Last Updated on May 10, 2023 by hassan abbas
What is Amazon Web Services (AWS)?
Amazon Web Services, a web-based platform, offers scalable and economical cloud computing solutions.
AWS, a widely used cloud platform, provides on-demand services such as processing power, database storage, and content distribution.
While AWS offers a wide range of services, determine which ones are best for your needs. This article explains the top ten most popular AWS service offerings related to various business demands.
The Top Ten AWS Services
1. Amazon Web Services EC2 – Elastic Compute Cloud
Amazon EC2 is a web service that provides compute capacity in the AWS cloud. The operating system, application software, and relevant configuration information can be bundled together in an Amazon Machine Image (AMI) (AMI). These AMIs can then generate new virtualized instances and shut them down using web service requests.
You can scale up or down the number of EC2 instances as your needs vary. These instances can be deployed in at least one geographic area or district, thanks to availability zones (AZs). Each site has several AZs, all of which are connected by low-latency networks in the same general area.
Use Cases for Amazon’s Elastic Compute Cloud (EC2)
You can set up virtual machines on the go with Amazon Elastic Compute Cloud (EC2), with no large infrastructure investment and low beginning expenses. Use the AWS admin console or automation scripts to additional provision servers for production and testing environments quickly and then shut them down when they’re no longer needed.
AWS EC2 is commonly used in the following scenarios:
On-demand infrastructure can host a wide range of software, from simple websites to enterprise-grade web applications. It’s simple to lift and shift from on-premises because you have complete control over the operating system. Spot pricing might save you up to 80% to 90% on your hosting costs.
With auto-scaling and load balancing features, you can build a fault-tolerant architecture.
Choose EC2 accelerated computing instances if you need a lot of processing and GPU capability for deep learning/machine learning.
2. Amazon Web Services RDS (Relational Database Service)
With Amazon RDS, you can quickly and easily set up, operate, and scale a cloud-based relational database. It provides cost-effective and scalable capacity while also taking care of time-consuming database administration tasks, including hardware provisioning, database setup, patching, and backups. It frees you to focus on your apps, allowing you to increase their performance, availability, security, and compatibility.
This service is available on Amazon’s Aurora, MySQL/PostgreSQL/Oracle, and SQL Server engines, as well as six other well-known databases. The same code, apps, and tools that you use with your current databases may be used with Amazon RDS. Amazon RDS backs up and fixes your database automatically, storing backups for a user-defined retention period and allowing for point-in-time recovery.
With just a single API call, you may scale up or decrease your relational database instance’s computation and storage capacity. Furthermore, Amazon RDS makes replication for production databases simple to install. You may boost the capacity of a single database setup for read-heavy applications by using Amazon RDS for MySQL. There are no upfront expenses with Amazon Web Services.
Use Cases for the Relational Database Service (RDS)
The Amazon Relational Database Service (Amazon RDS) is a managed database service that relieves a lot of database management, maintenance, and other duties.
AWS RDS is commonly used in the following scenarios:
Install a new database server in minutes and drastically improve dependability and uptime without incurring additional overhead or personnel expenditures. OLTP/transactional databases with fairly detailed day-to-day database requirements are a good fit.
With various database engines, you may customize the configuration for each database deployment (MySQL, MariaDB, PostgreSQL, Oracle, and Microsoft SQL Server). Set up automatic failover (Multi-AZ RDS setup), automated backups, and seamless resizing of database deployments based on traffic and application needs. Allows you to concentrate on the application rather than the database.
Use RDS in conjunction with NoSQL databases like DynamoDB or Amazon OpenSearch Service (for low-latency/high-traffic use cases) (for text and unstructured data).
3. Amazon Web Services Lambda
AWS Lambda is a serverless computing platform powered by events of Amazon Web Services. This means you won’t have to worry about deploying AWS resources or managing them. On the other hand, Lambda is where the code is placed and executed.
Add/delete S3 buckets, HTTP requests via Amazon API Gateway, and other operations trigger code execution in AWS Lambda. On the other hand, Amazon Lambda can only perform background tasks.
Thanks to AWS Lambda functions, you can concentrate on your core business logic instead of worrying about the operating system (OS) access control and patching, OS right-sizing and provisioning, scalability, and so on.
