What You need to Know About AWS Before Start Using It?

A common question for AWS newcomers is – what does Amazon AWS stand for? AWS means Amazon Web Services. This is a global corporation providing various cloud services to organizations, institutions, and companies of all sizes worldwide – from small local bakeries to Netflix and even NASA.

In this short AWS tutorial, we will illuminate the reasons behind such omnipresence and describe AWS's advantages, its types, costs, alternatives, and more.

What is AWS?

One of Amazon’s subsidiaries, AWS offers a wide variety of on-demand cloud services, such as storage, computing, analytics, and security. It dominates the cloud infrastructure service industry, with a third of the market share. For comparison, its closest competitor is Microsoft Azure, with 21% of the market. Its second competitor is Google Cloud, which currently has only an 8% market share. Other companies providing similar services include IBM Cloud, Oracle Cloud, Dell Technologies Cloud, and Alibaba Cloud.

What are Amazon Web Services used for?

AWS’ popularity is unprecedented, but you might wonder – precisely what does AWS do for companies? Well, it can help resolve a variety of business challenges. The most common uses of AWS are:

Data storage, backup, and cloud migration

Amazon offers several services for data storage and backup, as well as cloud migration and data transfer. Businesses can choose the most cost-effective solution for their needs. When deciding, one should consider the amount of space needed, how often they would access the storage and how fast the connection should be.

Cloud computing, analytics, and Big Data management

AWS provides various solutions facilitating cloud computing, including those explicitly tailored to streamline data analytics and management of Big Data. Examples of valuable services include Kinesis, EMR, and Amazon Glue.

AI and Machine Learning

A range of AWS services is dedicated to Artificial Intelligence and Machine Learning. AWS AI services are ready-made solutions that can be added to the software. In most cases, this is more cost-efficient than creating AI from scratch since it doesn’t require a significant upfront investment. Using AWS AI, developers can automate video and image analysis, detect fraud or data anomalies, predict hardware maintenance needs, enable software to recognize human speech and converse with users, and much more.

Machine Learning can be streamlined with Amazon SageMaker. The service helps reduce training time, automates MLOps practices, optimizes infrastructure usage, and more. AstraZeneca, Roche, Lenovo, Thomson Reuters, and Hyundai already use this service.

SDLC tools

AWS provides tools useful at all stages of the software development life cycle. When talking about mobile and front-end web development, we can categorize tools by SDLC stages. Thus for development, one could use AWS Amplify, Amazon Chime SDK, AWS AppSync, Amazon Location Service, and Amazon API GateWay. To facilitate deployment — AWS App Runner and, again, AWS Amplify. AWS Device Farm expedites testing. For performance monitoring, developers use Amazon CloudWatch. Valuable services for the back end are AWS Lambda and DynamoDB.

Marketing & Content delivery

With AWS, companies can utilize real-time analytics and AI-powered personalization, launch marketing messaging campaigns, and create marketing data lakes – amalgamations of data from different sources for further analysis.

The AWS tool for content delivery is called Amazon CloudFront. It expedites worldwide content delivery. Learn more about it in the next section of the article.

Three major AWS advantages

High demand for AWS is fully warranted as it offers significant advantages, including:

Flexibility and scalability

Amazon provides a wide variety of services and subscription plans. Every business can find what they need. Scalability is also not an issue – adding more capacities is simple when it is required. One drawback is that finding the right options is an intricate, complex process that requires either days of research or hiring a dedicated tech team. Making wrong choices results in unnecessary overhead, sometimes amounting to thousands of dollars per month. Check out our SOLD.com case study to learn how our dedicated development team helped our client save thousands on AWS costs.

Time and cost-effectiveness

AWS can be remarkably cost-efficient. Users save a lot on upfront and maintenance costs. In many cases, cloud solutions are the only way to keep business profitable – imagine what it would take for each small retailer to set up their own server rooms.

Using AWS, businesses can deliver services much faster while remaining agile and receptive to change. With AWS, they can get a plethora of benefits with several clicks.

For example, one could almost instantly add a virtual assistant, Amazon Lex, to their software. Training such AI from scratch would take more than 6 months and cost hundreds of thousands of dollars. With AWS, it costs less than 40 USD for 10 thousand speech requests and 7.2 USD for the same number of text requests.

Reliability and security

AWS is exceptionally reliable. It boasts the highest network availability among cloud service providers.

