AWS – How to Scale and Manage Distributed Systems?

AWS cloud computing

How to manage cloud environments in processes such as application migration, automatic deployment, or creating stable and secure environments? We prepare production environments using AWS services and Docker containers in Studio Software projects.

We participate in many technical training sessions as part of our knowledge development. In this regard, in late 2021 and early 2022, we organized a special workshop on comprehensive AWS services in collaboration with Noble Prog. These meetings aimed to focus on the knowledge of elastic application scaling and creating servers for specific web applications.

Below we will discuss some of the key issues discussed at the training in terms of scalability of cloud operations.

VPC and security

VPC or Virtual Private Cloud is a service that allows you to run AWS resources in a defined virtual network. The primary purpose of the operation is to provide complete control over the virtual network environment, including resource deployment, connectivity, and security. When configuring VPC resources, we add resources such as Amazon Elastic Compute Cloud (EC2) and Amazon Relational Database Service (RDS) instances. We also specify security, communication between accounts, availability zones, or AWS regions.

Grafika do artykułu_Configuring EC2 instances_EN

Elastic Load Balancing – flexible server load management

We also extensively discussed creating a scalable infrastructure to balance loads flexibly during the training. Elastic Cloud Balancing feature automatically distributes incoming traffic across multiple destinations, such as EC2 instances, containers, and IP addresses, in at least one availability zone.

Moreover, EC2 monitors the status of registered targets and routes traffic only to unloaded destinations. Flexible load balancing is essential when inbound traffic varies over time. It can automatically scale to most workloads.

Using a load balancing module improves application availability and fault tolerance. To this end, we analyzed the configurations for adding and removing compute resources from the load balancing system, monitoring control of resource health, creating auto-scaling groups, or moving the encryption workload of the load balancing system.

Implementing S3 as a data availability feature

Another topic was analyzing the performance of Amazon Simple Storage Service (S3) Replication, which replicates objects between resources as a fully managed and affordable feature. It gives great flexibility and functionality in cloud storage, providing the control needed for high data availability and other business needs. For example, with this service, you can configure the Amazon S3 service to replicate objects across different AWS regions automatically, so you don’t have to worry about failures in a specific part. Moreover, the S3 service enables latency analysis to verify and correct configuration issues quickly.

Elastic BeanStalk as a next step in the flexibility of AWS services

We also conducted a hands-on workshop where we created an application for our client, then migrated it to the cloud. Elastic Beanstalk makes it easier to manage in the cloud without knowing the entire infrastructure that runs these applications. It reduces management complexity without limiting choice and control. Upload an application, and the Elastic Beanstalk service automatically handles the details of capacity provisioning, load balancing, scaling, and monitoring application health.

These are just a few of the many topics about Elastic Beanstalk scaling applications in the cloud covered in training and workshops. We believe that updating and expanding on AWS service configuration topics will further impact the high quality of your deployed projects and the scalable growth of your organization.

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