Islam Hassan

𝐎𝐜𝐭𝐨𝐛𝐞𝐫 𝐜𝐲𝐛𝐞𝐫𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐰𝐚𝐫𝐞𝐧𝐞𝐬𝐬 𝐦𝐨𝐧𝐭𝐡 💃 💃 . 𝐃𝐚𝐲24: 𝐀𝐏𝐈 𝐆𝐚𝐭𝐞𝐰𝐚𝐲 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲. What Is an API gateway? An API gateway is a middleware component mediating the requests between APIs and various services. A key function of API gateways is to improve the security of APIs and the data they provide. API gateways also perform additional functions supporting API workflows, including rate-limiting, authentication, and analytics, many of which can also contribute to your API security posture. 𝐓𝐡𝐞 𝐀𝐏𝐈 𝐠𝐚𝐭𝐞𝐰𝐚𝐲'𝐬 𝐫𝐨𝐥𝐞 𝐢𝐧 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 🔐 Act as a proxy point to the control APIs inline. 🔐 Authenticate the identity of all API requests by validating credentials, ID tokens, and more authentication methods. 🔐 Determine the traffic allowed to reach the back end via the API. 🔐 Use rate-limiting and throttling to measure traffic passing through each API. 🔐 Enforce security governance by implementing runtime policies and logging all API transactions. 🔐 Provide an added layer of security for back end services powering APIs. 𝐀𝐏𝐈 𝐠𝐚𝐭𝐞𝐰𝐚𝐲 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐛𝐞𝐬𝐭 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 🔐 Use HTTPS Communication 🔐 Use a Centralized Authentication Server 🔐 Limit Requests 🔐 Implement Monitoring and Analytics 🔐 Leverage Serverless Functions 🔐 Implement API-led Connectivity 🔐 Manage Deprecated APIs #octobercybersecurityawarenessmonth

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🚀 𝐑𝐞𝐚𝐝 𝐭𝐡𝐢𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐟𝐚𝐜𝐢𝐧𝐠 𝐀𝐏𝐈 𝐋𝐚𝐭𝐞𝐧𝐜𝐲 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐢𝐧 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 🚀 . . . 🌟 When migrating a monolithic system to microservices architecture for a leading bank, we encountered a significant challenge—API latency increased due to the multiple internal service calls specially the Login API call which increased from 600ms to around 900ms. 🎯 Our primary goal was to reduce the API latency to ensure that the system remained performant and at the same time user experience was not compromised. This required identifying the sources of latency and implementing effective solutions to address them. ⚙️ Some of the key strategies we adopted to identify and tackle this issue: 🔍 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐓𝐫𝐚𝐜𝐢𝐧𝐠: Used advanced capabilities of AppDynamics for distributed tracing to pinpoint latency bottlenecks among multi services calls. ⚡𝐀𝐮𝐭𝐨𝐬𝐜𝐚𝐥𝐢𝐧𝐠: Implemented autoscaling mechanisms with Kubernetes for the internal microservices causing API bottlenecks. 🔄 𝐀𝐬𝐲𝐧𝐜𝐡𝐫𝐨𝐧𝐨𝐮𝐬 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Leveraged Kafka for asynchronous messaging, decoupling services and minimizing synchronous call dependencies. 🗄️ 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐂𝐚𝐜𝐡𝐢𝐧𝐠: Utilized Redis to cache expensive API call results, reducing load and speeding up response times. 🛡️ 𝐄𝐝𝐠𝐞 𝐂𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠: Deploying microservices closer to the end-users, through edge computing or content delivery networks (CDNs), can reduce network latency and improve response times. 🔗 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐑𝐞𝐪𝐮𝐞𝐬𝐭𝐬: Parallel API requests using Reactive Spring Webflux, wherever possible, can reduce the overhead of multiple synchronous individual requests and improve overall performance. 🏆 By employing these solutions, we successfully reduced API latency by 22%, improved system scalability, and enhanced overall performance. ⬆ Our proactive approach not only addressed the immediate challenge but also laid the foundation for scalable and high-performing microservices in the future. 🚀 Migrating to a microservices architecture presents unique challenges, but with the right strategies and tools, it is possible to overcome increased API latency and achieve a robust, high-performing system. Curious to know what strategies do you apply to your projects for these challenges. Let's connect and discuss! 🔗✨ #Microservices #API #CloudMigration #BackendEngineering #PerformanceOptimization