To ensure service dependability, Amazon follows 5 design principles:

• Automated failure recovery,
• Testing of recovery procedures,
• Horizontal scaling to increase availability,
• Workload utilization monitoring and automatic resource adjustment,
• Change automation.

AWS also has rigorous security protocols. Moreover, its systems are monitored 24/7 by some of the world’s brightest engineers for possible security risks.

Top 10 most popular AWS services

Overall, AWS offers more than 200 services to its customers. Some of the most widely used AWS services in 2022 are the following:

Amazon EC2

With EC2, users can create virtual servers (also called instances) using AWS, meaning they receive scalable on-demand storage and cloud computing capabilities. Businesses can use this cloud infrastructure to host websites or web apps, manage databases, and more. Using EC2, customers choose which virtual servers they need – memory-optimized, compute-optimized, general purpose (GP), accelerated computing, etc. Choosing wisely is critical – by optimizing the selection of virtual servers on a similar cloud platform, our team reduced our client’s cloud infrastructure costs by 40%.

Amazon S3

S3 is an object storage service. It is relatively low-cost and very secure. The service has various integrations needed to ensure compliance with HITECH, HIPAA, FedRAMP, and other regulations.

AWS Aurora

Amazon Aurora is a relational database (RDB) compatible with PostgreSQL and MySQL. It is perfect for storing data organized in tables. Moreover, it is scalable and supports the automation of simple tasks.

DynamoDB

DynamoDB is a NoSQL database that supports storing and retrieving data that is not organized in tables. The service doesn’t cost much and offers high performance.

Amazon RDS

Amazon RDS is a relational database similar to Aurora. The two have different architectures, which results in Aurora being somewhat quicker and having higher availability. On the other hand, Amazon RDS might be cheaper in some cases and it has an automatic failover feature.

Amazon Lambda

Amazon Lambda is a computing service that allows users to run code virtually without the need to manage servers.

Amazon VPC

Also known as Amazon Virtual Private Cloud, this service enables users to launch resources (including other AWS services) on a private network in the cloud. Customers have complete control over this environment and can configure encryption, operating systems, access, and other elements.

CloudFront

Amazon CloudFront is a content delivery network (CDN). The service is used by many renowned companies specializing in content delivery, such as Reuters, Hulu, and Slack. CloudFront ensures faster content access and download speeds for the clients of these companies. It does so by caching bulky content in various locations of its global network of proxy servers.

AWS Elastic Beanstalk

AWS Elastic Beanstalk is the service for deploying, managing and scaling web applications. It automatically manages all infrastructure necessary to run an app, such as databases, servers, load balancers, networks, etc.

Amazon EC2 Auto-scaling

Closing our list of the 10 most used AWS services is EC2 Auto-scaling. As you might have guessed by its name, it helps to use EC2 service more efficiently by automatically adjusting the number of virtual servers (instances) according to client needs.

5 Notable Mentions:

Less known but invaluable AWS resources that we would like to highlight include the following:

Amazon SNS

SNS stands for Simple Notification Service. This service enables app-to-app and app-to-person notifications of different types – email, SMS and pushes notifications. You can read our FRFS case study to learn how Amazon SNS allowed our team to notify company clients of delivery details timely.

Amazon SQS

Amazon Simple Queue Service is a cost-efficient message queuing solution. It is a virtual middleware that puts messages in a queue. This is necessary when there are limitations to the number of requests a particular system can process. For example, our client, SOLD.com, is using the Salesforce CRM, which only permits 30k requests per day. During various marketing campaigns, this number gets surpassed very quickly. If our team hadn’t implemented a queuing solution, all the messages above 30k would have been lost.

Amazon Redshift

Redshift is a cloud-based data warehouse powered by dedicated Amazon hardware and machine learning. It is used to analyze data and process various queries needed for business intelligence. Our dedicated software development team has implemented Amazon RedShift in Distil.ai and SOLD.com projects.

Elastic Load Balancing (ELB)

ELB is a load-balancing service that evenly distributes incoming app traffic among available computing resources, such as EC2 instances, IP addresses, containers, etc. The service also can automatically scale the number of available resources when necessary.

