First steps into AIML

Some time ago, I had a look at the AIML world. The possibilities were really interesting and it looked like a good challenge to start learning and exploring some material.
Picture this: me, diving into Machine Learning with some rest of my mathematical background.
I started with Coursera’s Standford course & the AWS ML Specialty certification to give me a guideline on how to progress.
Think of it as a treasure hunt for tech gems with the cert path as a map!

🔗 https://coursera.org/specializations/deep-learning

🔗 https://aws.amazon.com/fr/certification/certified-machine-learning-specialty/

GenAI fun

Then after passing the cert and gaining some experience with hands-on projects, the AIML rabbit hole led me right into GenAI.
I explored a bit and thought: “It’s like coding but with a splash of magic!”. The use cases sounded really interesting and promising.

When AIML meets GenAI, think peanut butter & jelly, but way cooler! Seriously, it’s the sweet spot where theory, creativity and code unite. At first, it’s all about AI creating art, crafting stories or composing music. Then you start to see awesome use cases:
📚 Education
🍃 Sustainability
🏥 Medical and Healthcare
👩‍🦯 Assistive and inclusive technology
🧑‍🔬 Research
🗓️ Productivity
🎶 Art and Creativity
🎬 Entertainment
And a lot of other fields…

Let’s build some knowledge

Later, I enrolled in the “Generative AI with LLMs” on Coursera to apply some deeper knowledge on the AWS landscape. I highly recommend it, this course is really a “must-follow” for any AI enthusiast! 👇
https://www.coursera.org/learn/generative-ai-with-llms

It tackles GenAI lifecycle for projects, transformer architecture, model fine-tuning, performance optimization, responsible AI challenges and even some reinforcement learning topics.

Oh, and speaking of resources, let’s not forget the amazing platforms that made my AIML and GAI journey even more incredible. Dive into these articles and communities that’ll help you understand the GenAI world in (nearly) no time👇

Learning resources

🔗 https://jalammar.github.io
📖 https://oreilly.com/library/view/generative-deep-learning/9781098134174/
🔗 https://huggingface.co/docs
🔗 https://deeplearning.ai/courses/
🔗 https://aws.amazon.com/blogs/machine-learning/category/artificial-intelligence/generative-ai/
🔗 https://a16z.com/2023/05/25/ai-canon/
🔗 https://promptingguide.ai
🔗 https://huyenchip.com/2023/06/07/generative-ai-strategy.html

🎉 Ready for more AIML and GenAI goodness?

From unique topics to innovative projects, I want to hear YOUR ideas! 🤔
Knowledge is best when shared so if you enjoyed this post, feel free to connect and share this post with others who might find it exciting!

Feel free to reach me on Twitter FlolightC to keep me updated about your AWS machine learning and Generative AI journey or to ask me questions! I’m always happy to discuss with you!

Believe it or not, the last step (for now!) brought me the Hashnode Hackathon!

I read the article mostly by curiosity but I found out this hackathon was the occasion to set up a real application, get a little challenge and test some capabilities of thirdweb.

At this time, I only knew thirdweb from some Twitter posts and I was really curious about how it could make the developments easier.

I started to think about an interesting idea and I got some about NFTs, DAO... I finally choose to build an opensource Coinbase-like prototype...

A few days after I started to develop a first draft on my spare time, this idea moved to building an open source educational project to help newcomers get a better understanding of how to deal with crypto tokens.

The links

The project is open source, open for contributions (even if I still need to improve the repository to help newcomers to contribute) and available on GitHub:

Find the deployed application here:

The first steps

Here is a list of some key ideas I followed to build this project.

Requirements:

• Coinbase-like design
• Connect with Metamask wallet
• Display all known tokens with their information (Name, Symbol, USD Price...)
• Display current wallet detailed balanced per token
• Display current wallet total balance
• Display wallet total balance evolution

Next steps:

• Implement the tutorial part to guide users through their first "fake" transaction
• Improve documentation
• Improve repository management to make it easier for people to use the project and contribute
• Display NFTs linked to the wallet

The Tech stack

The project is built using Next.JS framework and currently hosted on Vercel here.

For my first time trying this stack, I must admit it was super easy to start and deploy this way!

The database part is supported by Sanity.io. Again, this is a very "easy-to-set up" solution, definitely sufficient at the current step of the project and most of all, quick to use to generate the needed requests for Coin Backpack.

I created some contracts in thirdweb to represent tokens and be able to interact with them through the thirdweb SDK. This way, my application is able to retrieve the information about tokens, transactions... Of course, I also used the thirdweb Web3Provider to connect the user wallet.

It was really helpful not to have to develop totally from scratch the modules provided by thirdweb. If I had a remark to push after trying their solution, it would be that the documentation could probably be improved (but I guess it will be soon) to make it easier to find some technical details, without having to go through the guide articles (which are more tutorials than reference documentation).

Beside this point, I feel like thirdweb is probably going to become one of the references about building web3 projects fast, with ease and designed the right way.

The future of the project

I'm still working on the tool in order to dive deeper into the web3 topics and to develop the educative part. Currently, this point is, indeed, still in construction and will need some more time to be implemented and improved by users' feedbacks.

Again, if you like the project, feel free to suggest features, create issues or fork/send pull requests to the repository.

Conclusion

Thank you Hashnode team for setting this hackathon up, this was the trigger I needed to get started!

I have to admit that thirdweb help was really appreciated to simplify the development process and to abstract some highly technical operations.

I still need to spend some additional time testing more in details the NFTs related capabilities, but from what I read in the guides, it should be quite as easy to set up as the modules I already used.

I look forward using the other thirdweb capabilities in Coin Backpack or any other web3 projects in the future.

Feel free to reach me on Twitter FlolightC to share your thoughts about Coin Backpack project or to ask me questions ! I’m always happy to discuss with you!

For reference, here are some resources I used to develop this project:

• thirdweb guides
• Sanity
• Build a Coinbase clone tutorial
• Deploy your Next.JS app with Vercel

Two years ago, machine learning meant nothing to me and Artificial Intelligence was just some hyped word with disparate college memories.

However, my interest was growing as I was reading more and more interesting articles on these topics. One day I found out AWS was releasing a small course on Coursera about Machine Learning: Getting started with AWS Machine Learning.

I watched the videos, enjoyed the examples and passed the Quizz. I needed more material, my curiosity was growing and I wanted to practise, diving into the machine learning ocean and discover how interesting the fishing could be!

Some days later, I enrolled into the Standford ML course by Andrew Ng where I learned so much about theory but also some examples and practical use cases: everything to be able to be autonomous in my future learnings.

At that point, I started to think about going after the AWS Machine Learning Specialty exam. Following the same principle as for my Architect certification, I wanted to use the "exam goal" to explore even more about machine learning, the tools and the best practices used in the professional environment.

And here I am, a few months later, babbling about this exciting experience! I want to share part of this feeling with you, describing my own journey and hoping for you to enjoy it as much as I did!

What's on the menu?

Photo by Jessie McCall on Unsplash

The first thing to do when starting such a journey is to find a map. You wouldn't go to the Amazon forest without one, right?

In your case, you want to go to the Machine Learning Specialty page and check in particular the exam guide. This simple page will help you understand how the evaluation is performed and what are the needed skills.

Let's hear the master voice:

The exam validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for given business problems by using the AWS Cloud.

Now, the practical way! In November 2021, the assessed skills were spread like the following:

• 20% - Data Engineering

This domain includes everything related to data ingestion, transformation and storage. Data is your main asset in this journey, you want to treat it well and build a nice and genuine friendship!

Some services/topics you should explore: Glue, Kinesis, S3, Spark...

• 24% - Exploratory Data Analysis

Here we are talking about data preparation for modelling, feature engineering and data analysis (understand and visualize). This is the part where your AWS skills are not going to help you a lot and where you should develop your data-science and analytics knowledge. Improve your relation with data by adding some analytics friends and you should be good!

Explore some notions like: data cleansing methods, feature reduction, learn to choose visualizations...

• 36% - Modelling

This domain will check your abilities to transform a business problem into a machine learning one (or not if it is not needed!). You will need to learn how to choose the proper model, how to train it, how to optimize hyperparameters, and of course, how to evaluate the performance of your model. This is a very important part of the exam and it covers a broad range of topics. To carry on with our metaphor, this is the moment you ask your data some context, some help to be able to provide the best means of transport to the target destination...

You should definitely get some real-world experience (projects or use cases examples) to help you analyse the situations and take the right decision.

• 20% - Machine Learning Implementations and Operations

We know how to get and store the data, prepare and analyse it and choose the right method to use for the use case. Nice! But how will you actually build your solution in order to provide and optimize the business value?

This last domain is focused on choosing the right services to provide the right amount of performance, availability, scalability, resilience and fault tolerance. It includes also the strategies to deploy the model in production and a bunch of security best practices.

Time to have fun ! You did everything right until now, it's time to show that you know how to make use of all this work.

This is almost the end of the road: deploy the model to production, monitor it, adapt it, maintain it. Make it work!

Good program isn't it?!

Anyway, considering the large perimeter of the exam, remember that in order to pass, you will need to have a good knowledge and experience about machine learning but also about AWS services. On the other hand, don't be scared, the journey is at least as enjoyable as the congrats email when you pass and you will soon be able to navigate between all the AWS ML services.