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🔄 𝗥𝗮𝗯𝗯𝗶𝘁𝗠𝗤 𝘃𝘀. 𝗞𝗮𝗳𝗸𝗮 𝘃𝘀. 𝗔𝗰𝘁𝗶𝘃𝗲𝗠𝗤: 𝗞𝗲𝘆 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗳𝗼𝗿 𝗔𝘀𝘆𝗻𝗰𝗵𝗿𝗼𝗻𝗼𝘂𝘀 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 1. 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 & 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Kafka excels in high throughput and horizontal scalability, ideal for scenarios like real-time analytics and event streaming in microservices architectures. For example, LinkedIn processes over 1 trillion messages per day with Kafka. While RabbitMQ and ActiveMQ are robust, Kafka generally handles larger data volumes more efficiently. 2. 𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝘆: RabbitMQ and ActiveMQ support message prioritization, making them suitable for use cases like task scheduling where high-priority tasks need to be processed first. For instance, in an order processing system, orders marked as 'urgent' can be prioritized. Kafka, however, doesn’t natively support this feature. 3. 𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗢𝗿𝗱𝗲𝗿𝗶𝗻𝗴: Kafka ensures message ordering within a partition, making it ideal for use cases like tracking user activities. However, it doesn’t guarantee order across partitions. RabbitMQ and ActiveMQ guarantee ordering within queues or topics, making them better suited for scenarios requiring strict sequential processing. 4. 𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹: RabbitMQ’s queue-based AMQP model is great for traditional messaging patterns, like RPC calls in microservices. Kafka’s distributed log-based model is more suitable for event sourcing or log aggregation. ActiveMQ’s JMS model is often used in legacy systems requiring transactional messaging. 5. 𝗗𝘂𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Kafka’s log replication ensures that no messages are lost, even during failures, which is crucial for financial transactions. RabbitMQ and ActiveMQ offer configurable durability options, making them adaptable to different levels of fault tolerance based on the use case. 6. 𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Kafka’s built-in partition replication offers high availability for distributed systems. For example, a fault-tolerant payment processing system can use Kafka’s replication to ensure no transaction data is lost. RabbitMQ uses Mirrored Queues for replication, suitable for systems requiring high availability but with less complex requirements. ActiveMQ’s Primary-Replica mechanism works well in smaller-scale applications needing basic replication. 7. 𝗦𝘁𝗿𝗲𝗮𝗺 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Kafka’s native stream processing through Kafka Streams is perfect for real-time data transformations, like monitoring user behavior in an e-commerce application. RabbitMQ provides basic stream processing, and ActiveMQ relies on third-party libraries, making it less ideal for complex stream processing tasks. Choosing the right message broker depends on your specific use case. What’s your preferred messaging solution? 🛠️ #kafka #rabbitmq #activemq #systemdesign #interviewtips #coding #distributedmessaging

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As a former architect .. I find system designing and architecture in software world very interesting and challenging. A nice path to consider. #design #architecture #software #systems

