Sayan Chakraborty’s Post

We've had buckets of announcements this week, and I'm sure lots of you have eleven 9's of excitement about this one! 🪣✨ AWS has expanded S3 bucket scaling in a big way - here's what you need to know: S3 Bucket Scaling: What's New • Default quota now 10,000 buckets per account • Request increase up to 1 million buckets • Applied to all AWS Regions • No action needed for default increase Practical Benefits for Developers • Create buckets for individual datasets • Implement granular security policies • Enable default encryption per bucket • Use S3 Replication more easily Optimize Your S3 Architecture • Separate concerns with dedicated buckets • Improve data isolation and management • Remove barriers to scaling • Enhance overall storage architecture Cost and Scaling Considerations • First 2,000 buckets at no cost • Small monthly fee for buckets beyond 2,000 • Use Service Quotas for limit increases • New default applies to all AWS accounts Read all about it: https://lnkd.in/e2BPCnpy Could this S3 update solve any challenges in your current projects? Tell me all about it in the comments below 👇 👩🏻💻 Follow me (Brooke Jamieson) for the latest AWS + AI updates. 📍 save + share! #AWS #AmazonS3 #CloudStorage #CloudComputing

🚀 Building Event-Driven Architectures with AWS 🌐  Excited to share a recent project showcasing a serverless event-driven architecture using AWS! Here's how it works:  ✅ Amazon S3 acts as the event source, triggering actions whenever events (like file uploads) occur.   ✅ An AWS Lambda Function processes these events with custom logic, enabling seamless automation and data handling.   ✅ IAM ensures secure and fine-grained access between services, keeping the workflow secure.   ✅ Amazon CloudWatch Logs provides monitoring and debugging capabilities, ensuring the system runs smoothly.  This architecture is scalable, cost-efficient, and highly responsive, perfect for real-time workflows like file processing, data analytics, and automated notifications. A special thanks to my mentor, QASIM HASSAN, for his invaluable guidance and support throughout this project! 🙏  📈 Ready to scale your operations with serverless technology? Let’s connect and discuss how! 🌟  here is my youtube video in which I completely explain what we do in this project: https://lnkd.in/d-pNPtFD #AWS #Serverless #CloudComputing #EventDrivenArchitecture #Automation

AWS has announced two new features for Step Functions that aim to improve productivity and developer efficiency: Variables: Allows developers to assign and reference data across different states, streamlining state payload management. JSONata data transformations: Enables advanced data manipulation and transformation, including date/time formatting and mathematical operations. These additions to AWS Step Functions are designed to: 1/ Simplify the development of distributed serverless applications 2/ Enhance payload management 3/ Reduce the need for custom code. Here are the links to learn more: https://lnkd.in/gtx4aH6m https://lnkd.in/ganzc3YD #aws #serverless #stepfunctions

We are also glad to have worked with the Datadog team to ensure that their instrumentation fully support the new JSONata payloads for standard tracing. Also, with JSONata, you can now get deeper trace context when using AWS Step Functions. Here is the blog post from Datadog to learn more: https://lnkd.in/gxz2_fWd

I am excited to share that I've completed the "Architecting Serverless Applications" course on AWS! This journey has been incredible, diving deep into the world of serverless architecture, where I learned to design and deploy scalable, cost-effective applications without worrying about server management. Key Takeaways: - Event-driven Computing: Harnessing the power of AWS Lambda to trigger functions in response to various events. - Scalable Architectures: Building applications that automatically scale to meet demand, ensuring high availability and reliability. - Cost Optimization: Leveraging pay-as-you-go models to minimize costs and maximize efficiency. - Integration: Seamlessly integrating various AWS services like API Gateway, DynamoDB, and S3 to build robust applications. A big thank you to the AWS team for providing such a comprehensive and hands-on course. Looking forward to applying these skills in real-world projects and exploring more in the AWS ecosystem! #AWS #Serverless #CloudComputing #TechInnovation #ContinuousLearning #CareerGrowth #AWSCertified

Ditch the Server : AWS Lambda AWS Lambda lets you write code (functions) without managing servers. Lambda handles it all - scaling, patching, the whole shebang! Here's the Magic: Focus on Code: No server headaches, just write brilliant code. Pay-Per-Use: Only pay for what you use, perfect for any project size. Scales Like Crazy: Lambda handles any traffic surge. Event-Driven: Trigger functions with events (file uploads, database changes). Build What You Want: Microservices: Break down complex apps into bite-sized functions. Real-Time Magic: Respond to events instantly, like processing data streams. Serverless APIs: Build APIs without servers, hello serverless future! Background Tasks: Offload tasks (image resizing, data analysis). Ready to Go Serverless? Unleash the power of AWS Lambda and build faster, more scalable apps! #AWSLambda #Serverless #CloudComputing

