Cloud Computing – SaaS vs. PaaS vs. IaaS

In simple terms, Cloud computing is the delivery of different services through the Internet, including data storage, servers, databases, networking, and software.

Edge computing devices are designed to gather and process data on-site quickly and analyze data in real-time. It doesn’t focus on storing data. 

Cloud computing: On the other hand, is based on an infrastructure and can be easily scaled according to needs. It’s all about carrying out data collection, processing, and storage close to where that data is generated and, generally, close to where it can be usefully consumed as well.

Quantum Computing: Next remarkable technology trend is quantum computing, which is a form of computing that takes advantage of quantum phenomena like superposition and quantum entanglement.

3 main types of cloud computing available today

IaaS, PaaS and SaaS are the three (3) main types of cloud computing available today

IaaS (Infrastructure as a Service).

IaaS, also known as cloud infrastructure services, provides end users with cloud-based alternatives to on-premise, physical infrastructure, allowing businesses to purchase resources on-demand instead of the more costly venture of having to buy and manage hardware.

IaaS works primarily with cloud-based and pay-as-you-go services such as storage, networking and virtualization.

Examples of popular IaaS providers include: 

  • AWS EC2.
  • Rackspace.
  • Google Compute Engine (GCE).
  • Digital Ocean.
  • Microsoft Azure.
  • Magento 1 Enterprise Edition

PaaS (Platform as a Service).

PaaS, also known as cloud platform services, provides developers with a framework, software and tools needed to build apps and software — all accessible through the internet. 

Often seen as a scaled-down version of IaaS, PaaS gives its customers broader access to servers, storage and networking, all managed by a third-party provider.

PaaS focuses primarily on hardware and software tools available over the internet. 

Examples of popular PaaS providers include: 

  • AWS Elastic Beanstalk.
  • Heroku.
  • Windows Azure (mainly used as PaaS).
  • Google App Engine.
  • OpenShift.
  • Apache Stratos.
  • Adobe Magento Commerce Cloud

SaaS (Software as a Service).

SaaS, also known as cloud application services, is the most commonly used service within the cloud market. SaaS platforms make software available to users over the internet, usually for a monthly subscription fee.

They are typically ready-to-use and run from a users’ web browser, which allows businesses to skip any additional downloads or application installations. 

SaaS platforms involve software that is available via third-party over the Internet. 

Examples of popular SaaS providers include: 

  • BigCommerce.
  • Google Workspace, Salesforce.
  • Dropbox.
  • MailChimp.
  • ZenDesk.
  • DocuSign.
  • Slack.
  • Hubspot

Fundamental Cloud Computing Skills

These 15 cloud computing skills are an important part of the day-to-day work of a cloud engineer or cloud architect. Honing these skills will help you contribute to a team that’s designing, developing, securing, and maintaining cloud services within an organization.

1. Programming 

This is a critical skill for any software developer, but cloud architects and administrators will also have to write code from time to time. Certain popular programming languages are better suited for cloud-based software. These include Java, JavaScript, and Python, as well as emerging languages such as Go and Scala. For database programming, you’ll need to be familiar with SQL, NoSQL, and Linux.

2. Platform Expertise

Amazon, Microsoft, and Google lead the cloud services market. Knowing how each of these three platforms works is a necessary skill for cloud computing professionals. Other companies with cloud platforms include IBM, Dell, Oracle, and Alibaba, which has a large presence in China. While each of the major vendors offers a certification program, a Graduate Certificate in Cloud Software Development will provide a well-rounded look at the cloud platforms as a whole. 

3. Selecting the Right Services

Each cloud platform has specific strengths. Amazon is a leader in infrastructure; Microsoft is known for software; Google integrates with other vendor’s products; IBM focuses on artificial intelligence; Cisco Systems is a leader in networks, and so on. To work with cloud services, you need to be able to evaluate each platform and select the best option for a particular need.

4. Managing an Integrated Environment 

Because platforms have different strengths, organizations are unlikely to use a single cloud platform. Data integration across different platforms is a highly sought skill among cloud computing professionals. This is especially true for organizations that use cloud services alongside legacy onsite client-server applications. Additionally, a multi-cloud strategy is beneficial for the sake of redundancy, as it gives an organization a fallback option if one cloud service is down. 