For more practical information before we really start the journey, the exam is 180 minutes long and will cost you 300USD.

That said, let's see now how you can organize your learning.

Sagemaker my love 🥰

Before talking about my recent love story (is it a bit early for that?!), I would say that a good start for this certification is the AWS Machine Learning path.

Weither you are an beginner or the absolute expert, it will give you a large overview of the exam and will build the needed foundations to organize your learning depending on your strengths and weaknesses.

Now, let's come back to my (and probably your) future true love during this journey: Amazon Sagemaker!

A proud wizard once told me:

Read the Sagemaker documentation... a lot! ~ A proud wizard, once.

This should clearly become your main source of truth. Start by... the getting started! Navigate through the sections and take notes!

Learn all about the built-in algorithms and the way you can fine-tune them using hyperparameters. How to choose and set the objectives? Which data source can be plugged? What is the best way to deploy? How to secure Sagemaker notebooks...

The list of question to clarify is very large at the beginning but don't feel overwhelmed. Just start somewhere and the rest will follow.

Courses

Beside the official documentation, you will want to follow a specific course to guide you through the exam. Here are some I found interesting during my learning.

I used them as a starting point from which I could easily explore in detail the complex notions I didn't get at first sight.

• A Cloud Guru course
• Cloud Academy path
• Udemy course

Some videos to watch

AWS Power Hour Machine Learning serie

This is your call to get some more real-life use cases. As it can be hard to tackle every topic of the exam on your daily job or side projects, this is the way to get some experience from real projects (isn't transfer learning one of the topic to master?!). Here is a sample of what you'll be able to learn in the AWS Power Hour Machine Learning serie:

• Textract
• Comprehend
• CodeGuru
• Kendra
• Personalize
• ...

re:Invent sessions

This is true for one and every AWS certification but re:Invent sessions can be very informative to dive into some specific AWS tools and I particular Sagemaker capabilities.

Here are some sessions I found useful:

• Amazon SageMaker deep dive
• Introducing Amazon SageMaker Studio
• Amazon SageMaker for Fraud Detection
• Building, Training and Deploying Custom Algorithms Such as Fast.ai with Amazon SageMaker

Julien Simon's Book

I could not close this article without talking about the great book Learn Amazon SageMaker by Julien Simon. It guides you through the full Amazon Sagemaker process by providing some implementation examples and challenges. It covers every aspect of a professional machine learning project and elaborate about good practices and tips to help you navigate when moving your models to the next level, to the production environments.

Definitely a must read for this exam and for your next challenges in professional environments!

Finishing straight: readiness and the practise tests

Here you are, with all this courses and videos in your head. You did some hands-on labs and you learned about some real world use cases. But I know you don't feel so confident yet... And that's normal!

AWS exam readiness course will help you identify some of the remaining topics you need to deepen. It gives an overview of all topics for the exam without taking to much time... worth it!

Next step is for sure to check the available practise tests. They are even more important for this exam than for other certifications: you need to learn how to read, understand and tackle the questions. You will face long and complex question during more or less 3 hours, you better feel prepared and used to the format!

• AWS Sample Exam Questions
• AWS Practise exam
• Whizlabs tests (affiliate link)
• A Cloud Guru course final practise test
• Udemy practise test

There are really very few of quick questions you could find at the associate level. Most of the questions are in fact some real life use cases with 5 to 15 lines to read before even looking at the questions. This needs a little bit of training to stay focused and know what information to extract from the question.

To complete your learning material, I also found these resources useful:

• This Trello board by Kush Bhatnagar
• The activation function blog
• ACloud Guru Challenge: ML on AWS

Photo by Cameron Venti on Unsplash

The exam is a little marathon not a sprint

Now you are almost ready. Let's take some time to reflect on the exam itself and how to think about it to get the best chances.

Before the exam, try to get a good night sleep and relax as much as you can. The exam is going to last 3 hours and you don't want to feel overwhelmed right after the beginning!

During the exam, take the time to read question and create a virtual representation of the problem in your head. This is the key to make sure you understood the problem well enough to think about a solution.

A lot of questions will propose you several valid answers, you'll need to take note of all critical requirements (cost, simplicity, efficiency, liability, real-time...) to find the best answers. Don't panic if you feel like some questions are really hard to answer: sometimes AWS team include some slightly out of scope questions to explore future question ideas or to assess the common knowledge about some recently launched services. These questions won't be part of your rating but you will not know which ones they are.

Ok, I almost forgot the last task before the exam: you need to schedule the exam with Pearson Vue or PSI, on-site or from home, select your preferred language... This won't be the hardest part of the journey but don't be afraid to book your exam and set a deadline for your last learning sessions. You will never be ready if you listen to yourself!

Just go for it!

Conclusion

Is it already time to conclude? Hum... so what can we say?

This one is hard. Hard but not impossible!

I learned a lot in the process and I would definitely recommand to pursue this certification path if you are interested in machine learning. It will give you some practise and material to deepen your knowledge (even if you don't want to take the exam).

With a good dose of preparation, you will get the possibility to become officially part of the AWS ML family and to get opportunities in one of the most demanded field of at least the 5 next years! Isn't this interesting?

This exam is also really complete and will ask you to practice and learn about real uses cases. You are not protected from having some fun along the way, during your learning... As always, I hope I managed to share some of my feelings with you and that you are ready to start this awesome learning journey.

I wish you good luck!

Feel free to reach me on Twitter FlolightC to keep me updated about your AWS machine learning journey or to ask me questions ! I’m always happy to discuss with you!

The Challenge

Do you know about A Cloud Guru' challenges?

This time the "My Resume in Azure" one hit me in the middle of my afternoon. I was going for a break after two productive hours when I saw the Gwyneth Peña S. post.

I'll quickly have a look...

The goal is to publish a personal website, your online resume, based on Azure technologies and practice your Cloud skills in the process. You can see it as a hands-on lab where you need to do your research in order to make it happen.

I had very little experience building with Azure even if some theory was here somewhere in my head. This could be an opportunity to level up a bit.

Some time ago, I did part of the same challenge on the AWS side and despite being more confident, I still learnt about some topics.

So, no more thinking, I decided to go for it and try to learn a few things along the way!

This article won't be a detailed tutorial but it will give some guidance and remarks about the path I followed to complete the challenge, but also about some experiments to test and learn with some "side quests" along the way.

If you want to have a look at the result, here are the interesting links:

• GitHub repository

• Resume website

The first view of my Azure hosted resume

Prerequisites

• Free Azure account

  https://azure.microsoft.com/fr-fr/free/

• Free GitHub account

  I already had a GitHub account

• A domain from any DNS provider

  florianclanet.fr was ready!

• A text editor like Visual Studio Code

  Who do you think I am! But still... Here is the link because I don't know who you are 😄

• Azure Functions Visual Code extensions (if you use Visual Studio Code)

  Install it from the Visual Studio Code extension market

This list and a dose of motivation should guide you to the end of the challenge. If you are ready, let's start immediately!

The steps

Here is what Gwyneth suggested:

But here is what I decided to explore during the first step:

Then, when the job was done, I went back to the original idea and migrated my Azure Static Web App to some Blob storage + CDN + Azure function.

1. Create a GitHub repository for the project

This step is really easy. I just need to connect to my GitHub account and go to this url. I fill the name and choose my options (at least Readme) and click on "Create Repository".

From here I can clone the repository on my local machine and start developing (more on how to clone here).

2. Inside of the GitHub repo, create the website

Now that we have the repository cloned in local, I can start organizing the project. I split the folder into two subfolder:

• front --> for the html, js and css user interface static files
• backend --> for the Azure Function code to retrieve the user counter

At this point I spent some time searching for a nice theme and trying to fill it with my information.

Here is the link for the template if you need some inspiration (no affiliation here!).

When this step is completed, we have a pretty nice website that could be deployed and used "as-is". Let's talk a bit about the backend and how to add some dynamic information.

3. Add a visitors counter to the website

I choose to use CosmosDB (SQL mode), Azure Functions and Python (3.8) to code this part. So first step is of course setting up the database.

I created a CosmosDB account using the azure portal. I choose to use the serverless mode that allows you to pay "as you use" and is very useful when you are not going to use the database in heavy production workflows. Next I created a Cosmos container / database and added a record with "id" and "usersCounter" values.

Little digression here to highlight that you need to select Core SQL mode and not any other option like MongoDB for example. Only Core SQL supports binding configuration we will use later to interact from the Function to CosmosDB.

4. Deploying to Azure Static Web App

I know, Gwyneth clearly specified not to use it to understand fully what we are doing and to dive into some details. But I was curious to see how easy it would be...

And I wasn't disappointed!

It's really easy and with just some very simple steps, you have your resume online without even noticing you clicked on the Create button.

Azure Static Web App will deploy your frontend, your backend and will even create a GitHub action workflow for you.

If you want more details, here is the tutorial I followed.

Photo by Aziz Acharki on Unsplash

5. Migrate from Static Web App to Blob storage + Azure Function

When my resume was online and the code part was validated by the Static Web App deployment, I decided to continue the challenge by removing the Static Web App part and migrating the website to Azure Blob storage and Azure Functions solution.