Use Cases for Lambda Function-As-A-Service (FaaS)
Lambda is an excellent technological choice for event-driven background processing.
The following are some examples of AWS Lambda use cases:
For newly submitted photos, image manipulation is available.
Processing of metric data in real-time.
Validation, filtering, and modification of streaming data.
Lambda is excellent at handling enormous scale loads without requiring you to allocate more infrastructure to your application. AWS Lambda is metered by rounding up to the closest millisecond with no minimum execution duration, unlike Amazon EC2, which is charged by the hour but metered by the second.
It’s vital to remember that serverless is designed for temporary and event-driven applications. According to good serverless design principles, the environment should be assumed to exist just for a single invocation. Serverless is not the proper design choice if you rely on data structures or temporary files to keep the internal state between successive invocations.
4. Amazon Web Services S3 – Simple Storage Service
Simply stated, Amazon S3 stands for Amazon’s Simple Storage Service. Elastic Block Store is a cloud storage service provided by Amazon Web Services (AWS) (EBS). Many clients use it for a variety of things, including:
It is possible to recover after a natural or man-made disaster in the event of a calamity.
Analytics based on enormous volumes of data Cloud storage that is both hybrid and on-premises Apps for the Internet Lakes of data
Cloud-native applications require data storage.
A web-based management panel called S3 Administration Dashboard makes it simple to organize data and set up exact access rules. Standard protocols can also be used to access and upload to Amazon S3.
Use Cases for the Simple Storage Service (S3)
Archive old data that isn’t used very often. This is a good solution for on-premises NAS (Network Attached Storage) or external hard disks. Aids in the safe and secure storage of your data without the risk of data loss.
With no performance or operational overhead, you may automatically shift data to the most cost-effective access tier with S3 Intelligent-Tiering.
In S3, you can save static and dynamic assets like user-generated content (images), backup files, and raw event data/logs (for example, JSON or XML). Take the pressure off web servers by serving from a global network of highly accessible and redundant locations. You’ll also get regional assistance for holding assets in certain areas worldwide to meet regulatory obligations.
Tip Creating S3-based applications
5. Elastic Container Service (ECS)
AWS introduced Amazon ECS in 2014 as a simplified way for managing Amazon Elastic Compute Cloud (EC2) instance containers. Because of their small size and portability, containers may be easily deployed, separated, and distributed across multiple endpoints using Amazon ECS.
Amazon ECS resources can be created, accessed, and managed using a variety of Amazon interfaces, including the AWS Management Console, AWS Command Line Interface (AWS CLI), AWS SDKs, and the AWS Copilot service.
Developers can use an API or task definitions in Amazon ECS to deploy and manage applications running on clusters.
ECS can be used to manage and start a container cluster. By defining Amazon ECS containers in task definitions, you can operate services or tasks independently.
The AWS Fargate allows ECS to execute tasks or services on the serverless infrastructure. Amazon ECS users may simply deploy and administer containerized programs to their managed instances without manually installing, operating, and managing container orchestration software on-premises.
Use Cases for Elastic Container Service (ECS)
AWS Batch can use Amazon ECS to distribute tasks among containers. The Amazon ECS is useful for microservices, websites, video rendering services, machine learning, and other applications and fields.
Microservices built on containers change how DevOps analyzes and deploys apps and services. Amazon ECS makes deploying microservices and enabling service discovery a breeze, allowing you to alter and deploy any service without affecting others.
Amazon ECS Anywhere delivers consistent tools, workload scheduling, management, and monitoring across environments for container-based applications in the cloud or on-premises.
Amazon ECS is used to automatically scale and execute web applications that take advantage of AWS’ performance, dependability, scale, and availability in different availability zones.
Amazon ECS is used by AWS’s whole suite of services, including Amazon EC2, Amazon EC2 Spot Instances, and Fargate, to simplify batch processing, planning, and scheduling.
According to many businesses, the top five most popular AWS Services are like pearls waiting to be discovered in the cloud. They are cost-effective and secure, and they aid in maintaining operational efficiency. Any AWS service that you believe will match your infrastructure needs can be analyzed, road mapped, implemented, and optimized with the help of AWS Consultant Services.