Applying DevOps Principles on Lean Infrastructure. Lessons From Scaling to 102K Users.
Hi Azure Community, I'm a Microsoft Certified DevOps Engineer, and I want to share an unusual journey. I have been applying DevOps principles on traditional VPS infrastructure to scale to 102,000 users with 99.2% uptime. Why am I posting this in an Azure community? Because I'm planning migration to Azure in 2026, and I want to understand: What mistakes am I already making that will bite me during migration? THE CURRENT SETUP Platform: Social commerce (West Africa) Users: 102,000 active Monthly events: 2 million Uptime: 99.2% Infrastructure: Single VPS Stack: PHP/Laravel, MySQL, Redis Yes - one VPS. No cloud. No Kubernetes. No microservices. WHY I HAVEN'T USED AZURE YET Honest answer: Budget constraints in emerging market startup ecosystem. At our current scale, fully managed Azure services would significantly increase monthly burn before product-market expansion. The funding we raised needs to last through growth milestones. The trade: I manually optimize what Azure would auto-scale. I debug what Application Insights would catch. I do by hand what Azure Functions would automate. DEVOPS PRACTICES THAT KEPT US RUNNING Even on single-server infrastructure, core DevOps principles still apply: CI/CD Pipeline (GitHub Actions) • 3-5 deployments weekly • Zero-downtime deploys • Automated rollback on health check failures • Feature flags for gradual rollouts Monitoring & Observability • Custom monitoring (would love Application Insights) • Real-time alerting • Performance tracking and slow query detection • Resource usage monitoring Automation • Automated backups • Automated database optimization • Automated image compression • Automated security updates Infrastructure as Code • Configs in Git • Deployment scripts • Environment variables • Documented procedures Testing & Quality • Automated test suite • Pre-deployment health checks • Staging environment • Post-deployment verification KEY OPTIMIZATIONS Async Job Processing • Upload endpoint: 8 seconds → 340ms • 4x capacity increase Database Optimization • Feed loading: 6.4 seconds → 280ms • Strategic caching • Batch processing Image Compression • 3-8MB → 180KB (94% reduction) • Critical for mobile users Caching Strategy • Redis for hot data • Query result caching • Smart invalidation Progressive Enhancement • Server-rendered pages • 2-3 second loads on 4G WHAT I'M WORRIED ABOUT FOR AZURE MIGRATION This is where I need your help: Architecture Decisions • App Service vs Functions + managed services? • MySQL vs Azure SQL? • When does cost/benefit flip for managed services? Cost Management • How do startups manage Azure costs during growth? • Reserved instances vs pay-as-you-go? • Which Azure services are worth the premium? Migration Strategy • Lift-and-shift first, or re-architect immediately? • Zero-downtime migration with 102K active users? • Validation approach before full cutover? Monitoring & DevOps • Application Insights - worth it from day one? • Azure DevOps vs GitHub Actions for Azure deployments? • Operational burden reduction with managed services? Development Workflow • Local development against Azure services? • Cost-effective staging environments? • Testing Azure features without constant bills? MY PLANNED MIGRATION PATH Phase 1: Hybrid (Q1 2026) • Azure CDN for static assets • Azure Blob Storage for images • Application Insights trial • Keep compute on VPS Phase 2: Compute Migration (Q2 2026) • App Service for API • Azure Database for MySQL • Azure Cache for Redis • VPS for background jobs Phase 3: Full Azure (Q3 2026) • Azure Functions for processing • Full managed services • Retire VPS QUESTIONS FOR THIS COMMUNITY Question 1: Am I making migration harder by waiting? Should I have started with Azure at higher cost to avoid technical debt? Question 2: What will break when I migrate? What works on VPS but fails in cloud? What assumptions won't hold? Question 3: How do I validate before cutting over? Parallel infrastructure? Gradual traffic shift? Safe patterns? Question 4: Cost optimization from day one? What to optimize immediately vs later? Common cost mistakes? Question 5: DevOps practices that transfer? What stays the same? What needs rethinking for cloud-native? THE BIGGER QUESTION Have you migrated from self-hosted to Azure? What surprised you? I know my setup isn't best practice by Azure standards. But it's working, and I've learned optimization, monitoring, and DevOps fundamentals in practice. Will those lessons transfer? Or am I building habits that cloud will expose as problematic? Looking forward to insights from folks who've made similar migrations. --- About the Author: Microsoft Certified DevOps Engineer and Azure Developer. CTO at social commerce platform scaling in West Africa. Preparing for phased Azure migration in 2026. P.S. I got the Azure certifications to prepare for this migration. Now I need real-world wisdom from people who've actually done it!Burst / B series VMs
Hi everyone, in Cost Management reports I see a line item called “Windows Server Burst” associated with B-Series VMs. I’ve been trying to understand this for a while, but I haven’t been able to find any official Microsoft documentation that clearly explains what this charge covers. My assumption is that it refers to the Windows Server license cost for burstable VMs, and not an additional variable charge when the CPU actually goes into burst mode but I’d like to confirm. Has anyone found an official Microsoft reference or can provide clarification? Thanks a lot!
