Nathan Nellans’ Post

Are you leveraging the full potential of Infrastructure as Code (IaC) for your Azure deployments? Let's dive into Azure Bicep Playground ! 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗕𝗶𝗰𝗲𝗽? Bicep is a declarative language specifically designed for deploying Azure resources. It offers a cleaner, more concise syntax compared to traditional JSON templates, leading to improved readability and maintainability of your IaC code. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐳𝐮𝐫𝐞 𝐁𝐢𝐜𝐞𝐩 𝐏𝐥𝐚𝐲𝐠𝐫𝐨𝐮𝐧𝐝: 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: The playground fosters a real-time learning environment. Experiment with Bicep code and instantly view the corresponding JSON representation. This side-by-side comparison is invaluable for beginners to grasp Bicep concepts quickly. 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲: Streamline your development process. Write your Bicep code directly within the playground and receive immediate validation. This eliminates the need for constant switching between editors and deployment tools, saving you valuable time. 𝐅𝐮𝐭𝐮𝐫𝐞-𝐩𝐫𝐨𝐨𝐟𝐞𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Bicep stays current with the latest Azure services and APIs. The playground reflects these updates, ensuring you can seamlessly leverage new functionalities as soon as they're released. 𝑼𝒔𝒆 𝑪𝒂𝒔𝒆𝒔 𝒇𝒐𝒓 𝒕𝒉𝒆 𝑨𝒛𝒖𝒓𝒆 𝑩𝒊𝒄𝒆𝒑 𝑷𝒍𝒂𝒚𝒈𝒓𝒐𝒖𝒏𝒅: 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: The playground provides an ideal platform to explore Bicep functionalities and deepen your understanding through hands-on practice. 𝐑𝐚𝐩𝐢𝐝 𝐏𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐢𝐧𝐠: Effectively prototype your Azure resource deployments before integrating them into a full-fledged CI/CD pipeline. This iterative approach minimizes errors and streamlines the development process. 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐃𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠: Isolate and resolve issues within your Bicep code with ease. The playground's real-time validation helps pinpoint errors quickly, saving you valuable debugging time. Unlock the Power of Bicep Today! Head over to the Azure Bicep Playground and experience the benefits firsthand. This powerful tool can significantly enhance your Azure deployments and streamline your IaC workflow. https://lnkd.in/gKhQmpGr #Azure #Bicep #IaC #CloudDevelopment #Microsoft

Ever found yourself in a tech maze, scratching your head over why things just won't work? That was me recently. Deploying a web application as a practice project seemed straightforward, until it wasn't. The culprit? A classic case of overlooking the basics. After hours of digging into complex errors and scratching my head, I decided to give my frazzled brain a break. And then it hit me like a ton of bricks, or maybe just a gentle tap on the shoulder. Turns out, I forgot a step as fundamental as it gets – installing AWS CLI on my instances! 🤦♂️ Here I was, trying to copy scripts from an S3 bucket to instances via AWS CLI without even having it installed. Silly, right? it's all part of the learning journey. 🎓 Sometimes, we need those moments of humble realization to remind us that even the most complex issues can often be traced back to the basics. #AWS #CloudComputing #DevOps #IaC

🚀 New AWS Guide Alert! 🌐 Curious about how to create an AWS Lambda Function and use Function URLs? I've got you covered! 💡 In my latest Medium article, I break down the steps to help you deploy and scale your code with ease. If you're working with cloud services, this one's for you! ☁️ #AWS #Lambda #CloudComputing #Serverless #Python #TechGuide #Programming #DevOps #AWSLambda

AWS Lambda Limitation Overcome 🚀: Adding FFmpeg Support with Docker! 🐳 As developers, we face many roadblocks that put our skills and ingenuity to the test. Recently, I had a big one: AWS Lambda unsupported natively for FFmpeg, one of the key tools for multimedia processing. After hours of researching and trying to solve the problem, I came across a solution that I'm excited to share! In my latest Medium blog, I walk you through how you Dockerize your AWS Lambda function to add FFmpeg support seamlessly. Be it video encoding, audio extraction, or whatever-related to multimedia, this guide gives you empowerment around the limitations of the Lambda environment. 👉 Read the full guide here: https://lnkd.in/gVvAuh5F What you'll learn: 👉 Why AWS Lambda doesn't support FFmpeg out of the box? 👉 How to create a custom Docker image step by step? 👉 How to deploy your Dockerized Lambda function with FFmpeg. 👉 Real-world use cases for using Lambda in multimedia processing. This blog is packed with insights, code samples, and practical steps to get you up and going. It's time to break through the limitations of serverless computing together! 🔗 Dive into the blog now and level up your AWS Lambda skills! #AWSLambda #Docker #FFmpeg #Serverless #CloudComputing #DevOps #Python #AWS #TechBlog #Developers #CloudEngineering #MultimediaProcessing #ProblemSolving #CodingTips #LambdaFunctions

Struggling with file upload ? I've written a blog post that provides a step-by-step guide on setting up AWS S3 and CloudFront to handle file uploads in a Node.js application. This guide is based on my recent implementation in a MERN stack project. The blog covers: ▶Setting up S3 for file storage ▶Configuring CloudFront as a CDN ▶Implementing file operations in Node.js For those interested, I've included the full code in my GitHub repository: https://lnkd.in/dnfV-C4A