5. Maintaining Databases

Storing data on the cloud isn’t the same as using an onsite data center. Challenges include storage limitations, security, and database performance. What’s more, vendors typically offer a variety of databases, with some better suited for analyzing large data files and others optimized for processing transactions, Gorton says. Cloud computing professionals need to understand which databases and services best suit a particular business need. 

6. Managing a Network

With multiple cloud services interacting with one another, network management is a critical skill for cloud engineers. As with databases, different networks are suitable for different cloud services. For example, organizations often require employees to log into a virtual private network to access applications with access to sensitive information such as financial reports or personnel files; meanwhile, services such as videoconferencing may be routed on a different network because of performance requirements. As more employees continue to work remotely in the wake of COVID-19, effective network management will be an increasingly important cloud computing skill. 

7. Securing the Cloud Environment

Ensuring that an organization’s cloud services are secure requires particular attention to detail. It’s not enough to secure the data itself; organizations need to protect the applications that use the data as well as the servers on which the applications run. Devices that transmit data to the cloud must be secured as well, whether they’re the smartphones in employees’ hands or the sensors transmitting data from the hospital room. Staying on top of emerging trends in cybersecurity will help you keep your organization a step ahead of major threats.  

8. Adapting to New Roles and Technologies

The rise of cloud computing has led to a shift away from the traditional specialization of IT roles. While an onsite data center may have a system administrator, network engineer, security analyst, and storage engineer, today’s IT professionals need to be comfortable wearing each of those four hats—and taking on additional responsibilities or learning new technologies as necessary. 

Advanced Cloud Computing Skills

These seven skills apply to long-term cloud computing projects that an organization is likely to undertake as its use of cloud services matures. Developing these skills will further demonstrate your cloud expertise and enable you to take on additional responsibilities, which will help you build your resumé and advance your cloud computing career.

9. Migrating Data

There are two major types of data migration to the cloud: Moving an old (or legacy) application from an onsite server to the cloud and moving from one cloud platform to another. To successfully migrate data, cloud professionals must be able to assess and map out their infrastructure, understand each cloud platform’s process for data migration, and indicate where data has been moved to—all while ensuring that nothing is lost during the process.

10. Automating Key Tasks

Automation is a major benefit of cloud services. When a piece of software can input information and decide the next action in response, an end-user doesn’t have to make that decision, which further improves efficiency. Programming this automation requires knowledge of artificial intelligence and machine learning, as they enable the creation of complex algorithms that help computers make decisions. The ability to automate multiple tasks also requires knowledge of the organization’s cloud architecture, namely which individual systems interact with or depend upon each other.  

11. Designing Distributed Systems 

Cloud computing is less about building new systems from scratch and more about putting systems together based on existing services, Gorton says. Assembling these distributed systems—so named because resources are located in different places—requires several skills, Gorton adds. These include predicting and monitoring system performance and comparing attributes of different services and data models. 

12. Managing Change

It’s important to be able to draft plans for migrating data, bringing a new database online, creating a new network connection, or introducing another change to an organization’s cloud environment. These plans should include a written step-by-step procedure and a fallback option, which returns the project to its original state if a problem arises. The plans that organizations use for onsite changes such as server migrations or network upgrades can be applied here, though updates will be necessary to accommodate for the cloud.    

13. Estimating Cost and Workload

Cost and workload estimation are critical skills due to how cloud service providers write their contracts, Gorton says. For example, if a data limit is exceeded, or an application requires more computing power to complete data analysis, organizations can expect to be hit with an overage. Another essential but often-overlooked consideration is what Gorton calls “orphaned resources,” or features that are created, misplaced, and created again, at a cost to an organization. Keeping a watchful eye on whether features are no longer being used can help keep costs down.

14. Measuring and Analyzing

Employers value job candidates with expertise in metrics and analytics. For example, it’s important for organizations using third-party cloud services to monitor application performance, as this ensures that they are getting their money’s worth from a service provider’s contract. Or, a network engineer may be tasked with evaluating and comparing cloud-based communication services as a way to replace landline telephones. Understanding which metrics set apart a certain service, or which features will cost the most money in the long run, is an important cloud computing skill. 