Blob storage

I followed this Tutorial without any big issue. I stopped on the way to have a look at the different storage solutions and if you also want to take a look, here is a good starting point

I used some commands in order to have an overview of the az command-line and I think you should also go for it! It will save you a lot of time if you need to replicate what you did.

Here are some examples:

az storage blob service-properties update --account-name myresume --static-website --404-document error.html --index-document index.html
az storage blob upload-batch -s ./front -d '$web' --account-name myresume

I already had a domain name, I just configured a CNAME entry to point to my Azure static resource and asked Azure CDN to use HTTPS. If you are looking for some good resources here, you should follow this Tutorial and this one too. You will find a very useful way to avoid any downtime during DNS migration using cdnverify...

Azure Function

Azure Functions is supporting a lot of different runtimes such as C#, Javascript, Java, Python, Powershell... Find the complete list here.

On a first guess, I gave a try to the Python 3.9 runtime but as everything was not supported yet on Azure tooling, I came back to the 3.8 version.

To support the development as well as the first deployments, I installed the Visual Studio Code extension and the Core Tools. It makes it possible to test your Azure Functions on your local environment, helps you to create, manage and deploy your functions.

Here are the basic steps I followed to write my counter function:

• Configure a new HTTPTrigger

• Create CosmosDB account from portal or command line (serverless mode)

• Create a Cosmos container

• Create a document containing the counter property

• Add CORS policy for the static website to be able to call the Azure function

And one last thing, don't forgot to also upload your function parameters!

6. GitHub Actions

If you know me a bit, you can probably guess I quickly felt bad about the static and function manual deployments! If you don't know me yet, I'm telling you now: I enjoyed it for... something like 1,5 times!

As our project is already on GitHub, why not using GitHub Actions to automate this?

Our Action is probably going to access the Azure resources, we need to get and store a secret into GitHub Secret feature.

For the static website, we can for example retrieve the deployment credential with command line:

az ad sp create-for-rbac --name {myStaticSite} --role contributor --scopes /subscriptions/{subscription-id}/resourceGroups/{resource-group} --sdk-auth

Then we will create a new workflow under .github/workflows/.

Note: if you are using Azure Static Web Apps, the workflow file is already generated and ready to be used.

This workflow file will contain several sections:

• When to launch the Action (on push on main, on pull requests...)

• Where to run the script (Ubuntu...)

• What to run (action modules, custom commands...)

The goal is to automate everything that can be automated: build, tests, deployment...

On my side, I choose to automate the deployment of the static part and the build, test and the deployment of the Azure function whenever I'm pushing to the main branch.

This process is clearly sufficient for my use case but you could also add more branching customization, launch specific tests on pull requests... The automation and complexity are totally up to you and trust me, it feels great when it's working while you are going to grab a cup of coffee or tea!

At this point, you have a working static website, displaying the number of view thanks to the Azure Function requesting CosmosDB and you have a nice pipeline set up to be able to deploy without risk your brand new awesome website!

I think you can celebrate and prepare yourself to share with people what you learn through a blog article, a video or any other form of content you might enjoy creating!

Photo by Alasdair Elmes on Unsplash

Analysis

Here are just some final thoughts about this enjoyable journey.

The hardest part

Staying focus on the goal was definitely a hard part! I felt like I was willing to explore every rabbit hole I found along the way!

That's a classic feeling when you find yourself exploring new topics. My advice about this might be to stay focus as much as possible by writing down on a side paper/file every interesting topic you can find along the way that is not directly related to the initial goal of the learning session.

This way, you can come back later and learn about all these topics in an efficient way.

What I enjoyed

I liked a lot the idea to have a real project to work on while I was learning about Azure services. It clearly helped to stay focus and keep the motivation spinning!

Finding a free design to use was helping, I didn't spend too much time on any CSS or HTML structure and preferred to focus on the Cloud part itself but anyone interested to learn the end to end process will love the challenge. Working on your online resume exciting at all and is actually dealing with a lot of different topics.

My Biggest takeaway

Just start building!

I mean... What are you waiting for?

Cloud is great in the sense that you can start using it and learning about the several services and providers very quickly. And this is even true when you are building for a corporate client or a start up: go quickly to market strategy, fail fast, iterate often...

Those are not just marketing slogans but can also be experimented at your scale.

So, whatever the provider, the time or experience you have, you should start building right after reading this article!

Go to the challenge page, read the article, start your repository and share what happens next with the world using the #CloudGuruChallenge tag!

Feel free to reach me on Twitter (@FlolightC) to tell me about your resume on Azure journey or to ask me questions ! I’m always happy to discuss with you!

Copilot my friend

Everyone loves command line right?

Ok, at least if you regularly work with automation, pipelines, security... you do.

Everyone should love command lines!

It's the way to go to automate any strategic or boring task, removing the human factor from the equation and minimizing the error margin.

In this article, I will introduce you to AWS Copilot, and I'm sure you are going to become best friends in an instant!

Then we will prepare you to start the journey with a quick demo. Demos are like breakfast before hiking, right?

It prepares you just enough to be motivated enough to get started...

So, what are we waiting to prepare our hike?

Photo by Kelly Kiernan on Unsplash

What is Copilot?

You might (or might not) know about Amazon Elastic Compute Service (ECS), the AWS managed container orchestration system.

Thanks to Amazon ECS, running containerized application in a secure, observable and integrated way became really easy.

The idea of Amazon Copilot is to change the way you think about ECS. It's like going one step further...

No more manual management or lower-level infrastructure, with Copilot, you only think about your application.

We could say it's something like "ECS architecture design patterns and best practices" As A Service.

The only thing you need to do is to provide a container and Copilot will deploy and operate it following the ECS best practices to provide high availability, configuration and state of the art infrastructure.

Copilot can even handle the deployment pipeline for you.

How can you quickly start?

Prerequisites

• Install Copilot

Just install Copilot for your favourite OS from here

• Install Docker

Copilot will use docker to package the application.

You will find all the installation details here

• Configure your credentials

If you don't use it already, install the AWS CLI and configure your credentials using

aws configure

Deploy a demo app

AWS prepared something for you and me...

git clone https://github.com/aws-samples/amazon-ecs-cli-sample-app.git demo-app

This repository contains a ready-to-deploy application to quickly use copilot.

One more step and you will be done:

copilot init

Answer the questions: demo, Load Balanced Web Service, api, Dockerfile, 80.

You could also pass all those values as parameter but Copilot is kind enough to ask you if you forgot to give the information in the first time.

As Copilot is able to look inside your code (what a clever tool, isn't it?), it might be able to find the Dockerfile by itself (and port too).

Then choose to deploy a test environment.

When the deployment has completed, you will be able to check it.

Tips: You might use some commands from the "some helpful commands" section...

Here is what Copilot is doing underneath:

You know what's great news?

You don't even need to know how to manage any of the steps into this schema. Copilot is doing it for you, taking all the responsibilities.

Isn't this cool?

Clean up

In the mean time, maybe at some point you will want to clean up the environment:

copilot app delete

Super easy right?

Some helpful commands

To get familiar with the tool, try the following commands:

(You didn't think I was going to do all the work for you, right?)

copilot app ls   # list the applications managed by copilot
copilot app show   # describe environments and services
copilot env ls   # list the environments
copilot svc show   # describe service and will gather information to present it in one centralized place in the console
copilot svc ls   # list services
copilot svc logs   # show service logs
copilot svc status   # show service status

Documentation

Beside this little selection, feel free to launch copilot --help to get more details and copilot docs to access the online documentation in your browser (very useful to dive deeper into the details)

Tailor made deployments

Copilot offers you some really useful built-in patterns to help you manage your containerized application.

copilot svc deploy is performing deployment of updates to the ECS clusters.

copilot svc exec allows you to securely run commands into the containers tasks. This is especially useful for troubleshooting.

Infra-As-Code passionate or just curious?

AWS Copilot didn't forgot you: copilot svc package will show you the cloud formation used to deploy the infrastructure. You can then explore it and even use it outside of Copilot context.

This way, your are not bound to AWS Copilot, you just leave whenever you want.

Tips: The manifest.yml file (copilot/<your service or job name>/manifest.yml) is a copilot-generated file converted to Cloudformation format, describing the architecture of the service.

Pipeline my love

When I said Copilot CLI was helping implementing good practices and pattern, I also though about CI/CD...

You can indeed build a pipeline based on AWS CodePipeline, AWS CodeBuild AWS CodeDeploy and GitHub.

copilot pipeline init

This will initialize some files to prepare the pipeline deployment.

If you specify some arguments, Copilot will create two files:

• pipeline.yml: configuration options

• buildspec.yml: the steps to deploy through AWS CodePipeline

# Some arguments you can give to copilot pipeline init command
--github-url
 --github-access-token
 --git-branch
 --environments

Then you push these files to the repository and run the following:

copilot pipeline update

That's it! Your pipeline will be created into CodePipeline.

Tips: To add steps (testing) and get more details, have a look at the Copilot documentation

The latest cool features

AWS Copilot is still evolving quickly and the team just release some new features.

