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AWS Disaster Recovery Strategies – PoC with Terraform

Xebia

This post explores a proof-of-concept (PoC) written in Terraform , where one region is provisioned with a basic auto-scaled and load-balanced HTTP * basic service, and another recovery region is configured to serve as a plan B by using different strategies recommended by AWS. Backup service repository. Backup and Restore.

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Mastering AWS Infrastructure as Code with Pulumi and Python

Perficient

The goal is to deploy a highly available, scalable, and secure architecture with: Compute: EC2 instances with Auto Scaling and an Elastic Load Balancer. Amazon S3 : Object storage for data, logs, and backups. AWS Lambda : Serverless computing service for event-driven applications. MySQL, PostgreSQL).

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CASE STUDY: Moving at the Speed of Cryptocurrency with Infrastructure as Code

Blue Sentry

You can also build automation using Lambda Functions with custom triggers like AutoScaling Lifecycle Hooks, have a Load Balancer in front of your servers to balance the traffic as well as have DNS management in Route53.

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AWS Microservices Architecture – Enabling Faster Application Development

RapidValue

Some of the key AWS tools and components which are used to build Microservices-based architecture include: Computing power – AWS EC2 Elastic Container Service and AWS Lambda Serverless Computing. Networking – Amazon Service Discovery and AWS App Mesh, AWS Elastic Load Balancing, Amazon API Gateway and AWS Route 53 for DNS.

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AWS Cost Optimization: Strategies For Scaling Businesses Within Your Cloud Budget

Mobilunity

Their expertise in optimizing EC2, S3, and Lambda confirms businesses particular expenses for the resources they indeed need, lowering costs while maximizing performance. Load balancing optimizes traffic distribution across instances to maximize resource usage. AWS tools: Auto Scaling Groups, Elastic Load Balancer (ELB).

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