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Top 5 Cloud Terms Every Learner Should Know

PLUS: Google Upgrades Its AI-Powered Research Tool

In Today’s Cloudbites:

✍🏻 Top 5 Cloud Terms Every Learner Should Know

📚 Part 2: Exploring More Cloud Terms

☁️ Online Cloud Events to Look Forward to

🤫 PLUS: Google Upgrades Its AI-Powered Research Tool

Read time: 6 minutes

Hi friends, welcome back to Cloudbites

Today, I’ll be talking about the most frequently-used Cloud terms that you should know. I’ll also share some opportunities to help you develop your Cloud skills, as well as Google’s upgraded research tool: NotebookLM.


✍🏻 Top 5 Cloud Terms Explained

As a Cloud learner, having a clear understanding of cloud computing terms is essential to further your study and communicate with your peers.

To strengthen your knowledge, here are the top 5 Cloud terms and what they mean:

#1 Cloud Computing

It is essentially the delivery of computing services—including servers, storage, databases, networking, software, etc.

Instead of owning their own physical computing infrastructure or data centers, companies can rent storaging, applications, and many more from a Cloud service provider. 

I like to think that it's like renting a movie instead of buying it—it's cheaper and more flexible.

#2 SaaS vs. PaaS vs. IaaS

There are 3 main types of Cloud services: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).

Each of them has their own functions and control levels.

SaaS is where software applications are hosted by a third-party provider and made available to users online.

Users can access these applications via a web browser without having to install on their devices, such as Google Workspace and Microsoft Office 365.

Although SaaS users have the least control in terms of the back-end process, they gain benefit from the user-friendly interface.

On the other hand, PaaS has a platform for developing, deploying, and managing applications in the Cloud.

Examples include Google App Engine and Microsoft Azure App Service.

Last but not least, IaaS provides fundamental computing resources like virtual machines, storage, and networking.

With IaaS, users have more control over their back-end infrastructure as they manage operating systems, middleware, and applications.

Examples of IaaS are AWS and Microsoft Azure.

#2 Serverless

Serverless is a way of building and running apps without managing servers.

Because in a serverless architecture, the Cloud provider automatically provides, scales, and manages the infrastructure required to run the code.

With serverless, developers can focus solely on writing code without worrying about server management or scaling issues. 

#3 Virtualization

Virtualization is about creating a virtual version of physical resources like servers, storage devices, or operating systems.

It enables efficient resource allocation, allowing multiple virtual instances to run on a single server.

This makes it easier for Cloud providers to meet varying demands (scalability) and adapt to changing workloads (flexibility).

#4 Public vs. Private vs. Hybrid

There are 3 main types of Cloud environments: Public, Private, and Hybrid.

A Public Cloud is where third-party providers offer Cloud resources and applications to the general public.

Users will enjoy the benefits of scalability, rapid deployment, and cost-effectiveness, which makes it an attractive option for small businesses.

In constrast, a Private Cloud is dedicated to one organization, providing similar benefits like Public Cloud but with greater control and customization.

This is it ideal for larger organizations with specific performance needs that cannot be met by Public Cloud services.

Similar to its name, Hybrid Cloud is a combination of Public Cloud services with Private Cloud infrastructure.

This model enables businesses to maintain critical data and on-premises workloads while leveraging the scalability and flexibility of the Public Cloud for other operations.

#5 Cloud Migration

Cloud migration is transferring data, applications, and workloads from physical infrastructure to Cloud-based platforms.

Its purpose is to have better scalability, flexibility, and accessibility while reducing dependency on hardware and infrastructure maintenance.

📚 Part 2: Exploring More Cloud Terms

Here are some more (technical) terms to support your learning:

#1 Cloud Native

Cloud-native is a terms used to refer to applications or services that are specifically designed to work in a Cloud infrastructure.

These applications are built using microservices (small, independent components), containers (i.e. putting the components in virtual boxes), and DevOps practices for efficient development and deployment.

Examples of Cloud-native applications are Netflix, Airbnb, and Spotify.

#2 Containers

Containers are portable, isolated environments (boxes) that package applications and their dependencies.

Additionally, since they’re lightweight, they can run across different computing environments; from one computer to big Cloud servers.

When I first started learning the Cloud, I like to think of containers as moving boxes that makes managing apps easier.

#3 Cloud Security

With the increasing adoption of cloud computing, having strong security measures is essential to protect sensitive information.

Cloud security consists of technologies, policies, and procedures designed to protect Cloud environments, data, and applications.

Security measures in Cloud security include encryption, identity and access management (IAM), network security, and compliance controls to ensure the confidentiality and integrity of Cloud resources.

#4 Microservices

Microservices is an architectural approach to building applications by breaking them into lots of small, independent components.

As each component is responsible for specific business functions, it becomes easier to change and update applications.

#5 Edge Computing

Edge computing enhances the procedure of data processing by bringing computation and data storage closer to the source of data generation, which improves real-time response.

It has a distributed architecture where processing tasks are distributed across multiple edge devices rather than relying on one data center.

This allows for faster processing and reduces the need (as well as time) to send data back and forth over long distances.

☁️ Online Cloud Events to Look Forward to

#1 AWS – Introduction to Generative AI for Decision Makers (June 10)

Learn about the basics of generative AI terminology and the potential benefits and risks of using generative AI. 

Click here to register.

#2 AWS – Cloud Practitioner Essentials (June 12)

An introduction to AWS cloud computing concepts and foundational infrastructure services.

Click here to register.  

#3 AWS – Introduction to Prompt Engineering (June 13)

An introduction to the basics of foundation models, the concepts of prompt engineering, and basic prompt techniques.

Click here to register.


🤫 PLUS: Google Upgrades Its AI-Powered Research Tool

NotebookLM is Google’s AI-powered note-taking, research, and writing assistant. Recently, Google had just announced the tool’s improved ability to assist users in doing research. 

💡Here are some of the upgrades that Google made:

  • Previously, users could only upload Google Docs, PDFs, and text files into NotebookLM to access researching tools like summarizing

  • Now, users can upload web URLs to answer questions about a web page's content

  • NotebookLM also offers citations that reference the sources, as well as generating answers based on images, charts, and diagrams via Google Slides or Google Docs

You can get started now by visiting the NotebookLM website.


Thanks for reading! 😊

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