Hello everyone, I've developed a utility that solves the preemption challenge when leveraging cost benefits of GCP spot VMs. Keeper ensures continuous service by automatically recovering terminated spot instances, making spot VMs a reliable choice for some production workloads. 🔧 Technical Stack: • Cloud Functions (2nd gen) • Cloud Scheduler • Infrastructure as Code with Terraform • Python • Fully automated recovery 📈 Benefits: • Up to 91% cost savings with spot VMs • Minimal downtime • Easy setup and configuration • Infrastructure as Code approach 🔗 GitHub: https://lnkd.in/dMuKBpWU #CloudComputing #GCP #DevOps #Automation #IaC #Python #Terraform

🐳 Exploring Dockerfile: ENTRYPOINT vs CMD 📋 In my Dockerfile journey, understanding the distinction between ENTRYPOINT and CMD has been key. Here's a brief breakdown: 🔹 ENTRYPOINT: This instruction specifies the default command to run when a container is started. It's like setting the main executable for the container. The ENTRYPOINT is not overridden by command-line arguments during container execution. For example: ENTRYPOINT ["executable", "param1", "param2"] 🔹 CMD: On the other hand, CMD sets default arguments for the ENTRYPOINT or specifies the command to run if ENTRYPOINT is not specified. CMD can be overridden by command-line arguments. For example: CMD ["default_command", "arg1", "arg2"] In the example shown in the picture, running the container without any additional arguments will start the "app.py" script in debug mode (--debug), thanks to the CMD instruction. Understanding the distinction between ENTRYPOINT and CMD can help you design more flexible and reusable Docker images! 🚀💻 #Docker #Dockerfile #DevOps #TechInsights #aws #awscloud #awscommunity #azure #azuredevops

So, I had a little mishap with CORS errors recently! 😅 I forgot to set the CORS policy on my AWS S3 bucket, and guess what? The front-end developer was not thrilled about the "Access-Control-Allow-Origin" error. 🚫 A quick adjustment to the CORS settings, and poof—problem solved! ✅ Just a friendly reminder that sometimes the simplest oversights can cause the biggest headaches. Because who doesn’t love troubleshooting unnecessary errors? 🤦♂️ #AWS #S3 #CORS #DevOps

🚀 Excited to Share My Latest Project: ImageSafe! 🚀 #ImageSafe: A Self-Hosted Docker Hub for Private Container Management ImageSafe is a self-hosted Docker registry designed to securely store and manage container images. It's user-friendly and gives you full control over your data. With robust access controls, only authorized users can push or pull images. Features: Secure & Private: Only authorized users can manage images. Self-Hosted: Full control over your registry and data. Scalable: Grows with your team’s needs. Access Control: Easily manage who can push or pull images. Tech Stack: Docker, Nginx, Docker Compose, AWS S3 Bucket, Golang, AWS EC2, Kubernetes 👉 Check out the project: https://lnkd.in/dWwkuyKq 🙌 #Docker #DevOps #ContainerManagement #TechInnovation #SelfHosted #AWS #Golang #Kubernetes #CloudComputing

Coding with Callie #deployInPublic challenge 5 ✅ ! I’ve just completed the Simple NestJS API Deployment with Github Actions Challenge! 🌟 Here’s a quick rundown of what this challenge involved and what I accomplished: In this challenge, I deployed two simple NestJS APIs into Docker containers running on EC2 instances using GitHub Actions. The infrastructure setup mirrored the one from challenge 4, with the following components: AWS Resources set up automated with Terraform: A VPC with 2 public subnets and 2 private subnets in different availability zones. An Internet Gateway and 2 NAT Gateways to manage internet access. Public and Private Route Tables to handle routing. 2 Private EC2 Instances set up with #Docker and deployed with the APIs. A Security Group to manage access to the private instances. An Application Load Balancer to distribute the load between the two private servers. An Elastic Container Registry (ECR) for storing Docker images. An IAM Role for EC2 instances to connect via Session Manager and access the ECR repository. Here is what I Did: -Provisioned #AWS Infrastructure: Set up VPC, subnets, gateways, route tables, EC2 instances, and other necessary resources. -Configured the Load Balancer: Ensured it correctly distributed traffic between the two APIs through health checks. -Built and Pushed Docker Images: Verified that I could build Docker images from my local machine and push them to ECR using #GitHubActions. -Deployed APIs on EC2 Instances: Set up the APIs in Docker containers and ensured they were up and running. -Validated Everything: Checked that the APIs responded correctly when accessing the Application Load Balancer’s DNS address. The struggle for this was writing the script with #YAML. The syntax for yaml is very picky and unforgiving lol! But I have learned a lot from my mistakes!!! A huge shout-out to Johnny Zavala and Daniel Neri for their incredible support and guidance throughout this challenge. Your help made a big difference, and I couldn’t have done it without you! 🙌 I’m super excited for the next challenge and eager to dive into new learning opportunities. Stay tuned for more updates as I continue to explore and grow in the world of #DevOps and cloud technologies! 📸 Here’s a sneak peek at my setup! #DevOps #AWS #Docker #GithubActions #Terraform #CloudComputing #NestJS #APIDeployment #CodingWithCallie #OpenToWork