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𝗢𝗔𝘂𝘁𝗵 𝟮.𝟬 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 𝘄𝗶𝘁𝗵 𝘀𝗶𝗺𝗽𝗹𝗲 𝘁𝗲𝗿𝗺𝘀. OAuth 2.0 is an authorization framework that enables applications to access a user’s data on another service (like Facebook or GitHub) without sharing the user’s password. It’s essentially a digital handshake between the app, service, and user, with everyone agreeing on what is shared. Now that we’ve covered what it is, let’s dive into how it works. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗴𝗲𝗻𝗲𝗿𝗮𝗹𝗹𝘆 𝗳𝗼𝗹𝗹𝗼𝘄𝘀 𝟲 𝘀𝘁𝗲𝗽𝘀 𝘄𝗶𝘁𝗵 𝟰 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝘁𝘆𝗽𝗶𝗰𝗮𝗹𝗹𝘆 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱: 🔸 Client (app wanting access) 🔸 Resource owner (user) 🔸 Authorization server 🔸 Resource server To understand the process, let’s take a look at how a game would connect to a player’s Facebook account. 𝗦𝘁𝗲𝗽 𝟭) 𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗮𝗰𝗰𝗲𝘀𝘀: Within the game (client), the player (user) clicks on a “connect with Facebook” button to link their profile and find friends. 𝗦𝘁𝗲𝗽 𝟮) 𝗥𝗲𝗱𝗶𝗿𝗲𝗰𝘁 𝘁𝗼 𝘀𝗲𝗿𝘃𝗶𝗰𝗲: The game redirects the player to Facebook’s (service’s) login page. 𝗦𝘁𝗲𝗽 𝟯) 𝗣𝗲𝗿𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗿𝗲𝗾𝘂𝗲𝘀𝘁: After logging in, the data that the game is requesting access to will be shown to the player which they can either allow or deny. 𝗦𝘁𝗲𝗽 𝟰) 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝗱𝗲: If the player gives their approval, Facebook redirects the player back to the game with an authorization code (from authorization server). The code is a temporary credential that proves the player’s consent. 𝗦𝘁𝗲𝗽 𝟱) 𝗘𝘅𝗰𝗵𝗮𝗻𝗴𝗲 𝗰𝗼𝗱𝗲 𝗳𝗼𝗿 𝘁𝗼𝗸𝗲𝗻: The game now sends the authorization code along with its own identification to Facebook’s server in the background. Facebook identifies the authorization code and the game’s identity and returns an access token. 𝗦𝘁𝗲𝗽 𝟲) 𝗨𝘀𝗲 𝘁𝗵𝗲 𝘁𝗼𝗸𝗲𝗻: The game can now use the access token to request the agreed-upon data from Facebook (from the resource server), like the player's friends list. In this process, the player’s Facebook credentials were never shared, but the game was able to access the agreed-upon player data from Facebook. This is what OAuth 2.0 facilitates; allowing third-party applications to access data from services in a secure manner without sharing credentials. You can learn more about OAuth 2.0 here: https://lnkd.in/gZ2AWAFi ~~ A big thank you to our partner Postman who keeps our content free to the community. Wish building APIs was simpler and more organized? Postman Collections does just that. Check it out: https://lnkd.in/g3YCnt8s

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🚀 Excited to Share: Software Architecture - System Design Guide for Java & Spring Developers (Draft Version) 🚀 I’m thrilled to share the draft version of my guide, "Software Architecture: System Design Guide for Java & Spring Developers." written by Dr. BADR EL KHALYLY . 📘 This guide is a culmination of years of hands-on experience in the field, focusing on the key principles of backend architecture, microservice patterns, database architecture, security, and more. It’s designed to help developers and architects navigate the complex landscape of modern software design, particularly within the Java and Spring ecosystem. In this draft version, I’ve included insights on: Backend Architecture: Strategies for designing robust and scalable systems. Microservices Patterns: Best practices for building and deploying microservices. Database Architecture: How to structure and optimize your databases. Security: Essential security measures every architect should consider. This is just the beginning, and I’m continuously working to improve and expand this guide. Your feedback would be incredibly valuable to refine this content and make it even more impactful. 💡 Download the draft version here Thank you for your support, and I look forward to your thoughts and insights! #SoftwareArchitecture #Java #Spring #SystemDesign #Microservices #Security #DatabaseArchitecture #DevOps #CloudComputing

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5 Useful Tips When Working with RESTful APIs. |---------------------------------------------------------------------------| 1. Understand HTTP Methods:   - Learn the primary HTTP methods (GET, POST, PUT, DELETE, PATCH) and their appropriate uses to interact with RESTful APIs effectively. 2. Use Descriptive URIs:   - Design your endpoints with clear, descriptive, and intuitive URIs. For example, `/users/{id}` is better than `/getUserById`. 3. Handle Errors Gracefully:   - Implement proper error handling and use standard HTTP status codes (e.g., 404 for not found, 500 for server error) to convey issues clearly. 4. Utilize Versioning:   - Incorporate API versioning (e.g., `/v1/users`) to manage changes and updates without breaking existing clients. 5. Secure Your API:   - Use authentication (like OAuth) and encryption (HTTPS) to protect your API and data from unauthorized access and breaches. ---------------------------------------------- Websites to Learn about RESTful APIs --------------------------------------------- 1. MDN Web Docs   - Provides comprehensive documentation on web technologies, including RESTful APIs.   - Website: [MDN Web Docs](https://lnkd.in/d7-FW3ax) 2. RESTful API Tutorial   - Offers a beginner-friendly tutorial on RESTful APIs.   - Website: [RESTful API Tutorial](https://restfulapi.net/) 3. Postman Learning Center   - Provides tutorials and guides on using Postman for testing and developing APIs, including RESTful APIs.   - Website: [Postman Learning Center](https://lnkd.in/dAWJJhn7) 4. TutorialsPoint   - Offers a variety of tutorials on RESTful API concepts and implementation.   - Website: [TutorialsPoint RESTful Tutorial](https://lnkd.in/dAfpWNkx) 5. Swagger   - Offers tools and resources for designing, building, and documenting RESTful APIs.   - Website: [Swagger](https://swagger.io/) These resources provide both practical tips and educational materials to help you effectively design, develop, and manage RESTful APIs.

