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As a passionate advocate for automation, I have been using AWS CloudFormation since the first day I started migrating my applications to AWS. I need to manage my time efficiently and should not repeat myself. By applying automation in infrastructure provisioning and keeping my architecture as a code, I can save, test, and re-use my work later.

Managing your infrastructure as code is one of the key DevOps practices, and AWS CloudFormation is your service on AWS to realize it. In this post, I explain 11 reasons for using AWS CloudFormation and automating the provisioning of your infrastructure.

Save your time, bring quality to your process by starting to prepare your CloudFormation templates today!

Let’s say that you are a developer building awesome applications using Node.js or Python but lacking the knowledge and experience necessary to configure AWS environments. No worries! Elastic Beanstalk can make your life easier by handling configuration details. It uses preconfigured CloudFormation templates and provisions a scalable, load-balanced, and reliable environment for your application. It supports many programming languages, giving you less control but less worry in return. You can start from a single instance and make your architecture grow into a multi-instance cluster.

Although it may sound simple until now, Elastic Beanstalk is more than described here. It provides you many deployment options, and you can select one of them depending on your environment and use case. In this post, I will explain the options and when to consider them. Read more at Which AWS Elastic Beanstalk Deployment Method Should You Use? post.

Automating deployments of your web applications brings many benefits, especially when you run them on AWS. You standardize the process, prevent human errors, and can integrate with other AWS services like EC2 Autoscaling and Elastic Load Balancing. Today I will talk about how to automate your Ruby on Rails deployments using AWS CodeDeploy. Read more at Automating Ruby on Rails Deployments with AWS CodeDeploy post.

In recent days, I made some trials for connecting to MongoDB databases from AWS Lambda functions using Python. In today’s post I will share my experiences with you and take some notes about these trials for future reference. We will install MongoDB on an EC2 instance and develop simple Python functions to access it. Let’s start! Read more at Accessing a MongoDB instance from AWS Lambda using Python post.

In some cases, you may need to transfer your objects in one of your Amazon S3 buckets to a different AWS account. AWS CLI provides high-level commands on S3 to move objects between two buckets. By also using Amazon S3 bucket policies, you can perform this even if the destination bucket is in another AWS account. Today, I will talk about the steps you need to do along with a few explanation on bucket and object level permissions. Read more at Copying S3 Bucket Objects to Another AWS Account post.