#Cloud Computing Infrastructure

Comment “CLOUD” to get the links! 🔥 Trying to work in modern tech without understanding Cloud Computing is like building software for a single laptop in a world that runs on distributed systems. If you want scalability, reliability, and real-world engineering skills, this mini roadmap is your entry point. ⚡ Cloud Computing Explained A clear, high-level breakdown of what cloud computing actually is, why it exists, and how companies really use it. ⏱ Cloud Computing in 2 Minutes A fast, simplified overview to lock in the core ideas: servers, regions, scalability, and on-demand infrastructure. ☁ What is Cloud Storage? Understand object storage, why it replaced traditional servers, and how data is stored and accessed at scale. 💡 With these Cloud resources you will: 🚀 Think beyond “my code runs locally” and start thinking in distributed systems 🧠 Understand the foundations behind AWS, Azure, and GCP 🏗 Bridge the gap between writing code and deploying real, scalable applications ☁ Level up for Backend, Cloud, DevOps, and Production Engineering roles If you want to move from “I built an app” to “I deployed a system that scales,” Cloud Computing isn’t optional, it’s foundational. 📌 Save this post so you always have a Cloud roadmap. 💬 Comment “CLOUD” and I’ll send you all the links! 👉 Follow for more Backend Engineering, Cloud, System Design, and Career Growth.

Yesterday I visited one of the biggest data centers in Europe! 🌍 Microsoft’s Dublin data center powers cloud services and AI services for businesses, governments and organisations across Ireland, the UK and much of Northern Europe. Hyperscale data centers like this one can host tens of thousands, and sometimes even hundreds of thousands of servers! What I found insane wasn’t actually the number of servers, it was the huge amount of infrastructure (power, cooling, etc) that helps to keep this data center running. Thanks to @microsoft for inviting me on the tour! ❤️

AI has outgrown traditional cloud infrastructure. A new category is emerging: NeoClouds. 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 data centers were designed for general workloads: Web apps, Databases, Storage, Virtual machines. AI workloads are different. Training frontier models requires tightly coupled GPUs, extreme networking bandwidth, and sustained high-density power delivery. NVIDIA CEO Jensen Huang calls these environments 𝗔𝗜 𝗙𝗮𝗰𝘁𝗼𝗿𝗶𝗲𝘀.Facilities where compute and data go in, and trained intelligence comes out. NeoClouds are the operators building them like CoreWeave, Lambda, Nebius. They were purpose-built for GPU-intensive AI training from day 1, not retrofitted from general cloud architecture. 𝗪𝗵𝗮𝘁 𝗠𝗮𝗸𝗲𝘀 𝗡𝗲𝗼𝗖𝗹𝗼𝘂𝗱𝘀 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 ☑️ Massive GPU clusters functioning as a single supercomputer ☑️ Bare-metal performance with minimal abstraction layers ☑️ Ultra-low latency networking for distributed training ☑️ Advanced liquid cooling to sustain high thermal loads For large-scale model training, this changes economics and timelines dramatically. 🤝 Hyperscalers are not disappearing. They are partnering. Building AI-scale infrastructure takes years, and model demand is compounding now. We are seeing the specialization of cloud infrastructure in real time. Understanding where your workload fits is no longer optional. It affects cost, performance, and competitive advantage. ____ 👋 Hi, I’m Viktoria, Principal AI Evangelist at Databricks. I make complex AI accessible. Follow for more! #AIExplained #NeoCloud #AIFactory #CloudComputing #LearnAI

Follow @cloud_x_berry for more info #CloudArchitecture #CloudComputing #CloudEngineer #ModernCloud #TechInfrastructure cloud architecture basics, cloud compute services, cloud storage solutions, cloud networking, cloud security, cloud monitoring, scalable applications, high availability, load balancing, distributed systems, infrastructure as a service, platform as a service, serverless computing, containerized applications, Kubernetes in cloud, AWS Azure GCP, cloud deployment models, DevOps in cloud, cloud best practices, enterprise cloud systems

Summit at @oakridgelab was the fastest Supercomputer a few years back with 9000 @ibm CPUs and 28000 @nvidia GPUs. The machine was used for deep scientific and government work. Now a new champion has risen to replace SUMMIT. FRONTIER is officially the fasted Supercomputer as of September 2022. Check it out @oakridgelab page 😳 #technology #science #computing #usa🇺🇸 #tech #supercomputer #simulation #pcmr #pcbuild #performance #innovation #speed #lab #experiment #pc #nvidia #ibm #cpu #gpu

🌐 Want to become a Cloud Engineer? 🚀 Day 2 is all about networking—the foundation of cloud infrastructure! Now that you know what you need to focus on, here are a few resources to get you started: 📚 Computer Networking: A Top-Down Approach by Kurose and Ross [https://a.co/d/4Sou5J2] is a must-read to build your networking fundamentals. 💻 Networking commands you should know: ping: Check if a host is reachable. traceroute: See the path data takes across a network. netstat: Display network connections and routing tables. route: View or modify the routing table. dig/nslookup: Retrieve DNS information. tcpdump: Capture and analyze network traffic. tcpflow: Inspect the network flow. These tools will help you sharpen your troubleshooting skills and prepare for cloud engineering interviews. Let’s get started! 💡 #CloudEngineer #NetworkingSkills #TechWithKriti #NetworkingBasics #CloudSkills #WomenInTech #TechCareers #CloudComputing #AWSJourney #TechTok #CloudCertifications #TechCommunity #DevOps #NetworkingFundamentals #ITSkills #CyberSecurity #NetworkTroubleshooting #TechEducation #CloudArchitect #EngineerLife #AWSCommunity #AzureLearning #techtokwithkriti