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Explore the differences between Monolithic Architecture and Microservices Architecture in software development. 🖥️ 🔹 Monolithic Architecture: - Built as a single, self-contained unit with the UI, logic, and database in one codebase. - Simpler setup and deployment for smaller projects. - Potentially faster performance with less component communication. - Challenges in scaling the entire application even for specific parts. - Limited technology choices and maintenance difficulties due to codebase changes. 🔹 Microservices Architecture: - Application broken into smaller, independent services for specific functions. - Highly scalable with individual services scaled independently. - Easier maintenance as changes are isolated to specific services. - Offers technology freedom with varied technology choices. - Increased complexity in development, deployment, and slight performance overhead. - Debugging challenges due to issues spanning multiple services. Understanding these architectures can help navigate software development strategies efficiently. 💻 #SoftwareArchitecture #MonolithicVsMicroservices #DevOps

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What are the steps to design a database that follows the document model? What are the similarities and differences, compared to designing a relational database?

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Things you must have in your company to derisk your operation and I can solve for you: 1- A good control version. 2- An onboarding process for new devs. 3- A disaster 4ecovery plan in plan. 4- The understanding of your code.

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𝗘𝗣 –43- 𝗝𝘂𝘀𝘁 𝗶𝗻 𝗧𝗶𝗺𝗲 – 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀 𝘁𝗼 𝗸𝗲𝗲𝗽 𝗵𝗮𝗻𝗱𝘆 𝗳𝗼𝗿 𝗱𝗮𝘆-𝘁𝗼-𝗱𝗮𝘆 𝗶𝗻 𝘁𝗵𝗲 𝘁𝗲𝗰𝗵 𝗹𝗶𝗳𝗲    Template Pattern  Use Case: Defining the structure of an algorithm, allowing subclasses to redefine certain steps without changing the algorithm's structure. Example: In a game, the steps for "start game," "play turn," and "end game" are fixed, but specific game logic is implemented in subclasses (chess vs. checkers). Servant Pattern Use Case: Centralizing common functionality and making it reusable across multiple classes.  Example: A reusable "service" class that manages database connections for multiple different classes, handling all interactions with the database. These behavioral patterns help manage complex interactions between objects, making systems more maintainable and flexible. #designpattern  #behavioral  #objectscommunication 

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Card Generator in C ⌨️ This is a C-based card generator that reads names from a text file and generates a card (image) for each name using the Cairo library for rendering. https://lnkd.in/d639PGPP #git #github #c #image_generator #card #card_generator

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🆓 كل عام وأنتم بخير ، كوبونات مجانيه ❤ ً المحتوي المخطط لاعداده ان شاء الله هو كالتالي ✅ Solve the common interview algorithm problems for big tech companies like  Facebook, Amazon, and Google ✅ Master the common patterns and techniques to solve these problems ✅ Practice your Data structures and algorithms in depth ✅ Prepare for your next coding interview ✅ Improve your skills as a software engineer ✅ Master Breadth-First Search Algorithm for Binary level traversal ✅ Solve popular problems on Array Data Structure ✅ Master Sliding Window Technique ✅ Master Depth First Search for Binary Tree Traversal ✅ Master XOR Bit manipulation technique ✅ Master Dynamic Programming ✅ Master Two Pointers Techniques ✅ Master Coding Interview Patterns ✅ Master Breadth-First Search Algorithm for Binary level traversal Please Rate and write your honest review of the course 😍

