Can Distributed Computing Take On The Might Of AWS?

Trying to find out if distributed computing can take on the might of AWS computing? 

You’ve come to the right place.

AWS Computing Service: A brief overview

Amazon Web Services (AWS) doesn’t need an introduction, does it? It’s one of the most mature managed cloud services providers, and AWS claims to have over 1 million customers. AWS counts giants like Capital One, GE, etc. among its customers.

It has a presence in all key geographies, and experts have often commended its considerable cloud capabilities. You can read “Top cloud providers 2019: AWS, Microsoft Azure, Google Cloud; IBM makes a hybrid move; Salesforce dominates SaaS” to learn more about the prominence of AWS in the cloud space.

With EC2, Elastic Beanstalk, etc., AWS covers the entire gamut of managed cloud services. AWS also offers relational databases, NoSQL databases, AWS Lambda for Serverless computing, etc., and you can read more about them in “Cloud Products”.

Another advantage of AWS is the comprehensive AWS documentation.

Advantages and disadvantages of AWS

AWS offers many advantages, e.g.:

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• Signing up for AWS is easy, moreover, its management console makes it easy to use even for newbies.
• AWS is a highly reputed provider of managed cloud services, and it offers flexible and easy-to-understand billing options.
• With its global presence and robust infrastructure, AWS ensures high availability of services.
• AWS adds new services frequently, moreover, it focuses on cutting-edge technologies like Artificial Intelligence (AI), Machine Learning (ML), etc.
• Users can get unlimited capacity in most cases, moreover, AWS offers impressive speed and security.

Read more about this in “Advantages of AWS | disadvantages of AWS, Amazon Web Services”.

In addition to the generic disadvantages of cloud computing, AWS has a few drawbacks. These are as follows:

• Amazon EC2 and Amazon VPC consoles impose some limitations on resources.
• AWS imposes some limitations on security features, moreover, its technical support can be a bit expensive at times.

Distributed computing environment vs Cloud computing

Can distributed computing take over AWS? Let’s explore it in the form of a comparative overview of distributed and cloud computing.

The differences between distributed and cloud computing are as follows:

1. Objective:

Distributed computing systems enable resource-sharing in a collaborative manner. This kind of computing strives to offer various kinds of scalability, e.g., size scalability, i.e., supporting a large number of processes and users concurrently.

Consumers of distributed computing systems can also expect administrative scalability, geographical scalability, etc.

On the other hand, the objective of cloud computing is to deliver computing resources in an on-demand environment over the Internet. Cloud computing providers make it transparent that they are offering distinctly different services.

2. Types:

Unlike the public/private/hybrid classification in the case of cloud computing services, the classification of distributed computing stands on its implementation. There are offline distributed systems e.g batch processing systems, soft real-time distributed systems with a generous time window to give results e.g search indexer builders, and hard real-time systems e.g., front-end webservers, credit card transactions, etc.

These systems are also divided on how they work. There are 3 types of distributed systems, namely, “Distributed Information Systems”, “Distributed Pervasive Systems”, and “Distributed Computing Systems”.

The 1^st type of distributed system involves distributing information across servers using communication protocols like “Remote Procedure Calls” (RPC). The 2^nd type is made up of embedded devices like sensors, wireless cameras, etc., and they could be unstable.

In the case of the 3^rd one, connected computers communicate with each other using messaging protocols. Read more about this in “What is the difference between cloud computing and distributed computing?”.

3. Characteristics

A distributed computing system distributes tasks to different computers while giving the impression of one system to a user. This is entirely different from cloud computing, which provides access to a variety of shared computing resources to users, and users can configure these resources.

Challenges with Distributed Computing

Why do software engineers find distributed computing hard as compared to an AWS cloud service? Let’s see.

Handling Failures is Hard

In distributed ecosystems, servers and networks function separately. Unlike a single-machine scenario, if the network fails, the client’s machine keeps on working. This calls for distributed systems engineers to carry out extensive testing of all aspects of the network including multiple servers. 

In order to do this, systems engineers test every function for the very way they could fail and the resulting consequences on the rest of the code. This means writing test cases for every possible case a system can fail.

Testing Distributed Systems is Complex

A distributed system can face multiple permutations of errors. It gets quite complex to track these computations, especially when there are multiple requests, for example, sending messages. The hardest error to tackle in a distributed environment is an unknown error.

Distributed Bugs

Bugs in large distributed systems are latent. They can take up to several months to show across the entire system after deployment. It takes even more time to remove such bugs by triggering specific scenarios.

In short, the challenges engineers face with distributed computing include,

• They have to consider permutations of errors in critical systems. Most errors can happen anywhere, anytime, and independent of another error condition. They can’t combine error conditions.
• There are complex failure modes, e.g, the result of a network operation can be unknown like succeeded, server rejected, etc.
• Distributed computing errors occur everywhere from logical levels to low-level physical machines.
• The problems are more complex at higher levels with low fault tolerance.

Should you consider a distributed computing system over AWS?

Your business requirements, software development capabilities, and IT architecture capabilities will determine whether to build a distributed computing system or to sign up with a managed cloud services provider like AWS.

E.g., if you need to distribute the workload across several servers and have the capabilities to design and build an effective and secure distributed computing system, then such a system could work for you.

On the other hand, do you need a fully-managed, reliable, performant, and scalable on-demand computing resources over the Internet? In that case, you should choose AWS or a similar managed cloud services provider with a solid track record.

Planning to build a strategic app?

Depending on the circumstances, you can opt for either distributed computing or cloud computing. However, developing a strategic app involves many more complexities, and I recommend that you engage a reputed software development company for such projects.

Our guide “How to find the best software development company?” can help you to find one.

If you are still looking for experienced cloud engineers skilled in the relevant programming languages, tools, etc., DevTeam.Space can help you. The expert developer community at DevTeam.Space is an expert in all the latest technologies including AWS cloud computing.

You can partner with these software engineers by filling out your initial project requirements via this form and one of our technical managers will get back to you for further discussion.

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