Limitations of AWS Lambda: When considering AWS Lambda for your tasks, it's crucial to be aware of certain limitations that could impact your operations. Here are five key points to keep in mind: 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗧𝗶𝗺𝗲 𝗟𝗶𝗺𝗶𝘁:  Each Lambda function has a maximum execution timeout of 15 minutes, which might be restrictive for tasks with longer processing requirements. 𝗠𝗲𝗺𝗼𝗿𝘆 𝗮𝗻𝗱 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗶𝗺𝗶𝘁𝘀:  Lambda allows memory allocation between 128 MB and 10,240 MB, but CPU and resource availability scale with memory. This allocation may not suffice for compute-intensive tasks. 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝗦𝗶𝘇𝗲:  The deployment package size is capped at 50 MB for direct uploads and 250 MB for S3 .zip files. This constraint could pose challenges for larger applications. 𝗖𝗼𝗹𝗱 𝗦𝘁𝗮𝗿𝘁 𝗟𝗮𝘁𝗲𝗻𝗰𝘆:  "Cold starts" occur when a Lambda function is invoked after a period of inactivity, causing increased latency as the environment initializes. This latency can be problematic for applications requiring low latency. 𝗖𝗼𝗻𝗰𝘂𝗿𝗿𝗲𝗻𝗰𝘆 𝗟𝗶𝗺𝗶𝘁𝘀:  AWS imposes account-level limits on concurrent executions, with a default of 1,000. High levels of simultaneous function invocations can affect performance.  Stay informed about these limitations to make informed decisions when leveraging AWS Lambda for your projects. #AWS #Lambda #CloudComputing #TechLimitations #bigdata #dataengineering #interview

🚀 Thrilled to share my latest review on AWS Lambda with PeerSpot! 🚀 In this review, I explore how AWS Lambda has become an essential tool for our real-time data, media, and file processing needs. Its event-driven architecture has been instrumental in allowing us to process user-uploaded content, such as filtering, resizing, and applying effects to media files with minimal latency. Lambda's ability to automatically scale to meet demand has also enabled us to handle spikes in traffic seamlessly and cost-effectively. AWS Lambda has significantly improved our operations, driving cost savings and resource efficiency through its pay-per-use pricing model and eliminating the need for managing servers. This has freed our team to focus on strategic tasks, enhancing agility and scalability in response to changing workloads. While AWS Lambda offers many advantages, such as automatic scaling and event-driven architecture, there are areas for improvement. The 15-minute execution timeout is restrictive for long-running tasks, and cold start latency can impact performance, particularly for infrequent invocations. It would be great to see more flexible execution environments and reduced cold start latency in future updates. Thanks to PeerSpot for the opportunity to share these insights! 👉 Check out my full review here: https://lnkd.in/dZBufEWA #AWS #Lambda #Serverless #CloudComputing #RealTimeProcessing #DevOps #TechReview #PeerSpot #CloudArchitecture #Innovation #MediaProcessing #Scalability

🌟 Day 10 of 30: AWS Lambda—Serverless Simplicity or Hidden Complexity? 🖥️🔄🌟 AWS Lambda has redefined how we build and deploy applications, offering a serverless approach that promises simplicity and scalability. But is Lambda really as straightforward as it seems, or are there hidden complexities to consider? The Promise of Lambda: •🚀 No Servers to Manage: Focus on writing code, not managing infrastructure. Lambda automatically handles the scaling, patching, and maintenance. •⏱️ Pay Only for What You Use: With Lambda, you’re billed per request and execution time, making it cost-effective for unpredictable workloads. •🌐 Event-Driven Architecture: Trigger functions in response to various events, enabling real-time data processing and automation. The Hidden Complexity: •🔄 Cold Starts: If your functions aren’t running continuously, cold starts can introduce latency, impacting performance. •🧩 Complexity in Orchestration: While Lambda simplifies individual tasks, orchestrating multiple functions can become complex without proper design. •🛠️ Monitoring and Debugging: Serverless architecture means you have less visibility into the underlying infrastructure, making debugging and monitoring more challenging. AWS Lambda offers powerful capabilities, but success depends on understanding and navigating its nuances. How do you leverage Lambda in your serverless applications? #AWS #Lambda #Serverless #CloudComputing #TechInsights

💻👨💻 DAY 47 Of Revising My AWS Concepts 💡 Automating Tasks Without Servers? AWS Lambda to the Rescue! 🖥️ ✔Ever wondered how to build applications without worrying about server management? AWS Lambda lets you run code in response to events while only paying for what you use! In my latest project, I implemented a Lambda function to automate scaling and streamline processes with zero downtime. Here’s how: 🔹 Event-driven architecture: Perfect for microservices 🔹 Cost-effective: Pay only for the compute time you use 🔹 Integration with S3, RDS, and more 💡💡AWS Lambda is a server less computing service that allows developers to run code in response to events without the need for server management. 💡💡It follows an event-driven model, executing code in response to events triggered by changes to data in an Amazon S3 bucket, updates to a DynamoDB table, or HTTP requests via Amazon API Gateway, among other sources. 🔑Key Features of AWS Lambda🔑 🌟Server less Architecture 🌟Event-Driven Execution 🌟Automatic Scaling 🌟Pay-as-You-Go Pricing 📊Advantages of AWS Lambda Over EC2📊 👉Cost Efficiency 👉Automatic Scaling 👉Reduced Operational Overhead: 👉Event-Driven Model 👉Reduced Time to Market 👉Micro billing 🧾Steps involved in creating a function in AWS Lambda🧾 ✍Navigate to AWS Lambda ✍Create a New Lambda Function ✍Define Function Code ✍Create role in IAM ✍Attach the role in lambada configuration option ✍Test Your Function #AWS #AWSLambda #CloudComputing #Serverless #DevOps #TechInnovation #Automation