🚀 Tech Highlight for today's post: Amazon Simple Queue Service (SQS)! 🚀 Let's talk about Amazon Simple Queue Service (SQS) and why it's a must-have for any modern application: SQS ensures your messages are delivered and processed, even if parts of your system are down. The service handles any volume of messages, from a few per day to millions per second, and helps you build robust, scalable systems by decoupling application components. This means your services can work independently and efficiently while encrypting your data in transit and at rest, keeping your information secure. Key Features and Benefits: ✅ Standard and FIFO Queues: Offers both Standard (high throughput) and FIFO (First-In-First-Out) queues to meet different application needs. ✅ Dead-Letter Queues: Automatically handles messages that can't be processed successfully, allowing you to analyze and troubleshoot issues. ✅ Message Attributes: Attach custom metadata to your messages, providing more context and flexibility. ✅ Visibility Timeout: Temporarily hide messages from other consumers while being processed, ensuring they aren't processed multiple times. ✅ Long Polling: Reduce costs and increase efficiency by retrieving messages as soon as they become available. ✅ Message Retention: Store messages for up to 14 days, ensuring they are available until processed successfully. ✅ Batch Operations: Send, receive, and delete messages in batches, reducing network latency and improving throughput. Amazon SQS is perfect for distributed systems, microservices, and serverless applications. If you want to enhance your system's reliability and scalability, SQS is the way to go! #AmazonSQS #CloudComputing #MessagingService #Scalability #TechHighlight
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Did you know that Amazon SQS handles over 100 million messages per second at peak times? But we didn't stop there! We've been hard at work optimizing this essential service. Here's a sneak peek into how we've reduced latency, increased capacity, and saved energy: 🌟 Optimized Connections: We replaced one-per-request connections with a new binary framing protocol that multiplexes requests across a single connection. ⚡ 🌟 Enhanced Performance: The new protocol has shaved off 11% of dataplane latency on average and 17.4% at the P90 mark. 🚀 🌟 Increased Capacity: Our SQS fleet can now handle
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🚀 Unlock the Power of Decoupling with Amazon SQS! 🚀 Amazon Simple Queue Service (SQS) has been a cornerstone of AWS's offerings for over a decade, providing a fully managed, serverless solution to decouple applications and streamline workflows. Why Amazon SQS? 🌟 Oldest AWS Offering: Over 10 years of reliable service. 🔧 Fully Managed: No servers to manage, just seamless scaling. 📈 High Throughput: Retains up to 10,000 messages per second. 🕒 Message Retention: Default of 4 days, extendable to 14 days. 📚 Unlimited Queue Size: No cap on the number of messages. 🚀 Low Latency: Less than 10 milliseconds on publish and receive. 🏗️ Horizontal Scaling: Consumers share the workload to read messages efficiently. SQS Use Cases: Order Processing: E-commerce platforms can use SQS to handle order transactions, ensuring each step (order received, payment processed, inventory checked) is handled asynchronously and reliably. Log Aggregation: Collect logs from various services and process them in a centralized system without overloading your logging infrastructure. Task Queues: Offload long-running background tasks from your main application thread, improving responsiveness and reliability. Decoupling Microservices: Use SQS to ensure your microservices communicate asynchronously, improving fault tolerance and scalability. Batch Processing: Queue up tasks for batch processing, allowing for more efficient resource utilization. Pricing: Amazon SQS offers a pay-as-you-go pricing model: Standard Queue: $0.40 per million requests after the first million free requests each month. FIFO Queue: $0.50 per million requests after the first million free requests each month. Additional Charges: Based on the data transferred out of Amazon SQS. Real-Time Benefits: Reliability: Ensure message delivery with multiple availability zones. Scalability: Handle traffic spikes without downtime or performance degradation. Cost-Effectiveness: Pay only for what you use, with no upfront costs or long-term commitments. Whether you're an enterprise managing complex workflows or a startup looking to build scalable, resilient applications, Amazon SQS can help you achieve your goals. Get Started with Amazon SQS Today and Supercharge Your Application Architecture! #AWS #SQS #CloudComputing #Decoupling #Microservices #Scalability #Serverless #DataEngineering
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Amazon Bedrock is a fascinating topic. Bedrock is Amazon's proprietary, cloud-based platform that powers its e-commerce operations. Here's a brief overview: • Cloud Infrastructure : Bedrock is built on Amazon Web Services (AWS), providing scalability, reliability, and security. • Microservices Architecture : Bedrock uses a microservices-based design, allowing for flexibility, modularity, and easier maintenance. • Event-Driven Programming : Bedrock employs event-driven programming, enabling real-time processing and efficient handling of large volumes of data. • Data Analytics : Bedrock integrates with various data analytics tools, providing insights into customer behavior, sales trends, and operational performance. #Amazon #Bedrock #Alexashopping #Corporatelife
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Amazon Aurora Serverless v2 supports scaling to zero capacity now. If you have used this in the past you maybe thought it might of, but it didnt, even though it was serverless so likely caused some cost for some people or some frustrations, but its now here! I know it will save me a bit of money in some accounts, so thanks :-) Theres also been a nice addition to #FCS for #amazonConnect now supporting new languages which I know could help adoption in some of our European customers. New languages now supported include: Canadian French, Chinese (Simplified and Traditional), French, German, Italian, Japanese, Korean, Portuguese (Brazilian), and Spanish. Connect also enhanced its reporting Dashboards further today alongside other enhancements this week, with ability to now create custom dashboards Now, you can further customise these dashboards by changing widgets to create the view that best fits your specific business need. For example, if you want to monitor self-service, queue, and agent performance, you can add all three types of widgets to your dashboard to have a single end to end view of contact center performance.