• HTTP to HTTPS automated redirection for Load Balanced Services with domain name

• Aurora Serverless support

• NAT Gateway support for private workloads

• Volume sharing between containers

More features are currently under development, check out the public roadmap here

Resources

• ECS workshop

• Container from the couch

• FR Deploying a Modern Application Stack to AWS Fargate with Amazon ECS - AWS Online Tech Talks

• Deploying containers with the AWS Copilot CLI

• Use AWS Copilot CLI to deploy containers on an existing infrastructure - Tutorial

• GitHub repository

• Documentation

Conclusion

Copilot will be your friend if you want to easily deploy your containerized application in a production-ready way.

Think about it again...

You are a few commands away from having an "Architecture patterns as a service" tool!

Be aware that Copilot is open source and that the repository can be found here. The team is sometimes releasing new versions several times per month and you are free to participate by opening issues or launching pull requests.

Feel free to reach me on Twitter (@FlolightC) to tell me about your AWS Copilot use case or to ask me questions ! I’m always happy to discuss with you!

Because everyone need to start somewhere, I'm going to take the AWS example. But some of the following content is also applicable for other providers.

The strategy

AWS have hundred of services available and they are able to release at least the same amount every year. Knowing everything is really impossible, and most of the time, not so useful either.

What you need, is

• A foundational knowledge about Cloud concepts

• An overview of the AWS landscape.

Then, the next step will be to deep dive into the topics that interest you and maybe specialize.

Cloud foundational knowledge

AWS as well as other Cloud providers provides a lot of learning resources to help you with your learning path.

Follow me through the pretty Cloud beginner pathway!

Cloud Practitioner Essentials can be a good start.

And preparing the associated certification is definitely a good idea.

Accreditations

You will also find on AWS training website, some accreditations that you can pass before your first certification.

They are a way to complete and check you understanding of several topics like main services, cost management...

100DaysOfCloud

I can assure you that you are not going to become a Cloud expert in 2 days!

But what you can do is "becoming better at Cloud" every day.

Imagine, if you learn about one new concept per day during 100 days... Yes, you will know 100 more concepts at the end!

This is exactly the concept of #1OODaysOfCloud Challenge.

Moreover, you can share your learning on social media (Twitter) or GitHub to both help other people and keep your motivation intact.

Cloud Resume Challenge

This challenge is going to give you all you need to start working as a Cloud dev.

You can find all the details here.

In two words, it was proposed by Forrest Brazeal and the goal is to build an online resume, based on Cloud technologies and good practices.

The challenge is an end to end project that help you to become familiar with the main concepts of Cloud development.

AWS Well architected framework

When you become more confident with the fundamentals, you can start having a look at the good architectural patterns. You can:

• Read articles like this one

• Read the documentation here

• Follow the labs to gain experience here

Other certifications

You will probably find the certification path very useful to guide you through the learning material and topics. When your first certification will be celebrated, you will probably start to think about the next one...

Here, it depends on your goals and affinities but your main options are the following:

• You want an overview of the services and explore how to build architecture solutions with AWS

• You want to develop applications, to discover serverless concepts and to make the best out of the cloud development tools

• You want to dive into deploying, managing and operating solutions in AWS

• You want to specialize in a specific topic like Security, Network, Machine Learning...

On going project

Just before letting you go to your first learning step, I wanted to tell you about my on-going project to help newcomers get into Cloud.

It is a story, written for Cloud newcomers in you will be able to follow Cassandra and Sam through their learning path and discover a new and innovative way to learn Cloud concepts by reading a fiction.

Follow the path at your own pace and check the boxes until your first certification and probably more.

As you have understood, this book will be the perfect support to help you start your learning journey!

If you want to follow my work on this and be updated about the progress, feel free to check out this page:

pleasedrawmesomeclouds.flolight.dev

Conclusion

I hope these few lines gave you a clue about how to start learning about Cloud.

I have no doubt you are at the start of something big!

Keep your curiosity awake.

Be consistent during your learning.

Trust yourself.

You will be fine!

Don’t forget to react and to share this article if you liked it! Feel free to reach me on Twitter (@FlolightC) to tell me about your Cloud journey or to ask me questions! I’m always happy to discuss with you !

Kinesis Data Stream

🛠 Workflow:

• Producer (Kinesis Producer Library, API via SDK)
• Kinesis Data Stream
• Consumer (EC2, Lambda, EMR, Kinesis Data Analytics)
• Storage/Analysation (S3, DynamoDB, Redshift, BI Tools…)

💡 Benefits

• Data retention
• Real-time

🧪 Use cases

• Analyze logs in real-time
• Transform real-time streaming data and fed it to a custom ML application

Kinesis Data Firehose

🛠 Workflow

• Producer
• Kinesis Data Firehose
• Processing tool (optional: Lambda)
• Storage (S3, Redshift…)
• Additional steps (send on event from S3 to DynamoDB table)

💡 Benefits

• Collect streaming data and send to data store

🧪 Use cases

• Delivery service for streaming data
• Apache logs from EC2 instance to S3 or Redshift
• Streaming data from IoT devices to data lake

Kinesis Video Stream

🛠 Workflow

• Producer
• Kinesis Video Stream
• Consumer (EC2 continuous/Batch consumer program)
• Storage (S3…) or other service

💡 Benefits

• Real-time streaming of video data (images, audio, radar…)
• Batch process and store streaming video data
• Feed video data to other AWS services

🧪 Use cases

• Stream event video coverage to customers
• Ingest data for ML applications

Kinesis Data Analytics

🛠 Workflow

• Input (Kinesis Data Stream, Kinesis Data Firehose)
• Kinesis Data Analytics
• Storage (S3, Redshift…) / Visual tools (Quicksight, ELK…)

💡 Benefits

• Run SQL queries on streaming data and output to S3
• Create dashboards
• Metrics
• Alarms

🧪 Use cases

• Query real-time data
• Enrich data for ETL jobs
• Responsive real-time analytics
• Metric graphs

Conclusion

AWS Kinesis services can be confusing at the beginning but I hope this cheat sheet is going to help you understand and memorize to make the best out of these services.

Don’t forget to react and to share this article if you liked it! Feel free to reach me on Twitter (@FlolightC) to tell me about your Kinesis use case or to ask me questions ! I’m always happy to discuss with you !

And here is another announce from AWS re:Invent 2020 ! Join me to get a tour…

This time, I admit, it is not so innovative.

But not being the most amazing innovation of the century is not really an issue if the need is here.

Moreover, if people all around the Clouds would wait for a fundamental useful feature, this feature would surely be AWS CloudShell !

Let’s get to know better this little guy…

A Shell in the Cloud

The tool is browser based. Just open the AWS console and check it at the top, next to the notification bell.

Here are some of the characteristics:

• You are able to use Bash, PowerShell and Zsh.
• A lot of standard tools are available (and up-to-date) such as AWS CLI and common CLIs (ECS, SAM…), Python and Node.js SDK, npm, pip, Git and even your favourite editor: vi.
• Under the hood, CloudShell run on a Amazon Linux 2 virtual machine. One VM (which is the limit per region) can support up to 10 concurrent sessions.
• You can control the access using IAM policies
• There is no need to manage your credentials. People working with several accounts will understand how nice it will be.
• It is free to use but you will still by charged for both the resources created by your commands and the data transfer.

Storage

CloudShell provides 1GB storage embedded into your home directory.

You can use it to store your favourite scripts or your configuration files.

Be careful, this stored data is only kept during 120 days (of inactivity).

If you have further storage needs, you should consider to use an S3 bucket instead.

My opinion before to test it

I didn’t test it as I wanted to share first some impulsive thoughts about this new “service” (can we really call it service considering that it is more an AWS console feature? Who am I to decide!).

From my point of view, this will be very useful to run quick scripts without having to configure a complete environment on the local machine. Considering you are using the embedded tools, no configuration will be needed.

For instance, you could start experimenting and running some commands on any device. Even if you have no administrator or installation rights.

Quick tests will be possible and it is completely aligned with the need to try and fail quickly.

From another point of you, let’s wait and see if this feature can help people to adopt a scripting habit. It could be for some, the first step into the *-As-Code concepts at no cost and with a fast learning curve.

Conclusion

This new tool fills the gap between Cloud9 terminal and EC2 Instance Connect by removing the need to have a customer managed EC2 instance to be able to use an AWS integrated and fully ready command line environment.

I look forward to testing it in a near future and see the potential by myself ! Stay tuned…

Don’t forget to react and to share this article if you liked it! Feel free to reach me on Twitter (@FlolightC) to tell me about your CloudShell use case or to ask me questions ! I’m always happy to discuss with you !

AWS recently announced a new service: AWS Proton.

As I love to have a look at the new features provided by the AWS re:Invent, I wrote this article summarizing my findings.

AWS Proton is a tool to help with infrastructure automation and code deployments.

But it is not another CodePipeline because the tool is more designed for organizational purposes.

This service makes it easy for infrastructure teams to centralize and standardize classic infrastructure patterns so that they can be available for developers to deploy their code.

And this why it should be seen as an organizational tool.

It support the technical design of your organization by providing a way to explicitly expose it to all teams building applications and products on top of this layer.

If you know AWS CI/CD environments, you will be happy to hear that Proton is for instance integrated with Code Pipeline and Cloudwatch.

Let’s see how we can quickly use AWS Proton to set up a lambda serverless environment.