Inside Google Data Center #TechInnovation #GoogleCloud #GoogleDataCenter #DataCenterTour #CloudInfrastructure #ServerCooling #LiquidCooling #HighPerformanceComputing #AIInfrastructure #TechInside #FutureOfTech #GreenDataCenter #EdgeComputing #CyberSecurity #TechTour #GoogleCloud #HyperscaleDataCenter

Cloud Computing Roadmap: From Beginner to Expert 1. Introduction to Cloud Computing - Definition and Basics - Evolution of cloud computing - Benefits and Challenges 2. Cloud Service Models - Infrastructure as a Service (IaaS) - Virtual Machines - Storage solutions - Platform as a Service (PaaS) - App hosting - Database services - Software as a Service (SaaS) - Cloud-based software apps 3. Cloud Deployment Models - Public Cloud - Private Cloud - Hybrid Cloud - Multi-cloud 4. Core Cloud Services - Compute - EC2, Azure VM, Google Compute Engine - Storage - S3, Azure Blob, Google Cloud Storage - Databases - AWS RDS, Azure SQL, Google Cloud SQL 5. Networking in Cloud - Virtual Networks - Load Balancers - Content Delivery Networks 6. Cloud Security - Identity and Access Management (IAM) - Data encryption - Compliance and Certifications 7. Cloud Management and Monitoring - Resource monitoring - Automation and scaling - Cloud cost management 8. Containers and Microservices in Cloud - Docker - Kubernetes - Amazon ECS, Azure Kubernetes Service 9. Cloud DevOps - Continuous Integration & Continuous Deployment (CI/CD) - Infrastructure as Code (IaC) 10. Advanced Cloud Architectures - Serverless computing - AWS Lambda, Azure Functions - Big Data and Analytics - AWS Redshift, Google BigQuery - Machine Learning in the Cloud - AWS SageMaker, Azure ML 11. Multi-cloud strategies - Using AWS, Azure, GCP together - Data transfer and interoperability Projects to Add to Resume: 1. Deploy a multi-tier web application in the cloud. 2. Migrate an on-premises database to a cloud provider. 3. Set up a CI/CD pipeline using cloud services. #cloudcomputing #aws #gcp #azure #microsoft #jobs #interview #sql #dsa #programmer #programming #programminglife

Billions are being poured into data centres :- the backbone of AI, cloud, and your everyday apps. From Adani to Airtel, everyone’s betting big. Comment ‘Data centre’ & I’ll DM you the full breakdown. #datacentre #digitalindia #infra #investing #TechTrend #indianmarkets #AIReady #Bharat2030 [ data center, internet, tata, ]

Handling 1 Million RPS isn’t about code — it’s about smart architecture. 1️⃣ Traffic Distribution (Load Balancers) ➡️ Spreads incoming requests across many servers so nothing overloads. Example: 1M requests split across 200 servers = ~5K requests per server. ⸻ 2️⃣ Scale Out, Not Up (Horizontal Scaling) ➡️ Add more machines instead of making one server bigger. Example: Flash sale traffic? Instantly launch 50 new API instances. ⸻ 3️⃣ Fast Reads with Cache ➡️ Use Redis/Memcached to avoid hitting the database every time. Example: Cached user data = millions of DB calls saved daily. ⸻ 4️⃣ Edge Delivery with CDN ➡️ Static content loads from servers closest to the user. Example: Users in Delhi fetch images from a Delhi CDN node. ⸻ 5️⃣ Background Work with Queues ➡️ Heavy tasks run asynchronously so APIs respond instantly. Example: Payment succeeds now, email receipt sent in background. ⸻ 6️⃣ Split the Database (Sharding) ➡️ Divide data across multiple databases to handle scale. Example: Usernames A–M on one shard, N–Z on another. ⸻ 7️⃣ Rate Limiting ➡️ Prevent abuse and traffic spikes from taking the system down. Example: Limit clients to 100 requests/sec to block bots from killing the API. ⸻ 8️⃣ Lightweights Payloads ➡️ Smaller payloads = faster responses + less bandwidth. Example: Send only required fields instead of massive JSON blobs. Please follow for more such videos🙏 #systemdesign #softwaredevelopers #programming #tech #interview [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]

Se os serviços da AWS tivessem boca, você já teria levado uma bronca hoje? 🗣️🔥 A gente acha que Cloud é só alegria, mas imagina a paciência do EC2 com os Security Groups abertos e do S3 virando lixeira de log... Esse compilado é um aviso: trate bem sua infraestrutura, ou ela vai começar a responder (e não vai ser via ticket de suporte)! 😅 Qual desses serviços é o que mais sofre na sua mão? Comenta aí! 👇 #AWS #CloudComputing #techhumor

Microsoft’s underwater data center is changing the way we think about cloud storage. Servers placed 117 feet below the ocean surface use natural cooling, reduce energy consumption, and are protected from humidity and oxygen offering a more reliable and sustainable solution for the future of data management. #microsoft #datacenter #cloudcomputing #techinnovation #sustainabletech #ocean #facts #nature #knowledge