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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou istoWe are often asked to design for high availability, high scalability, and high throughput. What do they mean exactly? The diagram below is a system design cheat sheet with common solutions. 1. High Availability This means we need to ensure a high agreed level of uptime. We often describe the design target as “3 nines” or “4 nines”. “4 nines”, 99.99% uptime, means the service can only be down 8.64 seconds per day. To achieve high availability, we need to design redundancy in the system. There are several ways to do this: - Hot-hot: two instances receive the same input and send the output to the downstream service. In case one side is down, the other side can immediately take over. Since both sides send output to the downstream, the downstream system needs to dedupe. - Hot-warm: two instances receive the same input and only the hot side sends the output to the downstream service. In case the hot side is down, the warm side takes over and starts to send output to the downstream service. - Single-leader cluster: one leader instance receives data from the upstream system and replicates to other replicas. - Leaderless cluster: there is no leader in this type of cluster. Any write will get replicated to other instances. As long as the number of write instances plus the number of read instances are larger than the total number of instances, we should get valid data. 2. High Throughput This means the service needs to handle a high number of requests given a period of time. Commonly used metrics are QPS (query per second) or TPS (transaction per second). To achieve high throughput, we often add caches to the architecture so that the request can return without hitting slower I/O devices like databases or disks. We can also increase the number of threads for computation-intensive tasks. However, adding too many threads can deteriorate the performance. We then need to identify the bottlenecks in the system and increase its throughput. Using asynchronous processing can often effectively isolate heavy-lifting components. 3. High Scalability This means a system can quickly and easily extend to accommodate more volume (horizontal scalability) or more functionalities (vertical scalability). Normally we watch the response time to decide if we need to scale the system. Over to you: Do you have other things to share in your design toolbox? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou istoThe Payments Ecosystem How do fintech startups find new opportunities among so many payment companies? What do PayPal, Stripe, and Square do exactly? Steps 0-1: The cardholder opens an account in the issuing bank and gets the debit/credit card. The merchant registers with ISO (Independent Sales Organization) or MSP (Member Service Provider) for in-store sales. ISO/MSP partners with payment processors to open merchant accounts. Steps 2-5: The acquiring process. The payment gateway accepts the purchase transaction and collects payment information. It is then sent to a payment processor, which uses customer information to collect payments. The acquiring processor sends the transaction to the card network. It also owns and operates the merchant’s account during settlement, which doesn’t happen in real-time. Steps 6-8: The issuing process. The issuing processor talks to the card network on the issuing bank’s behalf. It validates and operates the customer’s account. I’ve listed some companies in different verticals in the diagram. Notice payment companies usually start from one vertical, but later expand to multiple verticals. -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou isto15 Open-Source Projects That Changed the World To come up with the list, we tried to look at the overall impact these projects have created on the industry and related technologies. Also, we’ve focused on projects that have led to a big change in the day-to-day lives of many software developers across the world. Web Development - Node.js: The cross-platform server-side Javascript runtime that brought JS to server-side development - React: The library that became the foundation of many web development frameworks. - Apache HTTP Server: The highly versatile web server loved by enterprises and startups alike. Served as inspiration for many other web servers over the years. Data Management - PostgreSQL: An open-source relational database management system that provided a high-quality alternative to costly systems - Redis: The super versatile data store that can be used a cache, message broker and even general-purpose storage - Elasticsearch: A scale solution to search, analyze and visualize large volumes of data Developer Tools - Git: Free and open-source version control tool that allows developer collaboration across the globe. - VSCode: One of the most popular source code editors in the world - Jupyter Notebook: The web application that lets developers share live code, equations, visualizations and narrative text. Machine Learning & Big Data - Tensorflow: The leading choice to leverage machine learning techniques - Apache Spark: Standard tool for big data processing and analytics platforms - Kafka: Standard platform for building real-time data pipelines and applications. DevOps & Containerization - Docker: The open source solution that allows developers to package and deploy applications in a consistent and portable way. - Kubernetes: The heart of Cloud-Native architecture and a platform to manage multiple containers - Linux: The OS that democratized the world of software development. Over to you: Do you agree with the list? What did we miss? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou isto7 must-know strategies to scale your database. 1 - Indexing: Check the query patterns of your application and create the right indexes. 2 - Materialized Views: Pre-compute complex query results and store them for faster access. 3 - Denormalization: Reduce complex joins to improve query performance. 4 - Vertical Scaling Boost your database server by adding more CPU, RAM, or storage. 5 - Caching Store frequently accessed data in a faster storage layer to reduce database load. 6 - Replication Create replicas of your primary database on different servers for scaling the reads. 7 - Sharding Split your database tables into smaller pieces and spread them across servers. Used for scaling the writes as well as the reads. Over to you: What other strategies do you use for scaling your databases? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior compartilhou istoVocê é desenvolvedor front-end, tem inglês fluente e quer trabalhar remoto com projetos super atuais? Dá uma olhada na vaga abaixo. Dúvidas? Fala comigo.Mario Cesar Costa Junior compartilhou istoA Outracoisa* contrata uma pessoa desenvolvedora Front End Senior para trabalho remoto. Requisitos - Inglês fluente - Disponibilidade para reuniões remotas de dailies, planning e testes - Mínimo de 5 anos de experiência em desenvolvimento front-end utilizando ReactJS/NextJS ou similar. Diferenciais - Cuidado especial com detalhes da interface. Tanto na usabilidade como na fidelidade do design. - Capacidade de implementar componentes de interface super customizados. - Experiência em interfaces com transições e animações. Candidatos, favor mandar mensagem para vamos@outracoisa.co
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou istoTop Eventual Consistency Patterns You Must Know Eventual consistency is a data consistency model that ensures that updates to a distributed database are eventually reflected across all nodes. Techniques like async replication help achieve eventual consistency. However, eventual consistency can also result in data inconsistency. Here are 4 patterns that can help you design applications. Pattern#1 - Event-based Eventual Consistency Services emit events and other services listen to these events to update their database instances. This makes services loosely coupled but delays data consistency. Pattern#2 - Background Sync Eventual Consistency In this pattern, a background job makes the data across databases consistent. It results in slower eventual consistency since the background job runs on a specific schedule. Pattern#3 - Saga-based Eventual Consistency Saga is a sequence of local transactions where each transaction updates data with a single service. It is used to manage long-lived transactions that are eventually consistent. Pattern#4 - CQRS-based Eventual Consistency Separate read and write operations into different databases that are eventually consistent. Read and write models can be optimized for specific requirements. Over to you: Which other eventual consistency patterns have you seen? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior publicou istoAlguma recomendação de vaga interessante usando Typescript + Postgres?