Connect to Github

• Let’s go to the Proton page
• On the menu on the right, we click on Source connection and create a GitHub connection.

Set up for Proton

Here we will just create (or select) a role for Proton to use to deploy Cloudformation stacks.

• We go back to the AWS Proton page and click on Account roles

• Let’s create/update the role we will use to enable resource creation by Proton

Create proton environment template

• Let’s navigate to AWS Proton page and click on “Get started”

• We click on create environment template

• Here, we can choose to provide our own template but for this example, we will use the AWS lambda one.

• Let’s fill all the information and hit create

That’s it, our environment template is created.

Create and deploy an environment

Now, let’s create an environment from our environment template.

• On AWS Proton page, we are going to click on “Environments” and “Create environment”
• We choose our previously created environment template

• Let’s fill the information as we want and provide the role we created at the beginning of the process

• Let’s fill the settings configured in the template

• We hit the “Create” button and wait for the creation to complete

We will see a new CloudFormation stack provisioning a DynamoDB table.

Create a service template

Let’s do the same process for the service part

• Let’s go to Proton page and click “Service templates” and “Create service template”

• As for the environment, we will use the sample lambda template

• Let’s fill the information and choose the environment template we created in the previous steps

• And we click “Create”

Here we are with our service template

Create the service

Now we are going to create a service and its service instance from the service template.

• On the AWS Proton page, we click on “Services” and “Create service”
• We choose our template

• And fill the information with the branch name and the GitHub repository

You can find some code sample in this repository.

When the deployment is completed, we are able to reach our service using the provided url.

We can use this newly created Proton structure for our future deployments.

Conclusion

We were able in a few minutes to set up an entire Proton process. And we have just touched how powerful it can be on a scaling and governance perspective.

Here are some AWS Proton major benefits:

• Developers can deploy safely their applications without having to manage the deployment infrastructure and CI/CD
• It works with containers and serverless stacks
• Proton provides consistent architecture across projects
• Easy infrastructure-as-code organization by design
• No additional charges, you pay only the resources created by your templates

This article was just an introduction on the topic. I encourage you to experiment the tool and create your own templates to match your business use cases.

For an enlightened point of view of AWS Proton, I recommand the excellent article of Forrest Brazeal for A Cloud Guru:

AWS is providing us with a new kind of tool that can help organizations on their daily struggle about quick response applications, innovation and process optimization. AWS Proton is still in its baby phase and will certainly be improved but this intriguing tool is already able to change the way we think about environment and pipeline management.

Feel free to reach me on Twitter (@FlolightC) to tell me about your Proton use case or to ask me questions ! I’m always happy to discuss with you !

No big introduction today because it is not needed!

You probably know that Amazon Web Services provides a lot of services.

Let me present you five you probably don’t know a lot about.

Snowmobile

Did you ever heard of the “Snow” family? Let me introduce you to one of John’s brothers…

What?

Snowmobile is one of the data-transfer solutions provided by AWS.

When transferring data from your data-center to AWS, you can chose to use the internet, or the AWS backbone network. This is fine for small datasets and even medium ones. But what if you need to upload a very large amount of data in a small time window? This network solutions won’t be enough.

That’s when you are going to check Snowmobile!

The goal is to provide data-transfer service for very large amount of data. We are talking about up to 100PB!

It consists of a physical container pulled by a semi-trailer truck who will come to the company to help you transfer data more quickly than through the network. The truck will then go back to AWS and the data is put in S3 to be available.

Snowmobile should be used for datasets larger than 10PB. If you have less than that and still struggle to use the network, you can have a look to AWS Snowball.

How?

• Request the service using AWS specific form
• You are contacted by AWS team to schedule the transfer, discuss logistics…
• The truck go to your company
• AWS team connect the Snowmobile to your infrastructure
• Transfer data to the Snowmobile
• The container is drove back to your AWS region
• Data is loaded into S3 or Glacier
• AWS team check with you if everything is fine

Cost

The cost will be around $0.005/GB/month but you will probably discuss these considerations with the AWS teams before ordering. A specific form is available to request Snowmobile, Snowball and Swowball Edge.

Outposts

Did you heard about Hybrid Cloud?

What?

Outposts is the way to integrate AWS Services into your data-center.

This is your best choice if you need low latency or local data treatment.

You can control where your compute and storage is living, while benefiting from the main AWS Services (compute, database, storage…).

How?

• Order your storage and compute capacity
• AWS team is coming to your site to connect your Outposts hardware to power, AWS network and your infrastructure
• Launch your resources on Outposts
• Start using your services and building applications

Cost

Pricing is based on the configuration you order. You will have an initial cost and then an additional cost based on the configuration you choose.

Details can be found here.

Ground Station

This is my favourite!

I’m pretty sure you didn’t know that AWS have a service about satellites. Crazy, right?

What?

With Ground Station, you can use data coming from satellites without needing to have your own infrastructure. The service provides you with antennas, modems, everything you need to connect other AWS Services or your own data-center to your satellite data.

An EC2 instance from a specific AMI is connecting to the antenna over an ENI connection.

Ground stations are fully managed and are inter-connected using the low latency AWS network backbone. To use the service, you reserve antenna time to connect tot the satellite.

How?

• Register your satellite(s)
• Schedule a satellite contact based your satellite(s) contact windows
• Use Ground Station to control, download data and send command to your satellite(s)
• Use other AWS services to process and distribute the received data

Cost

AWS bill you by the minute on the actual time you use the antenna.

Cloud Map

What?

Cloud Map is a mapping service to help with naming in the Cloud.

It is particularly useful with micro-service architectures. All the components can be by definition dynamics.

Cloud Map acts as the glue between your components, it is a registry keeping track of the latest versions of the architecture components. It works like a facade to other components and can provide health-check support.

When your application use Cloud Map, it will always try to get the latest resources. It is a strategy to increase the high availability of your service.

Even if your resources change dynamically, Cloud Map will keep the link up-to-date.

You can declare different resource types into Cloud Map: databases, micro-services, queues, lambdas, ECS clusters…

Health check capabilities

How?

• Create a namespace
• Create services
• Register service-instances
• Use API calls in the application to discover service instances

Feel free to check this article and this AWS blog post

Cost

The service is billed 1$ per million requests and 0.10$ per DNS registered resource. Check details here.

Amazon Lumberyard

Video game creators, this one is for you !

What?

Amazon Lumberyard is a free AAA game engine. The service is fully integrated with the AWS and Twitch environments.

You can integrate AWS services in your game: leader-boards using DynamoDB, Server side combat resolution…

You can develop for several platforms: PC, Xbox One, Playstation 4, iOs, Android… MacOS is not supported at the moment but is on the roadmap.

Another interesting point: you can have a look to the C++ project on Github.

How?

• Download the engine
• Configure it to build your game
• Develop your game
• Publish it

AWS provides a free course to start using Lumberyard, check it here.

Cost

Amazon Lumberyard is free to use, without any paid license. You only pay for other AWS services you choose to integrate to your game.

Conclusion

AWS has so many services that we can regularly find new ones to dig into. We can always have some nice surprises and that was the goal of this article !

Keep learning and let your journey be astonishing !

Feel free to react to this article here and to reach me on Twitter (@FlolightC) to tell me about the incredible AWS service you discovered yesterday or to ask me questions ! I’m always happy to discuss with you !

Photo by Cathryn Lavery on Unsplash

Did you want, at some point in your life, to start writing articles?

I felt like this a few times already. Having some thoughts to write down in order to keep them alive, to expand them and to share the result with people…

There is no secret here, that’s the main reason I started blogging a few month ago. At the beginning, I didn’t really have any idea of what I was willing to achieve. The secret ingredient happens when step by step, I sharpened my vision and progressed in the understanding of what type of content I wanted to share. I am still on this improvement journey and I hope it will never end.

I decided to write this article after listening to Dr. Michaela Greiler talk (“How to successfully blog as a dev and grow your audience”) during one of the Hashnode writing Boot-camps. She talked about how important it is to know what your goals are, to be able to enjoy blogging on the long term.

Indeed, how to be successful at writing blog posts depends entirely on the reasons your are into blogging. Define your own goals depending on why you want to blog and focus on them seems like the right thing to do.

I did a little introspection and here is what I found out about my blogging drivers.

You can take the opportunity to do the exercise and compare with the following thoughts. You might see that everyone have different motivations.

Why I want to blog?

Learning journal / Build credibility

It started as a way to keep track of the topics I was learning. I noticed it is easy to learn something at some point because I need it on the moment but it is at least as easy to forget it some weeks later. Blogging made me think deeper about what I learn on the way. Did I understood this method entirely? Am I aware of the Pros/Cons of the solution I choose?

At the same time, I want the articles I write to help me build credibility on my favourite topics. It is always useful to be able to showcase my skills by showing some content I created.

Having a blog post about this little proof of concept I build on my free time “just to see” is a way to support my arguments when trying to find a job or step up in my current one.

Improve my writing and communication skills

I always loved to write. When I was younger, I used to write stories (in French) or news articles about things I cared about.

Today, working in technology industry, I need to write in English, and I love that because it helps me to improve my writing skills in this language.

Indeed, it is very easy to lose my English level when the only things I read and write are colleague e-mails or technical papers and documentation!

Writing is another way to express thoughts.