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Predictive Scaling is a good use of Machine Learning. Hopefully we are about to see the gimmicky ✨ disappear in favour of actually useful uses of AI, such as tracking historical patterns if traffic to predict peak and throughs
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So, this is pretty cool. Amazon ECS has just released the ability to do predictive scaling. Predictive Scaling proactively increases the desired task count based on historical patterns. This helps improve availability and responsiveness for your applications, while also enabling cost savings by needing less over-provisioning. Additionally, you can use Predictive Scaling alongside your existing auto scaling policies, such as target tracking or step scaling, to scale based on both real-time and historic patterns. https://lnkd.in/grCWyMar
Optimize compute resources on Amazon ECS with Predictive Scaling | Amazon Web Services
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𝐒𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐢𝐧𝐠 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐧𝐝 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐢𝐧 𝐀𝐦𝐚𝐳𝐨𝐧 𝐄𝐊𝐒 𝐰𝐢𝐭𝐡 𝐅𝐥𝐮𝐞𝐧𝐭𝐝 𝐚𝐧𝐝 𝐂𝐥𝐨𝐮𝐝𝐖𝐚𝐭𝐜𝐡 𝐀𝐠𝐞𝐧𝐭 📈 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐜𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐠𝐮𝐢𝐝𝐞, 𝐈 𝐜𝐨𝐯𝐞𝐫: • 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐅𝐥𝐮𝐞𝐧𝐭𝐝 𝐚𝐧𝐝 𝐂𝐥𝐨𝐮𝐝𝐖𝐚𝐭𝐜𝐡 𝐀𝐠𝐞𝐧𝐭: Learn why both tools are essential for efficient log and metric management in Amazon EKS. • 𝐒𝐭𝐞𝐩-𝐛𝐲-𝐒𝐭𝐞𝐩 𝐒𝐞𝐭𝐮𝐩: Detailed instructions on deploying Fluentd and CloudWatch Agent on your EKS cluster. • 𝐂𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐚𝐭𝐢𝐨𝐧 𝐓𝐢𝐩𝐬: Customize Fluentd for log collection and configure CloudWatch Agent for metrics and container insights. • 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐚𝐧𝐝 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: Explore the advantages of centralized monitoring and real-time insights. 🚀 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: • Centralized monitoring • Real-time insights • Scalability and flexibility 𝐂𝐡𝐞𝐜𝐤 𝐨𝐮𝐭 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐛𝐥𝐨𝐠 𝐭𝐨 𝐬𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐞 𝐲𝐨𝐮𝐫 𝐄𝐊𝐒 𝐥𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐧𝐝 𝐦𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐬𝐞𝐭𝐮𝐩! [ https://lnkd.in/gr93g8s5 ]
Streamlining Logging and Monitoring in Amazon EKS with Fluentd and CloudWatch Agent
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Exploring Amazon Aurora! We are excited to share our latest video on Amazon Aurora, a powerful database solution that is transforming data management. In this video, we delve into its key features, advantages, performance, scalability, data security, and reliability. Learn how Amazon Aurora seamlessly integrates with AWS services and why it's a game-changer for modern database needs. Watch now to enhance your database management knowledge! #AmazonAurora #AWS #DatabaseManagement #CloudComputing #TechSkills #ProfessionalDevelopment
Amazon Aurora
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Optimizing Amazon Simple Queue Service (SQS) for speed and scale, by Jeff Barr "After carefully considering several long-term solutions, the Amazon SQS team invented a new, proprietary binary framing protocol between the customer front-end and storage back-end. The protocol multiplexes multiple requests and responses across a single connection, using 128-bit IDs and checksumming to prevent crosstalk. [...] The new protocol was put into production earlier this year and has processed 744.9 trillion requests as I write this. The scalability cliff has been eliminated and we are already looking for ways to put this new protocol to work in other ways. Performance-wise, the new protocol has reduced dataplane latency by 11% on average, and by 17.4% at the P90 mark. In addition to making SQS itself more performant, this change benefits services that build on SQS as well. For example, messages sent through Amazon Simple Notification Service (Amazon SNS) now spend 10% less time “inside” before being delivered. Finally, due to the protocol change, the existing fleet of SQS hosts (a mix of X86 and Graviton-powered instances) can now handle 17.8% more requests than before." #AWS #SQS