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### Building a Robust RabbitMQ Cluster for High Availability In today's distributed systems, the reliability and availability of your messaging infrastructure are crucial. RabbitMQ, a powerful message broker, offers robust clustering capabilities to ensure your messages are always delivered, even in the face of failures. Here’s an overview of why and how to set up a RabbitMQ cluster. #### Why Choose RabbitMQ Clustering? A RabbitMQ cluster consists of interconnected nodes that work together to distribute the message load and provide redundancy. The key benefits include: 1. **Fault Tolerance**: If one node fails, the remaining nodes continue processing messages, ensuring uninterrupted service. 2. **Scalability**: Easily add more nodes to the cluster to handle increased load, allowing your application to scale seamlessly. 3. **Centralized Management**: Manage all nodes from a single point, simplifying operations and maintenance. #### Steps to Set Up a RabbitMQ Cluster 1. **Node Installation**: Ensure RabbitMQ is installed on each machine that will be part of the cluster. 2. **Network Configuration**: Configure nodes to communicate over the network without firewall issues. 3. **Joining Nodes**: Designate an initial node and join additional nodes to this cluster. 4. **Queue Mirroring**: Configure queues to be mirrored across multiple nodes for high availability, ensuring data integrity in case of a node failure. #### Best Practices for RabbitMQ Clusters 1. **Monitoring and Alerts**: Utilize RabbitMQ’s management tools and plugins to monitor cluster health and performance. Set up alerts for anomalies or failures. 2. **Load Balancing**: Implement load balancers to evenly distribute traffic across nodes, avoiding any single point of failure. 3. **Regular Backups**: Regularly back up your configuration and queue definitions for disaster recovery. 4. **Testing Failover**: Regularly test the cluster’s failover capabilities to ensure it behaves as expected during a node failure. #### Benefits of a Well-Configured RabbitMQ Cluster - **Resilience**: Multiple nodes ensure your message broker can withstand failures without impacting performance. - **Performance**: Load distribution across nodes improves performance and reduces latency. - **Scalability**: Easily scale infrastructure by adding or removing nodes based on demand. Setting up a RabbitMQ cluster enables you to build a highly available, scalable, and resilient messaging system, supporting the demands of modern applications. This setup is ideal for applications requiring reliable message delivery and minimal downtime. For those interested in learning more or needing assistance with RabbitMQ clustering, feel free to reach out. Let’s connect and discuss how we can build more resilient systems together.🚀 #Java #RabbitMQ #Cluster #HighAvailability #Scalability #DistributedSystems #MessageBroker #TechTips #Microservices #Resilience #MessagingInfrastructure

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𝐅𝐥𝐚𝐬𝐤 𝐯𝐬. 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: 𝐊𝐞𝐲 𝐂𝐨𝐦𝐩𝐚𝐫𝐢𝐬𝐨𝐧 𝐏𝐨𝐢𝐧𝐭𝐬 𝘏𝘦𝘳𝘦’𝘴 𝘢 𝘲𝘶𝘪𝘤𝘬 𝘤𝘰𝘮𝘱𝘢𝘳𝘪𝘴𝘰𝘯 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘵𝘸𝘰 𝘢𝘸𝘦𝘴𝘰𝘮𝘦 𝘧𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬𝘴: -> 𝑷𝒆𝒓𝒇𝒐𝒓𝒎𝒂𝒏𝒄𝒆 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: High performance, great for high-concurrency. 𝐅𝐥𝐚𝐬𝐤: Slower under high load, synchronous. -> 𝑬𝒂𝒔𝒆 𝒐𝒇 𝑼𝒔𝒆 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: Modern, type hints, automatic data validation. 𝐅𝐥𝐚𝐬𝐤: Simple, flexible, great for quick prototypes. -> 𝑫𝒂𝒕𝒂𝒃𝒂𝒔𝒆 𝑺𝒖𝒑𝒑𝒐𝒓𝒕 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: Supports asynchronous databases. 𝐅𝐥𝐚𝐬𝐤: Extensive support via plugins, synchronous by default. -> 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 𝒂𝒏𝒅 𝑬𝒄𝒐𝒔𝒚𝒔𝒕𝒆𝒎 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: Growing community, rich ecosystem. 𝐅𝐥𝐚𝐬𝐤: Established community, vast number of extensions. -> 𝑫𝒐𝒄𝒖𝒎𝒆𝒏𝒕𝒂𝒕𝒊𝒐𝒏 𝒂𝒏𝒅 𝑳𝒆𝒂𝒓𝒏𝒊𝒏𝒈 𝑪𝒖𝒓𝒗𝒆 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: Excellent docs, steeper learning curve. 𝐅𝐥𝐚𝐬𝐤: Well-documented, beginner-friendly. -> 𝑫𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 𝑺𝒑𝒆𝒆𝒅 𝐅𝐚𝐬𝐭𝐀𝐏𝐈: Faster for complex apps with built-in features. 𝐅𝐥𝐚𝐬𝐤: Faster for simple apps, needs more setup for complexity. --- 👋 Hi it's sam , If you liked this, connect with me on LinkedIn for daily insights on #webdevelopment #fastapi #apis #flask #python #appdevelopment #aiapps #guide

