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Mastering S3 File Operations with Python Boto3: Read, Write, Copy, and Move Simplified https://lnkd.in/dTKB46yQ Amazon Web Services (AWS) #aws #awslambda #businesscompassllc

AWS Lambda SnapStart speeds up startup times for Python and .NET functions to under a second, enabling highly responsive serverless apps with minimal code changes. #aws #awscloud #cloud #announcements #awslambda #compute #launch #news

Apache Airflow 2.9.0 has been released, featuring numerous fixes, enhancements, and new functionalities. Known for its versatility, Airflow offers a broad spectrum of operators for smooth task execution across multiple platforms such as Google Cloud Platform, Amazon Web Services, and Microsoft Azure. Its flexibility enables the creation of sophisticated workflows using Python code, making it suitable for both traditional and cutting-edge technologies. With Airflow, orchestrating complex processes becomes simple and scalable. #airflow2.9.0 #apacheairflow 👇 Release notes: https://lnkd.in/gXz5VsFh Python : https://lnkd.in/gs2uNmQF Airflow doc: https://lnkd.in/g-66cKSF

Attention all Python enthusiasts! Our latest blog post "Soaring Through the Clouds: Master the Art of Python Application Deployment" is now live. This comprehensive guide provides a detailed roadmap on how you can deploy your Python applications on various cloud platforms like AWS, Azure, and Google Cloud. But that's not all! The post also delves into the marvel of containerization with Docker, explaining how you can package your entire app along with all its dependencies into a single portable unit. Whether you're a budding developer or an experienced programmer, this guide serves as your stepping stone towards achieving scalability, portability, and seamless cross-platform service integration. Dive into the world of cloud deployments and containerization, understand the perks of each platform, and learn how to leverage these for enhancing your application's performance and scalability. Remember, deploying your Python application is merely the start. The real magic unfolds when your users interact with your masterpiece. Tap to learn more: https://lnkd.in/eftigSUY  #PythonDeployment #CloudComputing #Docker

Streamlining AWS Lambda Cost Analysis with Python and Jenkins: An Automated Approach https://lnkd.in/dpR3fMbn Amazon Web Services (AWS) #aws #awslambda #businesscompassllc

Streamlining Python Application Deployment on AWS Lambda with the Serverless Framework: A Step-by-Step Guide #AWS #businesscompassllc #cloud

Let’s teach boto3 to store floats and datetime objects in DynamoDB! 👨🏫 The resource API in boto3 is a higher-level abstraction that lets you interact in a more pythonic way with AWS services. This means you can use language idioms that make the code easier to understand, and boto3 translates that into the underlying representation that the AWS API likes. In this blog post, our colleague Maurice shows how to teach the table resource in boto3 to handle more data types by writing custom serializers and deserializers and injecting them into the SDK’s data flow. Learn more here ► https://lnkd.in/eSzZ4MS8 #AWS #Cloud #DynamoDB #boto3 #python #API #CloudComputing

Building serverless apps on AWS using Python is a really nice choice in many cases. With the AWS SDK for python you can work with any resources and build what you need. You can also use the Cloud Development Kit (CDK) for Python which offers some higher level abstractions. Two of the most popular frameworks/tools to work with Python on AWS are AWS Chalice and AWS Powertools for Lambda. If you’re migrating from something like Flask, using Chalice might be exactly what you need. This article from Arnel Jan Sarmiento shows how you can use AWS Chalice along with the CDK to build serverless apps with Python https://lnkd.in/eewZX39T

Getting Started with Extracting File Information in Python https://lnkd.in/dgCPW4Sp Amazon Web Services (AWS) #aws #awslambda #businesscompassllc

Day 1 of 30 Days of DevOps 🤖 Kicking off my #30DaysOfDevOps journey with a simple yet impactful project: a weather dashboard! ☀️ This dashboard fetches real-time weather data using the OpenWeather API and stores it in Google Cloud Storage. ☁️ Built with Python, this project demonstrates core DevOps principles like: - Infrastructure as Code (IaC): Utilizing Google Cloud for storage and leveraging the dotenv library for managing environment variables. - Continuous Integration/Continuous Delivery (CI/CD): While not explicitly implemented in this basic example, the architecture can easily be extended to include CI/CD pipelines for automated deployments and testing. 🛠️ Check out the full article and code on Hashnode: https://lnkd.in/dqJPXCtV I'm excited to learn and grow throughout this challenge! I'm open to feedback and suggestions! 💡 Let me know what you think in the comments. 💬 #DevOps #Python #GoogleCloud #OpenWeatherAPI #30DayChallenge #LearningJourney