It helps me organize the ideas I have on my mind and the process to define my reasoning. It’s always nice to be able to present clearly some ideas to your team. Communication will be more fluent.

Share and connect with people

Blogging gives me the opportunity to share my analysis on problems as well as my thoughts. I’ve learned so many things from blog articles in the past decade that I want now to do my part in helping others.

Sharing gives me a pleasant feeling. Something like participating to make the day of other people a bit better. I sometimes even imagine some imaginary readers when I build my articles to be sure to “talk to someone”.

I had the occasion to connect with very interesting persons here. I enjoy the discussions my articles can create. This is part of the writing process and one of the reason I enjoy it so much.

Receiving advice and remarks from readers is an other alternative to improve my knowledge, to grow and diversify my point of views.

Photo by Joshua Earle on Unsplash

My vision

This is a very important thing to have to achieve goals. I am trying to figure this out one step at a time but I feel more comfortable today with the following balance:

• A Clear vision
• A Small part of unknown

What I call my little part of unknown is own by the liberty I give myself to explore new opportunities. I don’t want to miss an interesting topic because I have my head down in my objectives.

Curiosity is part of my personality and I don’t want to lose it !

For now, I am still working on the clear vision part on a short/medium term. It corresponds to the steps I want to achieve to be a little bit closer to my goals. I will share this in a future article, stay tuned…

Conclusion

I hope this article gave you an idea about some of the reason I wanted to blog.

Those goals are not written in the stone. I should review them once in a while to see if I am still aligned with them or if my interests maybe drifted a little. And so should you!

I think this exercise is an satisfying way to take a little breath from the current situation. It helps getting a clear view of the drivers, goals and motivation sources in the writing journey.

This clear vision is a nice thing to have. It is definitly something to reflect in your writing style and on the way you deal with topics and activities around your blog.

Blogging means to invest some time in writing. Make sure you do it for the right reasons and you will never regret it!

Feel free to reach me on Twitter (FlolightC) to tell me about your secrets reasons to start blogging or to ask me questions ! I’m always happy to discuss with you !

Photo by Annie Spratt on Unsplash

Do you want to learn what Cloud is ?

Or maybe you already have an idea but you would like to get better and be able to showcase your knowledge.

Microsoft AZ-900 Azure Fundamentals certification path is a perfect start.

After exploring a lot AWS Services, I felt the need to have a better understanding of other Cloud providers. This certification is interesting to have a first overview of the Microsoft Azure services. You will learn the basic Cloud principles as well as how you can find them in Azure.

In this article, I will help you understand how to pass the AZ-900 certification and some of the benefits to do so. I will talk about the new version released in November 2020.

Ready to dive into Azure stuff ? Follow me !

What is AZ-900 ?

The AZ-900 certification is the first level certification issued by Microsoft about its Azure cloud services.

If you have a look at the Microsoft Azure certification path compiled by Wizlabs (2020), you can see that AZ-900 is at the beginning of each road.

Microsoft Azure certification path by Whizlabs (2020)

The goal of this certification is to give you foundational knowledge of Cloud concepts and how Azure is implementing them into several services.

You don’t need any Cloud background to start learning and pass the exam. However a previous IT experience will make it easier and faster to achieve.

The skills

Here are the skills you need to learn about to pass the exam. I won’t just copy paste every requirement but I will give you an idea of what’s inside. You can find the details of every skill on the AZ-900 exam page.

Cloud concepts (20–25%)

Here we are talking about Cloud general concepts. You will learn about the benefits (CapEx vs OpEx…), the “y” drivers (High Availability, Elasticity, Scalability…). There is also some content about the different service levels (IaaS, PaaS, SaaS).

Be sure to well understand this section as it will be useful for every other certification you will take as well as for real-life situations.

Core Azure Services (15-20%)

In this section you should know the main Azure services. Like the one you will use every day as Azure technical people. You will discover the resources you can use as well as the patterns to manage them using Azure core architectural components (Regions, Availability Zones, Subscriptions, Management groups…).

This is about the shell of your future Azure architectures.

Solution and management tools in Azure (10–15%)

DevOps, monitoring, IoT, Data analytics, portal and shell…

If you think that they are very different topics, you are probably right !

This section is about the presentation of solutions to real-life problems, available through Azure services and how to manage them. I’m sure you will find here some tools that you are looking forward to use on your next Azure project.

General security and network security features (10–15%)

Because you know it (and if not, you NEED to learn it) security is of paramount importance in IT. And especially when you are using public cloud platforms.

You will find in this topic some details about how you can prevent security breaches using Azure network security features. Moreover, take time to have a deep look into the several compliance, alerting and prevention services (Sentinel, Security Center, KeyVault…).

Enjoy the cloud but stay safe !

Identity, governance, privacy, and compliance features (20–25%)

We keep the point about security, talking about identity and access management in Azure.

Identity federation with Active Directory, Multi-factor Authentication, Role-Based Access control policies… Everything to keep your Azure account and resources safe and secured.

You will also see how to manage resources using tags and package your environment resources to deploy them at scale using Azure Blueprint.

This section is also here to make your life easier when you will start to safely onboard your team on the platform.

Cost management and Service Level Agreements in Azure (10–15%)

Last but not least, there is a fairly consequent part of your learning about Costs, SLAs and services life-cycles.

The capacity to better optimize costs is one of the main assets of Cloud platforms, you need to learn how to do it ! And I’m sure you can’t wait to know how to comply with your business availability requirements or to try the next Azure features as soon as they are usable !

Face to face with the exam

You know what you need to learn, now let’s have a look at the exam details.

You have 60 min to answer between 40 and 60 questions.

Your time is global for the exam, you are free to divide it at your convenience between questions.

Be sure to plan at least 90 min to do the check-in process and read the instructions. You don’t want to miss anything. Right ?

All questions have checkbox style answers (nothing to write) and you will find different kind of questions:

• Multiple choice: 1 or more possible answers (the number is specified in the question ==> please, READ CAREFULLY THE QUESTIONS)
• Graphical answers: You will have for example a screenshot of Azure portal and you will need to select the correct service to click on for a particular situation
• Drag & Drop: You will need to match some Services or Concepts to the right definition

During the exam, you can flag questions to be able to quickly come back to it at the end if you need to spend more time on it.

This exam description is not the full requirement list. During the learning process, you should check the details on Microsoft website.

Schedule your exam

When you feel ready you can go to the exam page and plan it using the PearsonVue link.

The exam is 99$ but Microsoft run from time to time free virtual learning sessions with a free voucher at the end.

You can chose to take the exam from home or go to an exam centre.

You will have more informations about requirements for the exam during the scheduling process (identity papers, clean workspace…). Be sure to read everything and to check that you will be able to provide the necessary level of workspace confidence and peacefulness if you are doing this from home.

How to prepare the exam

Learning path

The main resource for this exam is the Microsoft Learn platform. It provides modules for free that you can complete at your own pace. This is a full text journey.

There are also some free labs included that you can complete using sandbox. You need to create a free Azure account to have access to the Azure portal and services.

Microsoft Learn path for AZ-900

Beside that, there are a lot of courses over the internet. Free, not free, video, text… If you need more than Microsoft Learn, just choose one and deal with it.

Last step will be to find some question examples. Check free platforms like examtopics but be careful: they might not be up-to-date and you can have some wrong answers in the correction.

For more serious content, you can have a free exam session on Whizlabs and some other for a few $.

Photo by Gabrielle Henderson on Unsplash

My advice

As a first step, try to have an overview of all concept and services included in the certification.

Then, when your ideas are a little bit more clear about Azure ecosystem, try to understand how services help to fulfil Cloud concepts (fault tolerance, elasticity, high availability…) and how they can interact with each other.

Think about real life use cases. Try to find how you could solve your team issues using Azure services. Or maybe how you would implement a certain architecture into Azure.

It does not have to be very complex example, but being able to refer to real-life helps you to memorize.

On your way, be sure to have a quick look at every concept you don’t understand very well at first sight. If you need, you can build yourself a Wishlist to keep track of the topic you need to check later. I wrote another article about how to use this concept. It is particularly efficient if your are new to the certification and cloud field.

I strongly recommand you to create a free account on the Azure portal. You will be able for free to explore the several services as well as completing the labs offered by the Microsoft Learn path (sandbox).

Spend some time on the Azure portal, especially if you are new to the Cloud field. You will get a better understanding of all the possibilities and you will have the whole picture in mind.

Last but not least, do not hesitate to ask people question. There is a great community of Cloud enthusiasts on forum and social media that can help you. You will solve your issues and meet with interesting people, you will see real-life experience and projects. In seven words:

You will build a strong background knowledge.

Conclusion

This AZ-900 certification is very useful, especially if you are new to the Cloud concepts. If you are already familiar with other Cloud provider, it is the occasion to quickly have an overview of Azure platform.

With some motivation, anyone is able to pass the exam and you will learn a lot in the way. It is very important to understand what you learn. Do not study just for the exam. Keep in mind that the goal is to setup the foundations for your future knowledge.

I hope you are ready to start learning and I wish you good luck on your journey !

Feel free to reach me on Twitter (FlolightC) to keep me updated about your Cloud journey or to ask me questions ! I’m always happy to discuss with you !