Optimizing Amazon Simple Queue Service (SQS) for speed and scale | Amazon Web Services
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Got some exciting news for anyone running containerised applications on Amazon EKS! AWS just launched Split Cost Allocation Data for Amazon EKS, bringing much-needed granular cost visibility to your Kubernetes deployments. This means we can finally say goodbye to cost allocation mysteries and hello to clear, pod-level insights into compute and memory utilization. This is a game-changer especially for: - Cost Optimization: Identify underutilized resources and optimize cluster configurations to squeeze every penny out of your EKS investment. No more wondering which team is secretly running that rogue compute-hungry pod! - Chargeback & Billing: Allocate costs accurately to individual business units or teams based on their actual Kubernetes application usage. Transparency is key, and Split Cost Allocation Data provides the data to achieve it. Split Cost Allocation Data integrates seamlessly with AWS Cost and Usage Reports (CUR), so you'll have all your cost insights in one place. Enabling it is simple and takes just a few clicks. Within 24 hours, you'll be wielding the power of granular cost visibility across your EKS clusters. Mohammad Wasim Amit Patil Sandeep Sharma Rethesh Nair "ren" Rudraksh Khandelwal Phani Kishore Lanka Naveen Sharma #thriveatps #amazon #eks #AWS #cloudarchitecture #costoptimization #devops
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Day 10 of Covering AWS Services In distributed systems, handling asynchronous communication is crucial. Amazon Simple Queue Service (SQS) is a fully managed, scalable solution that simplifies message queuing, enabling decoupled architecture that enhances reliability, efficiency, and scalability. Here’s why SQS is essential for modern applications: 1. Decoupling Services for Scalability With Amazon SQS, services can send and receive messages independently, leading to flexible scaling without impacting other parts of the application. Example: An e-commerce platform can queue order processing tasks, allowing the backend to handle high request volumes seamlessly, even during peak times. 2. Reliable Message Delivery Amazon SQS guarantees at-least-once delivery of messages, ensuring your application doesn’t miss important tasks. You can set the message retention period, allowing you to control when messages expire. Example: A finance app can queue transaction logs in SQS, making sure each transaction is captured reliably and ready for processing without delay. 3. Scaling Made Easy with Elasticity SQS scales automatically to handle any increase in message volume, adapting seamlessly as your application demands grow. Example: A streaming service can queue processing requests for video uploads, automatically scaling message handling as users upload more content. 4. Secure Message Processing With encryption and fine-grained access controls, SQS keeps your messages secure, from end-to-end encryption to ensuring only authorized services and users can access specific queues. Example: A healthcare system can securely queue patient data for processing, ensuring compliance with HIPAA while preventing unauthorized access. 5. Flexible Queue Options: Standard and FIFO Choose Standard Queue for high throughput or FIFO Queue for exact message order and no duplicates. This flexibility meets a variety of use cases, from batch processing to strict order processing. Example: A bank can use FIFO queues to process customer requests in order, ensuring actions happen in the correct sequence. Enhance Application Performance and Reliability with Amazon SQS From decoupling services to secure, reliable message handling, Amazon SQS is foundational to scalable, resilient applications. #AWS #AmazonSQS #MessageQueue #Scalability #CloudComputing #AsynchronousProcessing #Decoupling #Reliability #DistributedSystems #DataProcessing
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