aws-cloudformation-coverage-roadmap VS docker

Given AWS CloudFormation is AWS's native language and service for infrastructure as code, you will likely find more official quickstarts provided by AWS in the language. In addition to this, AWS Support will probably be more capable of assisting you with issues when you need help. AWS Support is essential for large enterprises, particularly those new to the cloud or slow to adopt. These types of organizations may have a skill gap within their organization regarding their cloud skill set, and in turn, they are more likely to use AWS Enterprise Support.

Today, I will show you how to build Amazon Location Service, which allows you to build location-based applications within your AWS environment using AWS Cloud Development Kit (AWS CDK) and AWS CloudFormation. I will also show examples of the recently popular CDK Migrate and AWS CloudFormation IaC generator.

AWS CloudFormation: Speed up cloud provisioning with infrastructure as code.

Infrastructure as Code (IaC) is an important part of any true hosting operation in the public cloud. Each of these platforms has their own IaC solution, e.g. AWS CloudFormation. But they also support popular open-source IaC tools like Pulumi or Terraform. A category of tools that also needs to be discussed is API gateways and other app-specific load balancers. There are applications for internal consumption, which can be called microservices if you have a lot of them. And often microservices use advanced networking options such as a service mesh instead of just the native private network offered by a VPC.

Cloudformation (IaC) does not need to be introduced to anyone, plus if you read the previous blogpost, the terraform provider (CC) we used is based on Cloudformation. Moreover, you will notice a lot of similarities, after all, we are implementing the same scenario, but with a different tool.

AWS Application Composer launched in the AWS Console at re:Invent one year ago, and this re:Invent it expanded to the VS Code IDE as part of the AWS Toolkit - but that’s not the only exciting part. When using App Composer in the IDE, users also get access to a generative AI partner that will help them write infrastructure as code (IaC) for all 1100+ AWS CloudFormation resources that Application Composer now supports.

CloudFormation

Of course, best practices today dictate that we should be deploying our infrastructure as code, using tools such as CloudFormation or Terraform.

If you're provisioning the above resources for the first time, you'll have to either configure Terraform to use specific AWS keys as you won't have OIDC connection yet. In my case, I chose to have those pre-requesites resources in a CloudFormation template and deploy them with StackSets.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

Linux Mint with Cinnamon: https://www.linuxmint.com/ as far as desktop OSes go it's familiar (Ubuntu without snaps by default), whereas the UI feels both snappy, doesn't use too much resources and is actually pretty to look at.

MobaXTerm: https://mobaxterm.mobatek.net/ this one is a bit more Windows centric but I ended up paying for it and replaced mRemoteNg and PuTTY with it, it's even better than Remmina or whatever Linux has to offer - you can manage SSH/RDP/VNC/... sessions, input across multiple sessions side by side and it just simplifies things a lot (jump host support, a port forwarding too and so much more).

GitKraken: https://www.gitkraken.com/ also a piece of software that I paid for, this one actually makes using Git pleasant, feels better to use than SourceTree and Git Cola (even though that latter is wonderfully lightweight, too) and honestly I prefer that to the CLI nowadays.

Kanboard: https://kanboard.org/ is a lightweight Kanban project management tool, it might not have every feature under the sun but it's the most snappy project management tool I've ever used, looks simple and runs well. I honestly love it, what a nice thing to have.

Most modern text editors and IDEs: I personally pay for JetBrains IDEs but also like Visual Studio Code as a text editor and both have helped me immensely, they're reasonably performant when you have the RAM, look nice, often give you suggestions about how to improve your code and also have a plethora of plugins in their ecosystems. Nowadays I unapologetically use LLMs as well and overall it feels like I have these great tools and cool autocomplete (that is sometimes a bit silly and wrong) at my disposal, that makes me happy.

Kdenlive: https://kdenlive.org/ imagine if there was a successor to Windows Movie Maker, though something that gets most of the important stuff out of Sony Vegas, except is also completely free and works on most platforms. Kdenlive is all of that and also somehow quite pleasant to use, I actually prefer it to DaVinci resolve. There is a bit of a learning curve to any piece of software like this, but everything mostly makes sense in this one.

Gitea: https://about.gitea.com/ I still use this for my personal Git repositories and integrating with CI systems and it's lightweight, looks good and just feels pleasant to use. Previously I self-hosted GitLab and constantly ran into resource exhaustion as well as doubts about the next update is going to corrupt all of my data and break (it did), so now I use Gitea instead.

Drone CI: https://www.drone.io/ a container native CI solution that I can also self host. It's container oriented, integrates with Gitea nicely, is similarly nice to GitLab CI and doesn't cause me headaches like Jenkins would.

Docker: https://www.docker.com/ yes, even Docker desktop. It just makes working with containers really pleasant and predictable, even when something like Podman also exists (and also is great). I don't know, I feel like Docker really saved me from having brittle legacy environments, even self-contained containers with health checks and resource limits with still the same brittle code inside of those make me feel way more safe.

Note: Before running your application in the next step, make sure you have Docker installed and running. It's required to locally run Encore applications with databases.

Developing WordPress plugins and themes often requires a reliable development environment. Current we have good solutions as wp-env from Autommatic, Local WP from WP Engine, Docker, XAMPP (for old ones) and so on. All this can be good suits for a development environment, specially Local WP that is probably the easiest one to get up and running and wp-env that leverages Docker as a development environment in a very easy way to use.

Docker, an open-source development platform, provides containerization technology for building and packaging applications along with their dependencies into portable images.

With each app containerized with Docker, this allows it to be run on any other developer's machine also running Docker. Although I had automated deployments to Heroku without this, I decided to upload each service to a container registry.

Docker

Today we are going to see all the power that a CLI (Command line interface) can bring to development, a CLI can help us perform tasks more effectively and lightly through commands via terminal, without needing an interface. For example, git and Docker, we practically use their CLI all the time, when we execute a git commit -m "commit message" or docker ps -a we are using a CLI. I'm going to leave an article that details what a CLI is.

Docker (required): Understanding Docker is crucial for deploying software in containers, making your project portable and scalable. I use it for start Folo server.