Photo by Mika Baumeister on Unsplash

When you have a new idea, you don’t want to lose it !

And when this idea is a web or mobile application, you probably don’t want to spend two weeks trying to build it. And then find out that it’s not really what you want.

I search a lot and here is a good solution that would have helped my past self saving a few hours.

I was in this situation a few days ago and I tried to find out what tools I could use to have a basic prototype. I wanted to make a support to be able to show and discuss my idea with other people.

My goal here was to find a free and easy tool. I was not ready to spend some time learning a complete new process.

I just wanted to get it done !

I looked for this tool on my favourite search engine. After reading some articles, I quickly find out that I could use Keynote or Powerpoint.

Indeed, I know those tools and I use them regularly to expose my ideas. This is the case for a lot of people and even if you are not a Keynote master, don’t run, the learning curve is friendly.

So why not giving it a try?

Keynote / Powerpoint

This is probably the more obvious solution but you still need to think about it. It is usually used to prepare presentations or to support courses.

But, isn’t a new application kind of a presentation ?

Yes it is !

Configure the environment

I grabbed a glass of water, breathed a little and tried to bring with me the whole world motivation to open Keynote (Spoiler: I regret nothing !).

After this little setup time, I configured my page to have a nice ratio for my target and I was ready to add some elements.

Just before that, however, I though it would be nice to have a phone template on my slides. It can help you to add some context but it is not mandatory. I went to Mokuphone to get my template phone and used the Instant Alpha feature to remove the background.

this is an Iphone template but you can chose Android too

Then you can bring some icons for your navigation menu and arrange them on you layout. To find some resources here you can check websites like Flaticon, Hero Icons…

Be sure to do this step add the beginning, on your first “template” slide to be able to duplicate it for next screens.

Quickly create a menu using forms and icons

This is one of the limitations I saw in this method. If in the middle of the process you decide to change the menu, you will need to adjust all other slides. And I won’t scream about it as this is why there are good professional tools dedicated to UI/UX design on the market.

Design it !

From here you can duplicate your template and start building your pages/screens. Keep it simple and attractive !

Choose your colour pallet for the application. You can use some online tools to help you: Coolors.co, Adobe colour wheel.

Use Figures to create your layouts and buttons. Play with the border to differentiate components. Keynote will also help you with alignments which is super-useful to have a nice looking design.

Use links to design your workflow

Maybe at some point, you will need to add some interaction to showcase your application workflow. You can do this using the link feature.

Right click on the element and you will be able to link it to another slide or url. This is very useful to model your navigation.

Collaborate

Keynote (and Powerpoint) has a sharing functionality to work together with your mates on your project. I didn’t try it as it was a personal project at this time but think about it if your need to share the workload in your team.

Versioning

One Keynote very nice feature is the versioning. In just two clicks, you will be able to revert back your work to a previously saved version.

No more “last-last-last-true-final-mydoc-1.678” file name on your laptop !

Each time you save your document, Keynote create a new version. You can have a look at the other version in the File > Revert To menu.

Conclusion

That’s it, I was able to build my fake application in less than two days ! And I played a lot with design and other “not-so-useful-at-this-moment” features !

Whatever your tool, always think about what you want to achieve. Try to make it as close as possible from what you have in mind. You have to feel home in your prototype. Try some things, remove some others, rebuild what does not fit your vision.

Keynote was very quick to use but I was stating to see some limit near the end. I might consider other tools like Figma next time.

Remember that this step is key to transcribe what you have in mind. At the same time, you don’t need yet to spent too much time to make it perfect. Make it face your audience instead !

I hope this article was useful for you. Don't hesitate to give me your feedback on these tools or to suggest me other ones.

You can share this on the comment section bellow or contact me directly on my Twitter !

I recently had to configure all my tools after a fresh Windows re-installation. This went well and quick as I keep up to date a list of my favourites tools. This way, I just need to go through my list and I know I have most of the things I will need to work. Next step would be to automate those installation but it will be for another article !

I though it was the occasion to make a list of the most useful ones.

So here it is !

Browsers

Those two are the main one I use for my everyday web browsing and basic testing. Of course, when needed, I switch to other ones like Safari, Edge...

• Chrome
• Firefox

Utilities

• Screenpresso

Perfect to capture your screen (image and video) and edit the screenshot to add information on it.

• 7-Zip

I think it won't be convenient to introduce 7-Zip any more... But for every compression job, he'll be there !

• f.lux

A nice tool to manage the light coming from your screen. It will adapt it to the time of day and the kind of light you should have on your room.

• KeePass or Dashlane

Please don't tell me you keep your passwords and secrets on a piece of paper somewhere near your desk... Use a password manager like KeePass (local) or Dashlane (synchronized)

• LdapAdmin

I use this to have a look at LDAP directories, search for entries. Very useful if you manage some running corporate applications and you sometimes want to check groups and accounts to help people around you.

• TreeSize

I think I'm on the best team when it comes to store all kind of "for later" files. This application helps me finding what is taking space on my disk and manage it.

Communication

Nothing big to say here, we all need to communicate with colleagues and other people. My big regret is to have like 4 or 5 application for that depending on who my interlocutor is !

• MS Teams / Amazon Chime / G Suite...

Coding related

• Git

Of course ! What would we do without it ?

• GitKraken

For me the best visual tool to work with Git. It can save a lot of time when you are stressed or trying to solve some git weird issues.

• Python

Always have a Python install on your computer ! Think about the number of little things you could automate in your daily life ! If you are interested to know more, check this nice resource: Automate the boring stuff

• Insomnia / Postman

If you are building APIs, those two tools should be on your disk ! Insomnia is light and very quick to use whereas Postman is a little bit more complex but allows you to create collections, share them with your team, document it, and a lot of other features

Database access

Here it depends on your database system preference but let's admit that it is always useful to have some of those already installed on your machine !

• pgAdmin / DBeaver
• MS SQL Management Studio

Edition

• Visual Studio

• Visual Studio Code

I always switch between VS and VSCode depending on the work I do. I mainly use VS for back-end and VSCode for front but it more a habit than anything else !

• Notepad++

While VS and VSC are great tools, I feel very comfortable writing quick notes with notepad++. It is like my virtual notebook.

• yEd / Visio

Sofwares I open when I don't use online editors like Diagrams

• Zeplin

Used by my team for every design related stuff.

Terminal / transfers

• MobaXterm
• PuTTY

I use those to open remote connections when I'm not using simple RDP or ssh solutions. They are useful to store configurations and organize your assets.

• cmder

This is a simple command line with useful linux-like commands. But you could also use Windows integrated Bash shell or just Power-Shell if you feel more comfortable with it.

• FileZilla

Use the client part to connect to ftp/sftp servers to transfer and retrieve files. You can save your servers configurations and share them with your team.

Conclusion

This is the list of the main tools I use in my everyday work. If I have some free time, I often start by installing them all so I'll be ready when I need them.

Anyway, use the tools that suit you ! Save your configurations somewhere a make a list like this so you don't spend too much time when your next Windows installation will come !

I hope this article was useful for you. Don't hesitate to give me your feedback on these tools or to suggest me other ones.

You can share this on the comment section bellow or contact me directly on my Twitter !

Photo by Riley Crawford on Unsplash

One way to host a simple static website is to use AWS S3 to keep your files.

Yes, put your index.html and style files into an S3 bucket named . and you will be ready to publish your content.

Then you could link your own domain using Route 53, add a CloudFront distribution, HTTPS support…

But what about deployment ?

I can assure you that you don’t want to spend any time copy-pasting your pages to the S3 bucket. You have better things to do !

Here is my simple way to automate this. If you are new to the topic, this is a 30 minutes configuration, reading this article included !

So, no more talk and let’s build our pipeline !

To implements the following solution, you will need:

• A GitHub account
• An AWS account

Here is the idea:

1. Create a GitHub repository for your website — 10min

2. Configure an AWS IAM user — 5min

3. Configure a GitHub Action — 5min

4. Make a change and Deploy — 5min

5. Celebrate — 5min (at least !)

1. Create a GitHub repository

If you already have your repository configured, you can go to Part 2 !

Here, you want to put your code into a repository that will be used to track the changes and trigger the deployment.

1. Go to GitHub and connect to your account 2. Create a new repository

3. Feel free to fill the parameters to have the repository you want

4. Clone the newly created repository to your local laptop using Git command line or your favourite UI tool for Git (mine is GitKraken).

git clone https://github.com/YOUR-USERNAME/YOUR-REPOSITORY

You will find the url to use in your repository, clicking on the “Code” button

For more information on the git clone have a look a the GitHub documentation.

5. Put your files on the created folder and push it

git push

An example of a simple site repository:

Now, if you go to https://github.com/<username>/<repositoryname>, you will see your code waiting for you on the main branch !

Fine, let’s have a bit of AWS now !

2. Create an AWS IAM user

Your goal is to push some files to your S3 bucket. For this purpose, you will need to have rights on the S3 bucket.

You will use an IAM user with S3 policy.

1. Open the AWS console 2. Go to the IAM page

3. Click on “Users” in the menu and Add a new user

4. Pick a name and choose the programmatic access

5. You are going to use an existing policy that will give you full control on the S3 service.

(We use this for demonstration simplicity. You can enforce more security by creating your own policy to respect the least privilege principle.)