Scaling Smart with Azure: Architecture That Works
Hi Tech Community! I’m Zainab, currently based in Abu Dhabi and serving as Vice President of Finance & HR at Hoddz Trends LLC a global tech solutions company headquartered in Arkansas, USA. While I lead on strategy, people, and financials, I also roll up my sleeves when it comes to tech innovation. In this discussion, I want to explore the real-world challenges of scaling systems with Microsoft Azure. From choosing the right architecture to optimizing performance and cost, I’ll be sharing insights drawn from experience and I’d love to hear yours too. Whether you're building from scratch, migrating legacy systems, or refining deployments, let’s talk about what actually works.
Former Employer Abuse
My former employer, Albert Williams, president of American Security Force Inc., keeps adding my outlook accounts, computers and mobile devices to the company's azure cloud even though I left the company more than a year ago. What can I do to remove myself from his grip? Does Microsoft have a solution against abusive employers?
Conditional access policy or User risk policy set to force password at high risk doesnt work
Hi all, When setting Conditional access policy or User risk policy set to force password at high risk doesn't work instead I get a blocked windows on users. I have set SSPR too and I think this is a requirement What am I doing wrong?
AzureFunBytes - Episode 1 - Jay covers Azure Storage and solves three problems using it.
AzureFunBytes - A Twitch show on how to use all the fundamentals that are Microsoft Azure. Today Jay covers Azures Storage and solves three problems using it. How can I store objects for my app in the cloud? How do I create a static web site using blob storage? How do I increase storage on an Azure Linux Virtual Machine? Jay takes questions and gives you a start with code and procedure to deploy it. Follow AzureFunBytes on Twitter and Twitch for updates on future episodes. Links for you! Introduction to the core Azure Storage services What is Azure Blob storage? Introduction to Azure managed disks Use the portal to attach a data disk to a Linux VM - Microsoft Learn: Core Cloud Services - Azure data storage options Microsoft Learn: Azure Fundamentals Microsoft LearnTV 24*7 streaming Azure content Get $200 in free Azure credit along with 12 months of free servicesAzure Web App Service and GitHub Actions (Video Tutorial)
The last time we met, I spent some time showing you how to deploy an application using Azure DevOps and Azure Web App Service. It's helpful to watch the last video to get you some context on how to create a Web App Service in Azure. Today we'll add a new step by introducing the same process of deploying from the master branch of the react-block-basic GitHub repository. GitHub Actions GitHub Actions is an API for cause and effect on GitHub: orchestrate any workflow, based on any event, while GitHub manages the execution, provides rich feedback and secures every step along the way. With GitHub Actions, workflows and steps are just code in a repository, so you can create, share, reuse, and fork your software development practices. Get Fast CI/CD - Any language or platform. YAML builds Live logging Workflows are reusable - like code! (Hello fellow StackOverflow Devs!) Simple stateless react app I love to use this app, react-clock-basic to help people learn with. It's simple has minimal dependencies and is stateless. There's no data source to configure for this, we just simply want a clock to tell us the time. jaydestro / react-clock-basic A basic clock that displays the current date and time React Clock This is a fork of this clock app that includes deployments for Azure Kubernetes Service and Docker. App Service Deployment Method: In Azure cloud shell: git clone https://github.com/jaydestro/react-clock-basic.git az group create --name $NAME --location eastus az network vnet create --name $nameVNET --resource-group $NAME --subnet-name default az acr create --resource-group $NAME--name $NAMEacr --sku Basic --admin-enabled true az acr build --registry $NAMEacr --image react-clock-basic:v1 . Go to portal in Azure, create a new app service, select your resource group, pick linux, pick docker container, create a new service plan, select dev/test - click Docker Drop down source, select Azure Container Registry. Click the registry you created above then select the image name and version. Click Review and create. A basic clock that displays the current date and time Go here for live demo. Component Diagram This project also demonstrates: a typcial React project layout structure babel setup and configuration webpack… View on GitHub Your links to start The video should help provide you with a great start on using this service with your Azure Web App Service. Utilizing resources like GitHub actions can help you on your journey to becoming a Microsoft DevOps Certified Expert. Here are links to documentation and guidance on the next steps including Microsoft Learn, Learn TV, and more! Microsoft Learn: Azure Fundamentals Microsoft Learn: Host a web application with Azure App service Microsoft Docs: App Service Documentation GitHub Actions Documentation react-clock-basic demo app Get 12 Months of free service and $200 for Microsoft Azure If you need more help, reach out in the comments or send me a tweet or find me on LinkedIn. Make sure you like and subscribe to my channel on YouTube and stay up to date on my new tutorials. See you next time as we learn Azure together.Multiple Node Pools on Azure Kubernetes Service
