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Aman Kumar

Aug 09 · 5 min read

AWS Architecture And Its Components

AWS is some of the best and most Well-known Cloud Computing markets today. Now, almost one-third of all Internet sites or applications are powered by AWS. As a result, AWS holds a vast market share in the Cloud Computing sector. Therefore, it becomes necessary to learn this technology.

AWS has an active customer base traversing over 190 countries and more than a million customers, including more than 2,000 government agencies, 5,000 education institutions, and nearly 17,500 non-profits.

With demand for AWS constantly increasing, it also invites many opportunities for SMEs and other companies to take their business to another level. Learn how AWS architecture forms the future business landscape and how Kockpit can help you automate your business processes.

What is AWS?

AWS Architecture comprises infrastructure as service components and other managed services such as RDS or relational database services. The basic architecture of AWS Elastic Compute Cloud(EC2).

It allows users to use virtual machines of different configurations as per their requirements. Also, It provides various configuration options, various pricing options, mapping of individual servers, etc. In AWS architecture, we use a Simple Storage Service(S3) bucket, allowing users to store and extract various types of data using API calls. Although, It doesn't contain any computing element.

AWS Architecture: Key components

Load Balancing

SiLoad balancing refers to software or hardware load over web servers that improves the efficiency of the server and the application. The hardware load balancer is a pretty standard network appliance used in the traditional web, BI & data analytics application architectures.

AWS provides the Elastic Load Balancing(ELB) service. It transfers the traffic to EC2 instances across numerous available sources and dynamic addition & removal of Amazon EC2 hosts from the load-balancing rotation. Elastic Load Balancing can dynamically grow & shrink the load-balancing capacity to adjust to traffic demands.

Amazon Cloud-front

Amazon Cloud-front is responsible for content delivery, i.e., used to deliver the website. It may contain static, dynamic, and streaming content using a global network of edge locations. The content requests by the users are automatically transmitted to the nearest edge location, thus, improving the performance and facilitating business decision-making.

Cloud-front is designed to work with other Amazon Web Services, like Amazon Simple Storage Service(S3) & Amazon Elastic Compute Cloud(EC2). It works fine with any non-AWS origin server and stores the original files similarly.

In Amazon Web Services, there are no monthly commitments or contracts. Instead, the user pays only for as much as we deliver through the service.

Elastic Load Balancer

Elastic Load Balancer or "ELB" is responsible for spreading the traffic to different web servers, thus improving performance. As per the traffic conditions, ELB can dynamically grow and shrink the load-balancing capacity.

Security Management

Amazon's Elastic Compute Cloud (EC2) provides an aspect known as security groups. Security groups are similar to an inbound network firewall, in which we have to specify the ports, protocols, and source IP ranges that are allowed to reach your EC2 instances.

Each EC2 instance can be assigned to one or more security groups, each of which routes the appropriate traffic to each instance. Security groups can be configured using specific IP addresses or Subnets, limiting access to EC2 instances.

Elastic Caches

Amazon Elastic Cache is a web service used to manage the memory cache in the cloud. It is an efficient internet service where the memory cache can be controlled in the cloud without hassle. In memory management, cache plays a critical role. It helps reduce the service load and improves the database tier's performance and scalability by caching frequently used information.

Thus, it also helps streamline BI & data analytics processes by enhancing the performance and scalability and lowering the processing time.

Amazon RDS

Amazon RDS stands for Amazon Relational Database Service and provides equal access to MySQL, Oracle, or Microsoft SQL Server database engine. In Amazon RDS, similar Queries, applications, and tools are used.

RDS automatically patches the database software and handles backups according to user instructions. It also supports point-in-time recovery. No up-front investments are required, and we only pay for the resources we use.


In analytics Power BI and Big Data services, data warehousing and data security are key aspects, and AWS allows data analytics tools to store and manage ginormous amounts of data.

AWS cloud provides various options for storing, backing up, accessing, and web application data and assets. In addition, the Amazon S3 provides a simple web-services interface that can be used to store & retrieve any amount of data from anywhere, at any time on the web.

Amazon S3 stores the data as objects within a resource called a bucket. The user can store unlimited data as per requirement within the bucket & read, write and delete objects from the bucket.


Shifting to a cloud platform invites a pool of opportunities, faster processing power, and a centralized platform where all your data is stored safely. Kockpit Analytics uses Amazon Web service for its many data warehousing, cloud computing, and content delivery needs.

We offer robust analytics big data and business intelligence solutions for various domains and firmly hold the position of best data analytics companies in Delhi NCR. Hence, we extract the full value of AWS services for our clients. To learn more, visit our official website or click here for a free consultation!

Aman Kumar


Developer, Kockpit Analytics, Frontend End Development, decision science. All views are my own.

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