6. You can put some tags to identify you user if you need it

7. Review your informations and create the user

8. Here you need to keep the Access key ID and the Secret access key somewhere safe. This is the equivalent of your Login-Password.

And that’s it for the AWS IAM part ! Easy stuff right ?

Let’s go back to GitHub !

3. Configure a GitHub Action

You will use a GitHub Action to deploy your files into the S3 bucket.

To make GitHub able to use our AWS user rights, you need to configure the user credentials you just created.

1. Go to the Setting section of your repository menu and click on Secrets

2. Create two new secrets and put the values you kept from the IAM User creation.

AWS_SECRET_ACCESS_KEY

Now that you have our credentials ready, let’s create the workflow itself.

All the steps in your workflow should be created in the .github/workflow/ folder. GitHub Action will monitor this folder to find what to execute.

3. Let’s create a .github/workflow/main.yml

mkdir .github/workflow
touch .github/workflow/main.yml

And add the following code to your main.yml file:

Here you are creating an Action to execute some steps every time a push happen on the main branch. You run your Action on an ubuntu (linux) machine and you have a dependency to one of the already created AWS GitHub Actions.

It configures your credentials as well as the region. It should correspond to the one in which you created your S3 bucket.

Then you can see the Action steps.

As you are pushing a simple html/css folder, you have no build step but you could add some steps here. Maybe generate some build artefacts into a folder and push this folder to the S3 bucket.

You use the aws s3 sync command to synchronise the folder “thefoldertodeploy” with the content of the S3 bucket.

Now you can push this to the main branch.

4. Make a change and Deploy

Now that your Action is configured, change a little thing visible on your website and push this change to the main branch.

Then go to the Actions section of your GitHub repository and observe the steps being executed !

If you want to know more about GitHub Actions, here is a link to spend some time on it !

5. Congrats, it’s celebration time!

Photo by Clay Banks on Unsplash

Congrats ! You have just found a way to focus on what really matter: the content !

GitHub Actions is a really good way to implement a simple pipeline for your static website. You can get ready to push modification within minutes and you will never be responsible for your deployments anymore.

From there, you can do a little exploration session on GitHub actions or just add this topic to your Wish list !

I'm always open for feedback and questions, here in the comments or on my Twitter

Photo by Lennart Jönsson on Unsplash

IT industry is moving fast, very fast ! And nobody can deny that.

I am not going to teach you something new but being industry-aware is really a Big advantage in IT world ! One way to stay up-to-date on major topics is to study for certification exams. It will also help you expand your knowledge.

I found out, on my way to the exam, that I was learning a lot.

And not just about the topics I needed to pass, but also a lot of other side points I was not aware before. This leads me to try the process in the reverse. I was then trying to learn new things having the certification path in mind to guide me through the journey.

I was trying to learn new things having the certification path in mind to guide me through the journey.

Even if everything I will tell you here worked well for me, it might not work the exact same way for you. I am sharing a way to get new skills in an efficient and durable way. You should definitely adapt my story to your personal experience. Try to find out what are the things that can work for you and apply them to get the best out of your training time.

The Wish List method

Everyone knows what a wish list is !

Santa, weddings, birthday and even IT releases sometimes. Wish lists are the way to keep track of our desires and to fulfil them when the time comes.

Wish lists are great !

And they can even be useful for learning. Weird idea ? Absolutely not !

I am sure everyone got lost at least once in the infinite curiosity loop of internet.

You know, when you read an article, or watch a video and you go check one detail on Google. You click on the first link that have another question in it… and then an hour slipped by.

And you will not memorize for long a big part of what you just read. Wish lists are the key to avoid this and enjoy even more the content you can find through your learning path.

The idea behind Wish lists is simple:

For every topic needing a digression, to check some details or explore an other related topic, you add an entry in your Wish list.

This entry should be well classified into the right part of your Wish list. It should be very easy to check on it later.

For example, it can be a link to a useful blog post.

I was learning about AWS Lambda service and I saw a blog post about Lambda performance.

I immediately add it to my Wish list for later reading !

In this case, reading this at the beginning of my learning would have been kind of a mistake. I didn’t have enough knowledge to get all the technical points. But I felt there was something interesting for later.

I added the Lambda article to my Wish list, in the Lambda>Performance chapter. I knew that the day would come where I would remember this article as ready to be read with my acquired knowledge.

This is a good example but don’t get fooled, I didn’t use this method on the first try ! This is the result of all the mistakes I did, trying to learn a lot in a small amount of time.

After a quick training, I started working on my Solution Architect Associate certification. This is when I began to think about my learning strategy. After a lot of trial and errors, I started to build a habit about learning new things in a regular way. I can tell you: Wish lists are clearly part of this process.

1. Find guidance

As it was my first AWS certification, I looked for some kind of guidance to know where to start. I needed to plan my learning and find a way to check that my knowledge was covering all the exam scope.

Photo by Ayelt van Veen on Unsplash

This is step one to get an overview of your learning scope.

Here are some of the main sources you should start with for every new big topic you are trying to learn. I don’t talk about the documentation written by the provider or the community around the topic. It should be of course the first resource to explore !

1.1 Video courses

Beside the AWS guides and documentation, I found some courses on learning platforms:

• Udemy
• Coursera
• A Cloud Guru
• Pluralsight

This is a good starting point. They organise the content in different sections corresponding to the existing domains in the exam.

They usually also include some labs. Those help you to get a better understanding on how to apply the knowledge you are acquiring through the videos.

From my point of view, this is a good way to plan your journey.

It is a bit like having a tourist guide book showing you the path. You can go the other way but it will always try to have your back if you feel a bit lost in the middle of nowhere !

Photo by Holly Mandarich on Unsplash

1.2 Articles

Blog posts or articles can be a good source of inspiration when trying to build your agenda. Big companies usually have their own blog(s). Reading them gives you a hint on new products, but also practical use cases or tutorials.

Community is very powerful. You will find a lot of people writing on their previous experience. They sometimes even talk about how they organized their learning to pass the exam.

You will find a lot of resources in blogs, be careful not to be diverted from your main goal.

A good way to handle all those resources is to use the wish list method. Be sure to organize your findings in a way it is easy to dive into it later.

1.3 Books

Books can also be useful, as learning material but also as guidance.

Inspire your agenda by the book table of contents.

We can usually assume that the authors have a good understanding of the topic they are writing about. The organization of their work has been knowingly chosen. Make sure you checked several books as they can give you different point of view.

For some interesting references, books can of course be part of your wish list. They can be time consuming but retains also great knowledge. Try to get the best out of this

2. Make your Wish list

The Wish list is the key element of the strategy to be able to reach efficiently my certification goal as well as to learn long-term and valuable knowledge.

You can use whatever software you want (even paper if you want, but this is not very convenient to keep links). Build the wish list template that works for you and the topic your are trying to master.

It can be a simple text editor (Markdown can be a good way to deal with presentation layer). You might even make your Wish lists public.To do so, track them into a GitHub repository (GitKraken would be a good tool to help you with that). Productivity tools like Trello are also nice a way to organize your Wish lists even if it can ask for a bit more organisation at the beginning.

During my AWS architecting journey for example I had a Wish list mostly split by AWS services or sometime by big domains like performance, high-availability, security…

The Wish list can be really huge if you are adding stuff without never reading it. That’s why the organisation should be easy to read for you. When starting an exploration session, you don’t want to spend five minutes looking for the right topic to dive in !

Oh wait ! I didn’t introduce you to Exploration sessions, right ? …

Photo by Dariusz Sankowski on Unsplash

3. Split your learning between Sprints and Exploration times

This is a good way to keep your motivation intact through your learning.

Sprints are learning sessions during which you try to cover exam topics. The goal is to progress on the direct path to the exam. It can be by watching a training video, trying some sample questions, memorizing concepts, preparing some training material like notes or cue cards.

Exploration times are here to please your curious self as well as starting to build the knowledge you are looking for. The idea for you is to take the Wish list we made on the previous part and start reducing it. Try visiting the links, digging into the topics, watching videos, reading the articles…

These two kind of learning session are complementary.

Nothing stops you from mixing Sprints with Explorations but make sure you set some time limit for exploration. Indeed, the more curious you are, the more you risk to spend a lot of time digging topics until you land on another one.

“The more curious you are, the more you risk to spend a lot of time digging topics until you land on another one.”

As attractive as this idea sounds, this snowball phenomenon is not the result you want to achieve. You will quickly fall under a lot of equally interesting pieces of information that your brain is not going to be able to prioritize. The consequence is that you are not going to memorize very well what you have just explored.

Start to set specific timing limits. You can just store the underlying topics into your wish list and save it for a later exploration session.

Conclusion

Learning knew things is challenging and time consuming. You knows that if you are a curious human being !

The Wish list method gives you an easy way to organise your learning and to stay focus on your goal during Sprint times.

On the other hand, you will expand your knowledge beyond your smallest goal during Exploration times by building up a strong background knowledge.

Using this method to improve your knowledge through certifications path is a great way to become industry aware of a lot of topics. It gives you a significant advantage when looking for interesting opportunities.

I hope this method can improve the way you think about learning.

Having a great time learning is the most important to enjoy what you are learning!