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How to build and deploy a Python application on EKS using Pulumi
Introduction
In an earlier article, we saw how to bootstrap a new EKS cluster using Python and Pulumi. In this article, we will build upon the EKS cluster and deploy a Python Flask application.
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How to setup an AWS EKS cluster with the AWS Load Balancer Controller using Pulumi
Table of contents
Introduction
Pulumi is an Infrastructure as code platform that lets you create, deploy and manage AWS resources using a programming language like Python. Pulumi supports multiple cloud providers as well multiple different programming languages.
Pulumi is similar to Terraform which is also a popular Infrastructure-as-code platform. A major difference between Pulumi and Terraform is that Pulumi lets you choose one of the support general-purpose programming languages whereas Terraform has a domain-specific language called Hashicorp Configuration Language (HCL).
In this tutorial we are going to try and do the following:
- Use Pulumi with Python to setup our Infrastructure
- Setup an AWS EKS cluster
- Enable the AWS Load Balancer Controller
- Deploy a simple application to the EKS cluster that is publically accessible over the internet
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How to use Pulumi and Python to create an EC2 instance
Introduction
Pulumi is an Infrastructure as code platform that lets you create, deploy and manage AWS resources using a programming language like Python. Pulumi supports multiple cloud providers as well multiple different programming languages.
Pulumi is similar to Terraform which is also a popular Infrastructure-as-code platform. A major difference between Pulumi and Terraform is that Pulumi lets you choose one of the support general-purpose programming languages whereas Terraform has a domain-specific language called Hashicorp Configuration Language (HCL).
Pulumi is an open-source tool and it provides both free and paid tiers based on usage. For this tutorial, we will be using the Community version which is free for individual use.
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AWS Elasticache Deep Dive: What is it and when to use it
Introduction
AWS offers a broad selection of datastores and therefore, it is important to choose the right datastore for your application. Amazon Elasticache is a fully-managed in-memory data store that supports both Redis and Memcached. In-memory databases provide low latency lookups and high throughput.
Common use-cases for Elasticache are:
- Caching
- Real-time data analysis
- Leaderboards
- Chat rooms
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AWS IAM, Boto3 and Python: Complete Guide with examples
AWS Boto3 is the Python SDK for AWS. Boto3 can be used to directly interact with AWS resources from Python scripts. In this tutorial, we will look at how we can use the Boto3 library to perform various operations on AWS IAM. IAM (Identity & Access Management) can be used to create new AWS users, manage their permissions, create new policies and much more.