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A good tip. I used IIS for many years before .NET Core and migrated to Kestrel because it is much lighter and more efficient for multiplatform .NET applications (Windows, Linux, MacOS). Take advantage of the full potential in cloudnative microservice development using the Devprime platform and its accelerators. Follow: Devprime Try it free: https://devprime.io #dotnet #devprime #kestrel #microservices #startup #startupfounder #startupinvestment #startupfunding #csharp #visualstudio #developer #software #cloud #cloudnative #azure #aws #gcp #aks #gke #eks

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Here are some key steps to implement the Azure Well-Architected Framework into existing enterprise-level applications: ## Assess Current Architecture - Conduct a thorough assessment of the existing application architecture against the five pillars of the Well-Architected Framework: - Cost Optimization - Operational Excellence - Performance Efficiency - Reliability - Security - Identify gaps and areas for improvement in each pillar. - Prioritize the pillars based on business impact and risk. ## Develop an Implementation Plan - Create a phased plan to address the gaps identified in the assessment. - Prioritize quick wins and high-impact improvements. - Allocate resources and budget for the implementation. - Establish KPIs and success criteria for each pillar. ## Optimize Costs - Right-size virtual machines and other resources based on actual usage. - Utilize reserved instances, Azure Hybrid Benefit, and other cost optimization features. - Implement cost monitoring and alerts to proactively manage costs. - Optimize data storage tiers based on access patterns. ## Enhance Operational Excellence - Implement Infrastructure as Code (IaC) for consistent and repeatable deployments. - Automate manual tasks and processes using Azure Automation, Logic Apps, etc. - Implement monitoring and logging using Azure Monitor, Application Insights, etc. - Establish incident response and disaster recovery plans. ## Improve Performance Efficiency - Select the right Azure services and resources based on workload requirements. - Implement caching, content delivery networks (CDNs), and other performance optimization techniques. - Continuously monitor and optimize performance bottlenecks. - Scale resources up or out based on demand. ## Ensure Reliability - Implement high availability features like load balancing, health probes, etc. - Implement data redundancy and backup strategies. - Test disaster recovery plans regularly. - Implement circuit breakers, retries, and other resilience patterns. ## Enhance Security - Implement role-based access control (RBAC) and just-in-time access. - Implement network security features like network security groups, firewalls, etc. - Implement data encryption at rest and in transit. - Implement vulnerability scanning and penetration testing. ## Continuously Optimize and Improve - Regularly review and assess the application architecture against the Well-Architected Framework. - Implement a process for continuous improvement and optimization. - Leverage Azure Advisor and Well-Architected Review tools for ongoing guidance and recommendations. - Collaborate with Azure experts and the community for best practices and lessons learned. By following these steps and continuously optimizing the application architecture based on the Well-Architected Framework, enterprises can enhance the reliability, security, performance, and cost-effectiveness of their existing applications on Azure.

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Understanding and Addressing Cache System Failures: A Detailed Insight Cache systems are indispensable in modern computing, enabling faster data access and reducing the load on backend systems. However, when not properly managed, they can lead to severe issues that undermine system performance and reliability. Here’s an in-depth look at common cache failures, their causes, and strategies to mitigate them: 1. Thunder Herd Problem What Happens: When a large number of cache keys expire simultaneously, incoming queries bypass the cache and overwhelm the database with requests, potentially causing it to crash. Solutions: Stagger Expiry Times: Add random values to key expiration times to distribute requests evenly over time. Prioritize Core Data: Allow only essential business data to access the database during cache recovery, blocking non-critical requests. Asynchronous Cache Refresh: Preemptively refresh popular keys before expiration to maintain availability. 2. Cache Penetration What Happens: Requests for non-existent keys bypass the cache and hit the database, often due to malicious attacks or poorly structured queries. This burdens both the cache and database. Solutions: Cache Null Values: Store null results for non-existent keys to avoid repeated database hits. Use Bloom Filters: A lightweight, probabilistic structure that checks key existence before hitting the database. Input Validation: Prevent unnecessary queries with proper input sanitization and query optimization.

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