15. Communicating 

Beyond your range of technical skills, soft skills such as communication and decision-making are valuable for a career in cloud computing. Internal stakeholders will turn to you for advice as they evaluate cloud platforms for their departments (or the entire company), so it’s important that you can clearly explain the benefits and drawbacks of each option. Cloud engineers working in customer-driven industries such as retail or travel should also be comfortable communicating directly with a company’s vendor—especially when experiencing problems or negotiating a new service contract.

Some Cloud Management & monitoring tools include

  • Amazon Cloudwatch. Amazon Web Services offers to monitor for cloudresources and applications running on Amazon AWS.
  • Microsoft Cloud Monitoring.
  • AppDynamics.
  • BMC TrueSight Pulse.
  • CA Unified Infrastructure Management (CA Technologies)
  • New Relic
  • Hyperic
  • Splunk (Mainly Data Management & visualization)

Below are a few combinations of skills required for a Cloud expert:

Cloud Security – Cyber security professionals know and understand common risks, vulnerabilities, cloud architecture security, cloud application security and so much more. This is one of the major cloud computing skills in demand.

Machine Learning and AI

Cloud migration and deployment – Organisations may need to migrate from native IT setups to cloud platforms.

Database skills – Also needed are skills to store, manage, and access data. For this, knowledge of database query languages is essential. While SQL is popular, some of the other important ones include Hadoop and MongoDB. 

DevOps – will cover in detail later

Serverless architecture

Programming languages – As opposed to generic languages like C, C++, Java, cloud developer skills include knowledgeof data-oriented ones like Ruby, Python and Perl. Some most Popular Cloud Computing Languages

Java – is one of the most popular programming languages.









Linux – Cloud engineers need the mastery of Linux environments

Kubernetes (Containerization tools)


Top 10 Most Popular Programming Languages

1. Python

Benefits: Python is widely regarded as a programming language that’s easy to learn, due to its simple syntax, a large library of standards and toolkits, and integration with other popular programming languages such as C and C++. In fact, it’s the first language that students learn in the Align program, Gorton says. “You can cover a lot of computer science concepts quickly, and it’s relatively easy to build on.” It is a popular programming language, especially among startups, and therefore Python skills are in high demand.

Drawbacks: Python is not suitable for mobile application development.

Common uses: Python is used in a wide variety of applications, including artificial intelligence, financial services, and data science. Social media sites such as Instagram and Pinterest are also built on Python.

2. JavaScript

Benefits: JavaScript is the most popular programming language for building interactive websites; “virtually everyone is using it,” Gorton says. When combined with Node.js, programmers can use JavaScript to produce web content on the server before a page is sent to the browser, which can be used to build games and communication applications that run directly in the browser. A wide variety of add-ons extend the functionality of JavaScript as well. 

Drawbacks: Internet browsers can disable JavaScript code from running, as JavaScript is used to code pop-up ads that in some cases can contain malicious content. 

Common uses: JavaScript is used extensively in website and mobile application development. Node.js allows for the development of browser-based applications, which do not require users to download an application.

3. Java

Benefits: Java is the programming language most commonly associated with the development of client-server applications, which are used by large businesses around the world. Java is designed to be a loosely coupled programming language, meaning that an application written in Java can run on any platform that supports Java. As a result, Java is described as the “write once, run anywhere” programming language.

Drawbacks: Java is not ideal for applications that run on the cloud, as opposed to the server (which is common for business applications). In addition, the software company Oracle, which owns Java, charges a licensing fee to use the Java Development Kit.

Common uses: Along with business applications, Java is used extensively in the Android mobile operating system.

4. C#

Benefits: Microsoft developed C# as a faster and more secure variant of C. It is fully integrated with Microsoft’s .NET software framework, which supports the development of applications for Windows, browser plug-ins, and mobile devices. C# offers shared codebases, a large code library, and a variety of data types.

Drawbacks: C# can have a steep learning curve, especially for resolving errors. It is less flexible than languages such as C++. 

