AWS Training in Singapore

Deploying this multi-tier website requires learners to launch an EC2 instance and deploy the website on it. Make sure that the architecture is scalable and fast enough to use while keeping the upfront cost low or zero.

In this project, the learners have to design an architecture that automatically scales up and down based on the workload, using ELB. It is important to create a decoupling architecture to connect the RDS database and an EBE.

Develop a push notification systems, which will send necessary notifications to patients based on their doctor’s prescription. Use AWS SNS for sending messages and integrate EC2 that is created in a VPC with SNS topic for storing the message.

Build an app that uploads objects from the S3 bucket to Elastic Beanstalk. Set up Lambda functions as object creation in the S3 bucket and add Lambda code to segregate the uploaded objects into separate buckets as per the extension.

Replicate EC2 instances to varied regions depending on availability. The main strategy is to extend the size of EBS volumes without losing the data, ensuring to scale and mounting them to different EC2 instances one at a time.

The project involves auto scaling and load balancing among multiple EC2 instances within AWS based on varied or defined metrics for autoscaling instances. The project also deals with routing custom domains to AWS resources.

In the project, the learners will create a custom VPC in AWS with the help of subnets that have both private and public access. The route tables are also configured to subnets by using the internet and the NAT gateway.

The project deals with moving artifacts from on-premise to S3 in the most cost-efficient manner. It also deals with creating Lifecycle rules for events in S3 objects, hosting a static website, and experimenting with Route 53.

This project is about creating a highly available and scalable AWS database service by using RDS. The process involves creating Database Architecture, collecting data for real-time analysis, and relocating latency issues.

This project involves the learners provisioning and deploying AWS resources by using CloudFormation. In the process, the learners also have to define the deletion rules, by using IaC and minimize the deployment time.

In this project, the learners will create users in Identity Access Management to define granular access that differs for every user. The learners will also define custom policies that add users to the groups.

The main aim of this project is to make the learners use the application services in AWS Lambda for deploying the code and to conduct configuration management by using OpsWorks. The Web app is also deployed to Elastic Beanstalk.