in this free course on


Serverless has become a trending topic in the world of cloud computing for its simplicity and many advantages including the pay-as-you-go model, automatic scaling, easy integration with other services and REST APIs.

Serverless computing can break down your application into functions where each function focuses on performing specific tasks such as reading from or writing to databases and making API calls. One of the main benefits of serverless computing is that you can focus solely on your code, rather than managing underlying infrastructure, which is a plus for any developer.

Of course there are countless serverless use-cases, and only a couple have been mentioned here, but it’s important to keep in mind that they are not ideal for every scenario.

Want to explore different use-cases with Serverless? Check out Get started with Serverless for a free hands-on tutorial.


DevOps has been on the rise since 2017. It generated $2.9 billion in 2017 and this has been projected to reach $6.6 billion by 2022. This huge increase is due to high demand for automation as it so effectively brings together development and operations. It is also due to the integration of AI & ML in DevOps.

Increasingly, organizations are trying to adopt the agile methodology which DevOps provides, also adding other approaches such as ArchOps, Test Ops, DataOps, WinOps, DevSecOps, and so on.

Explore DevOps pipelines for your workload here.


Data is said to be the oil of the 21st century. But much like oil, when data is unrefined it does not provide much value. Once refined, however, data can provide valuable insights which can play a significant role across many industries.

For example, in the retail industry consolidating large volumes of data such as product benchmarks, customer feedback and product fulfillment can create valuable insights. The data itself might be collected from a number of sources such as call centers, social media, and so on.

The need to collect and convert data into actionable insights has never been more pressing.

Uncover insights with data collection, organization, and analysis.


Due to the pandemic, many organizations increased their adoption of technology. Chatbots were one such area, reducing the load on call centers and helplines while saving time for customers. Chatbots, however, cannot exist without NLP.

Last year alone, there were a number of breakthroughs in NLP. OpenAI released its largest NLP model –

GPT-3 which used deep learning to recreate content. Facebook AI launched open source chatbot BlenderBot which was able to demonstrate both personality and empathy.

Discover NLP and Build apps that can interpret unstructured data and analyze insights.

Build voice and text chatbots that can understand what users are asking.


Increasingly, we will see rapid adoption of cloud technologies by organizations. Some key areas that are expected to see the most growth in cloud computing include pair programming, code reviews, and open source projects.

If you would like to know more about how to use these technologies in your applications, please reach out through the Dtec Mentoring sessions with IBM or contact us directly at,

Follow us on Meetup ( to join upcoming workshops and webinars on the topics discussed in this article.

Written by:

Mridul Bhandari, Developer Advocate, IBM

Masa Abushamleh, Developer Advocate, IBM