Common uses: C# is the go-to language for Microsoft ad Windows application development. It can also be used for mobile devices and video game consoles using an extension of the .NET Framework called Mono.

5. C

Benefits: Along with Python and Java, C forms a “good foundation” for learning how to program, Gorton says. As one of the first programming languages ever developed, C has served as the foundation for writing more modern languages such as Python, Ruby, and PHP. It is also an easy language to debug, test, and maintain.

Drawbacks: Since it’s an older programming language, C is not suitable for more modern use cases such as websites or mobile applications. C also has a complex syntax as compared to more modern languages.

Common uses: Because it can run on any type of device, C is often used to program hardware, such as embedded devices in automobiles and medical devices used in healthcare. 

6. C++

Benefits: C++ is an extension of C that works well for programming the systems that run applications, as opposed to the applications themselves. C++ also works well for multi-device and multi-platform systems. Over time, programmers have written a large set of libraries and compilers for C++. Being able to use these utilities effectively is just as important to understanding a programming language as writing code, Gorton says.

Drawbacks: Like C, C++ has complex syntax and an abundance of features that can make it complicated for new programmers. C++ also does not support run-time checking, which is a method of detecting errors or defects while software is running. 

Common uses: C++ has many uses and is the language behind everything from computer games to mathematical simulations.

7. Go

Benefits: Also referred to as Golang, Go was developed by Google to be an efficient, readable, and secure language for system-level programming. It works well for distributed systems, in which systems are located on different networks and need to communicate by sending messages to each other. While it is a relatively new language, Go has a large standards library and extensive documentation.

Drawbacks: Go has not gained widespread use outside of Silicon Valley. Go does not include a library for graphical user interfaces, which are the most common ways that end-users interact with any device that has a screen.

Common uses: Go is used primarily for applications that need to process a lot of data. In addition to Google, companies using Go for certain applications include Netflix, Twitch, and Uber.

8. R

Benefits: R is heavily used in statistical analytics and machine learning applications. The language is extensible and runs on many operating systems. Many large companies have adopted R in order to analyze their massive data sets, so programmers who know R are in great demand. 

Drawbacks: R does not have the strict programming guidelines of older and more established languages. 

Common uses: R is primarily used in statistical software products. 

9. Swift

Benefits: Swift is Apple’s language for developing applications for Mac computers and Apple’s mobile devices, including the iPhone, iPad, and Apple Watch. Like many modern programming languages, Swift has a highly readable syntax, runs code quickly, and can be used for both client-side and server-side development. 

Drawbacks: Swift can only be used on newer versions of iOS 7 and will not work with older applications. As a newer programming language, the code can be unstable at times, and there are fewer third-party resources available to programmers.

Common uses: Swift is used for iOS and macOS applications. 

10. PHP

Benefits: PHP is widely used for server-side web development, when a website frequently requests information from a server. As an older language, PHP benefits from a large ecosystem of users who have produced frameworks, libraries, and automation tools to make the programming language easier to use. PHP code is also easy to debug.

Drawbacks: As Python and JavaScript have gained popularity, PHP’s popularity has dropped. PHP is also known for its security vulnerabilities. According to Indeed, most PHP programmers take short-term roles that last less than one year.

Common uses: PHP is the code running content-oriented websites such as Facebook, WordPress, and Wikipedia. 

7 Other Programming Languages to Consider

The following programming languages aren’t quite as popular as the 10 listed above, but they are also worth considering if you’re looking to expand your programming options.

  • Dart is optimal for programming applications that need to run on multiple platforms, such as Windows and iOS. 
  • Kotlin is used to develop applications for the Android OS. 
  • MATLAB is a proprietary language developed by MathWorks and used for scientific research and numerical computing. 
  • Perl got its start for programming text, which makes it easy to learn and popular for developing a proof of concept. 
  • Ruby is losing traction as compared to other languages, but the Ruby on Rails framework was influential to other, later Web application frameworks for Python, PHP, and JavaScript.
  • Rust emphasizes high performance and security and is useful for applications where many things are happening concurrently.
  • Scala, named as a play on scalable language, is compatible with Java and is useful for cloud-based applications.