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AWS – How To Deploy Two Application In Nginx Server?
GenAI – How To Deploy Two Application In Nginx Server ? Table Of Contents: Steps To Deploy Two Application In Nginx Server. Step-1: Mention This PUBLIC_URL Wherever You Are Referring The Static Files. Set base paths so React can load static files properly when hosted under a subfolder. In App.js, all paths to static files should use: src={`${process.env.PUBLIC_URL}/images/Harman-3.png`} Step-2: Take Two Separate Build For Two Applications. # For Softline $env:PUBLIC_URL="/softline/"; npm run build # For Hardline $env:PUBLIC_URL="/hardline/"; npm run build Step-3: SSH Into Server ssh [email protected] Step 4: Create Directories for Each App sudo mkdir -p /var/www/html/hardline sudo mkdir -p
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AWS – How To Redeploy Python API Changes?
GenAI – How To Redeploy Python API Changes? Table Of Contents: Steps To Redeploy The Python Changes. Step-1: Make Your Code Changes Update your FastAPI or Flask code (hardline_main.py, etc.) Step-2: Stop the Existing Service sudo systemctl stop hardline.service Update your FastAPI or Flask code (hardline_main.py, etc.) Step-3: Reload systemd Daemon sudo systemctl daemon-reload This reloads the service definitions (needed only if you’ve edited .service files). Step-4: Start the Updated Service sudo systemctl start hardline.service This starts the service again using your latest code. Step 5 (Optional but Recommended): Enable Service on Boot sudo systemctl enable hardline.service Makes sure your
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AWS – How To Host React JS App In AWS Using EC2 Instance ?
GenAI – How To Host React JS App In AWS ? Table Of Contents: Introduction. Steps To Host React JS App In AWS. (1) Introduction. Step-1: Update System Packages Update your package index to ensure you’re installing the latest versions. sudo apt update Step 2: Install NGINX Web Server Install the NGINX package using APT. sudo apt install nginx Step-3: Upload the React Build Folder To The VM Upload The Build Folder Of The React Js App To The Virtual Machine.(deep_learning_07) On your local machine, navigate to the React app directory, and manually drag the /build folder to the VM,
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AWS – Amazon BedRock
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AWS – Interview Question & Answers
AWS – Interview Question & Answers Table Of Contents:
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AWS – How To Deploy ML Model Using Sagemaker Endpoint Using Docker Container?
GenAI – How To Deploy ML Model Using Sagemaker Endpoint Using Docker Container? Table Of Content: Step By Step Process Of Deployment. (1) Step By Step Process Of Deployment. Step-1: Create A ECR Repository Step-2: Push The Docker Image Into The Repository. Step-3: Attach The Image To Sagemaker Notebook Step-4: Host The Created Image On Sagemaker End Point. (2) How The Sagemaker Will Invoke The Docker Container ? (3) – How Sagemaker Internally Works ? (4) – How Sagemaker Calls The Docker Container Internally ? (5) – If There Are ‘N’ Different Containers Then How Sagemaker Will Decide Which Container
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AWS – How To Deploy ML Model Using Sagemaker Endpoint?
AWS – How To Deploy ML Model Using Sagemaker Endpoint Using Prebuild Container? Table Of Contents: Setup AWS & Install Dependencies. Train & Save The Model. Create A Docker Container. Push The Docker Image To Amazon ECR. Deploy The Model To Sagemaker Endpoint. Make Prediction Using Endpoint Cleanup The Resources. (1) Setup AWS & Install Dependencies. AWS Dependencies: Ensure You Have The The Following Dependencies Installed. An AWS account with SageMaker and ECR permissions. Docker installed (docker – version). AWS CLI configured (aws configure). Boto3 and SageMaker SDK installed. Python Libraries: Python libraries to build the model. pip install boto3
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AWS – Jupyter Lab
AWS – Jupyter Lab Table Of Contents: What Is Jupyter Lab? How To Open Jupyter Lab? (1) What Is Jupyter Lab JupyterLab is an advanced, flexible, and interactive development environment for working with Jupyter Notebooks, code, and data. It is the next-generation interface of the classic Jupyter Notebook and provides a more powerful and modular experience. (2) How To Open Jupyter Lab? Step – 1: Search For Sagemaker In The Search Box. Step – 2: Click On Amazon Sagemaker Step – 3: Click On Open Studio Step – 4: It Will Open Sagemaker Studio Step – 5: Click On Jupyter
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AWS – Cost Explorer & Budgets
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AWS – Private Link