One of the most impressive parts of moving applications into the cloud is the ability to apply different types of computing power to your application based on use-case. By taking advantage of all the different compute types within Azure, users access to various CPUs and GPUs that can be implemented. No upfront costs or concerns about racking the gear. No fighting for better support with your vendor or having to buy the latest and greatest to keep up. Azure provides you with a number of options to help implement these various compute options. Different use cases will often require you to make decisions about what compute options you've selected. How will they improve portions of your application for the business? In this post we'll look at how you can use multiple types of compute options within a Kubernetes cluster in order to use different resources for different parts of their application. Getting Started This is a post on understanding Azure Kubernetes Service (AKS) node pools. This is a blog post that makes assumptions that you're done the Azure tutorials around fundamentals. It will also assume you know how to create and use the Azure Kubernetes Service to launch a cluster. If you'd like to start with these, check out these Microsoft Learn Modules and blog posts: Microsoft Docs Learn Azure Fundamentals Microsoft Docs Learn Introduction to Azure Kubernetes Service Kubernetes Terminology for Beginners Azure Kubernetes Service - A Beginner's Guide. What's a node in Kubernetes? From the official Kubernetes Docs The Kubernetes node has the services necessary to run application containers and be managed from the master systems. A node is a worker machine in Kubernetes, previously known as a minion. A node may be a VM or physical machine, depending on the cluster. Each node contains the services necessary to run pods and is managed by the master components. The services on a node include the container runtime, kubelet and kube-proxy. See The Kubernetes Node section in the architecture design doc for more details._ It could be your local computer using minikube, a server in a datacenter or a virtual machine in the cloud. What's a node pool? You can use different types of CPUs and storage with management for your AKS managed nodes. A subset of VM's like hardware and configuration. Scale them based on your utilization. From Create and manage multiple node pools for a cluster in AKS on Microsoft docs website: In Azure Kubernetes Service (AKS), nodes of the same configuration are grouped together into node pools. These node pools contain the underlying VMs that run your applications. The initial number of nodes and their size (SKU) is defined when you create an AKS cluster, which creates a default node pool. To support applications that have different compute or storage demands, you can create additional node pools. For example, use these additional node pools to provide GPUs for compute-intensive applications, or access to high-performance SSD storage. What's a GPU Optimized VM?: From Microsoft docs: GPU optimized VM sizes are specialized virtual machines available with single or multiple NVIDIA GPUs. These sizes are designed for compute-intensive, graphics-intensive, and visualization workloads. Solving a problem Even Fake companies need help Tailwind Traders is the world's biggest fake company with a reference app used for this and many other examples. You can review this video from Azure Friday about the reference apps. You can also review the application repository here, it's open to the world to build with all the tools in this blog post. The Tailwind Traders Website at its core is an e-commerce site with a number of extremely critical services that the company requires reliability and uptime in order to successfully execute new orders. In order for Tailwind Traders to understand their customers better, much of the experience the user has is stored in a NoSQL database in Azure Cosmos DB. Cosmos provides Tailwind Traders with a low latency and high throughput database that works with the MongoDB API. Daily, reports on this information are run and delivered into a web presentable front end. The reports app uses a number of algorithms that the data science team at Tailwind Traders developed along with the application engineer; these are extremely compute-intensive and seem to be taxing the capabilities of the more general-purpose CPU offerings in Azure. The Tailwind Traders engineering team recently looked at processing times of their daily reports for and recognized that even though they were wise enough to architect their application into microservices, they felt that the return time of some reports (nearly 8-9 hours) had a potential of being reduced by utilizing GPUs available in Microsoft Azure. Tailwind Traders will want to use standard CPUs for a portion of the web