AWS Auto Scaling

AWS Auto Scaling has functionality similar to EC2 Auto-scaling. However, while the latter is focused on managing EC2 instances, AWS Auto Scaling provides a broader application area. Aside from EC2, it can be used with Aurora, DynamoDB, and other services. Another difference is that EC2 offers more flexibility in configuring scaling patterns. It also provides an option for predictive scaling powered by machine learning. With AWS Auto Scaling, on the other hand, users can set target resource utilization levels. For example, “Increase capacity when CPU utilization exceeds 80%”.

The feature is very convenient. By implementing it, our dedicated development team has managed to save one of our clients, SOLD.com, around 2k USD per month – a 23.5% decrease in their AWS costs.

AWS for business: world-renowned companies that use Amazon Web Services

AWS has more than a million active users. This includes 51 Fortune 500 companies, such as the Bank of America, IBM, Microsoft, Walmart, Unilever, Procter & Gamble, FedEx, and many more.

AWS clients represent nearly all industries. For instance, in the healthcare sector, AWS is used by AstraZeneca, Roche, Pfizer, GE Healthcare, and Cerner, among others. In the energy sector, it is utilized by ENGIE, ExxonMobil, BP, Bajaj Energy, Edison, and GE Renewable Energy. FinTech companies using AWS include PayPay, Western Union, Goldman Sachs, Volkswagen Financial Services, Raiffeisen Bank International, and Nasdaq. When talking about automotive, our client Volvo Group is using AWS, along with BMW, Volkswagen Group, Lyft, and many others.

AWS cost and implementation time

AWS costs vary significantly – it can be a couple of dollars or a couple of million per month, depending on which services and how much storage/computing power you use. Some of the biggest AWS spenders, Netflix, Twitch, and LinkedIn, spend 19, 15, and 13 million USD per month on AWS. The key is to select the right combination of services, covering all your needs without overspending. Our dedicated software development team would happily assist you with this task.

AWS implementation time depends on your starting point. Thus, the process is pretty fast if you don’t yet have any physical or virtual infrastructure and want to use AWS for a small business or personal use. It might just be a matter of setting up an account.

On the other hand, it is less straightforward for large corporations that decide to migrate. Often they need to move terabytes of data. AWS offers some tools to facilitate such transitions. Thus, the company has shared a case study detailing how one of its clients migrated north of 100 TB of data in their cloud, using Amazon FSx and DataSync services.

AWS maintenance and support

So, how does AWS work regarding support and maintenance? Amazon regularly performs scheduled maintenance of its virtual servers. This might include making updates and installing patches or software. AWS is taking steps to minimize possible impact. However, minor disruptions might occur. Therefore, users are advised to schedule maintenance in the most appropriate timeframe. For example, US-oriented companies can choose 9:30 to 10:00 GMT when the majority of their customers are asleep and the traffic is low.

Regarding support, AWS has several support plans. The basic one is available for all customers for free and includes 24/7 access to customer service and documentation, as well as AWS Trusted Advisor and Personal Health Dashboard services.

Trust Softkit Experience

Softkit is a bespoke software development agency with extensive experience in helping companies with their AWS needs, including:

• Selecting suitable AWS services and subscription plans,
• Lowering AWS costs,
• Ensuring smooth migration to AWS without the disruption of workflows.

Our most vivid case studies of using AWS include the following:

Cloud-based processing of requests for the Volvo Group vehicles – more than 4k+ requests are processed per second at peak times. Moreover, we ensured 99,9999999%+ of software uptime using AWS Managed Services, DevOps automation, and server scaling;

1. Image analysis using Amazon Rekognition for the FRFS marketplace ensures that there is no forbidden content such as violence, nudity, weapons, or smoking on product photos uploaded by vendors. Our team also used Amazon SNS to set up messaging for the client.
2. Decrease in AWS costs by 23.5% (around 2k USD) per month for SOLD.com by implementing the AWS Auto-scaling feature.
3. For SOLD.com, we also utilized Amazon SQS to set up a message queuing system. This was necessary since the company uses Salesforce – a CRM with a limit of 30k requests per day. During marketing campaigns, this number is exceeded and without Amazon SQS, some data would be lost. Another AWS product implemented for the client was AWS Data Pipeline to set up data transfer from Attom Data.
4. Implementing AWS S3 and RedShift for Distil.ai – a marketing analytics platform requiring substantial data storage and processing capacities.

Learning all about AWS can take months. Luckily, you do not need to — Softkit is here to help.