front end of my app. The company's CIO would like to have reports on their collected data processed quicker on GPUs in order for the business to best place the most popular and impressive products to potential customers based on data captured. The more information Tailwind Traders is able to gain on their customer's experience, the more they can improve it. Proposed Solution: TWT's team will build an AKS cluster with multiple node pools. The two pools will contain different types of computing power to handle the microserviced application workloads. To begin, the team will create a new cluster for AKS, in this case, nodepool01 that will handle the web app front end using a Bs2 series VM for the node pool. You can also create node pools and specify your specific CPU type with az cli tool rather than do so by the portal: # Create a resource group in East US az group create --name myResourceGroup --location eastus # Create a basic single-node AKS cluster az aks create \ --resource-group myResourceGroup \ --name cluster01 \ --vm-set-type VirtualMachineScaleSets \ --node-count 2 \ --generate-ssh-keys \ --kubernetes-version 1.15.7 \ --load-balancer-sku standard # Add a node pool to the cluster az aks nodepool add \ --resource-group myResourceGroup \ --cluster-name cluster01 \ --name nodepool02 \ --node-count 3 \ --kubernetes-version 1.15.7 This cluster will use B-series burstable VMs which are ideal for workloads that do not need the full performance of the CPU continuously, like web servers, small databases and development and test environments - exactly the solution for a web front end service and its required components such as a load balancer. The TWT team chose to create a secondary node pool nodepool02 that will handle my GPU intensive workloads, such as processing data for reports that are used to improve customer experience. The secondary node pool is created using a NC6s_v2 class virtual machine. The TWT tech team next can create a node pool using the az aks node pool add command again. This time, specify the name nodepool02 , and use the --node-vm-size parameter to specify the Standard_NC6 size: az aks nodepool add \ --resource-group myResourceGroup \ --cluster-name myAKSCluster \ --name nodepool02 \ --node-count 1 \ --node-vm-size Standard_NC6 \ --no-wait The TWT team can begin assigning specific pods to nodes by scheduling pods using taints and tolerations. By providing a dedicates pool of GPU backed nodes, TWT will now be able to run their reports using the power of single or multiple NVIDIA GPUs. More Info There's more documentation available to you to find out the best way to implement node pools with AKS. Check out the different links and videos provided before so you can begin using this powerful option for those who want to diversify compute options within their AKS cluster. Resources Microsoft Docs: az aks nodepool Create and manage multiple node pools for a cluster in Azure Kubernetes Service (AKS) GitHub Actions for deploying to Kubernetes service Azure Kubernetes Service (AKS) Multiple node pools in Azure Kubernetes Service (AKS) | Azure Friday Getting production ready in Kubernetes The Author If you're running into issues and need assistance with AKS or any other Azure service, reach out to me: Twitter: @jaydestro Twitch: jaydestro Github: jaydestro I am always happy to hear from developers and engineers who are trying to implement new services to improve their experience for their customers.What I Learned From A Dress, an On-Call Nightmare - Jay Gordon | WFH Conf 2020
In 2015 the viral internet moment of “The Dress” occurred that completely changed what I knew about deploying production web servers. As the on-call resource over the evening, I saw web traffic that peaked at 670,000 active visitors on BuzzFeed.com. In this talk, I share lessons on the moment. After a day of managing a physical data centre build and dealing with a bunch of llamas getting loose in Los Angeles, I came home to what I hoped was an average evening. After a meal and a quick shower, my phone began blowing up with alerts. My wife was sitting on the couch and turned to me, and asked “oh is that about the dress?” I ask her, “what dress?” A dress was shared on the internet that people seemed enamoured with due to a visual trick that caused people to see the dress in different colours. This set off a huge interest in sharing what people thought the colour was. BuzzFeed’s editorial team quickly used a NoSQL backed database app to quickly capture votes from the dress crazed masses. There was one big problem, no one could do anything else. The rest of the website’s backend failed causing front end servers to no longer be able to serve new web traffic. After a several hour alert incident and various remediations, the team I worked with were able to place a reasonable fix in order to keep the mass of traffic coming to our app for collecting people’s votes. The toll an incident like this takes on a team is tremendous. I can explain how old ideas with trusted technology can still lead to failure that can’t be predicted. Viewers will take away an understanding of the human cost of toil in a team when you’re not sure how the traffic is going to come.