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou isto6 API Styles You Should KNOW - GRPC: High-performance RPC framework for distributed systems. - SOAP: Protocol for structured web services with strict XML standards. - GraphQL: Query language for APIs to fetch only needed data. - Webhook: Real-time communication via HTTP POST to trigger actions. - REST: Architectural style using HTTP methods to manipulate resources. - WebSocket: Bidirectional, real-time communication for low-latency applications. 👍🏿 Subscribe to our newsletter - https://bit.ly/3x4j5dT #systemdesign #coding #interviewtips
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Mario Cesar Costa Junior compartilhou istoMario Cesar Costa Junior compartilhou istoWhat do Amazon, Netflix, and Uber have in common? They are extremely good at scaling their system whenever needed. Here are 8 must-know strategies to scale your system. 1 - Stateless Services Design stateless services because they don’t rely on server-specific data and are easier to scale. 2 - Horizontal Scaling Add more servers so that the workload can be shared. 3 - Load Balancing Use a load balancer to distribute incoming requests evenly across multiple servers. 4 - Auto Scaling Implement auto-scaling policies to adjust resources based on real-time traffic. 5 - Caching Use caching to reduce the load on the database and handle repetitive requests at scale. 6 - Database Replication Replicate data across multiple nodes to scale the read operations while improving redundancy. 7 - Database Sharding Distribute data across multiple instances to scale the writes as well as reads. 8 - Async Processing Move time-consuming and resource-intensive tasks to background workers using async processing to scale out new requests. Over to you: Which other strategies have you used? – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/3KCnWXq #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior gostou dissoMario Cesar Costa Junior gostou dissoWe are often asked to design for high availability, high scalability, and high throughput. What do they mean exactly? The diagram below is a system design cheat sheet with common solutions. 1. High Availability This means we need to ensure a high agreed level of uptime. We often describe the design target as “3 nines” or “4 nines”. “4 nines”, 99.99% uptime, means the service can only be down 8.64 seconds per day. To achieve high availability, we need to design redundancy in the system. There are several ways to do this: - Hot-hot: two instances receive the same input and send the output to the downstream service. In case one side is down, the other side can immediately take over. Since both sides send output to the downstream, the downstream system needs to dedupe. - Hot-warm: two instances receive the same input and only the hot side sends the output to the downstream service. In case the hot side is down, the warm side takes over and starts to send output to the downstream service. - Single-leader cluster: one leader instance receives data from the upstream system and replicates to other replicas. - Leaderless cluster: there is no leader in this type of cluster. Any write will get replicated to other instances. As long as the number of write instances plus the number of read instances are larger than the total number of instances, we should get valid data. 2. High Throughput This means the service needs to handle a high number of requests given a period of time. Commonly used metrics are QPS (query per second) or TPS (transaction per second). To achieve high throughput, we often add caches to the architecture so that the request can return without hitting slower I/O devices like databases or disks. We can also increase the number of threads for computation-intensive tasks. However, adding too many threads can deteriorate the performance. We then need to identify the bottlenecks in the system and increase its throughput. Using asynchronous processing can often effectively isolate heavy-lifting components. 3. High Scalability This means a system can quickly and easily extend to accommodate more volume (horizontal scalability) or more functionalities (vertical scalability). Normally we watch the response time to decide if we need to scale the system. Over to you: Do you have other things to share in your design toolbox? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior gostou dissoÉ um orgulho ser a mais nova sócia e C-Level da Vibbra! 2025 o desafio será novo: CSO - Chief Strategy Officer 🩵 Em 2020 decidi mudar de ares na minha carreira. Entendi que precisava ampliar mais meus conhecimentos e conhecer mais sobre o mercado de trabalho. E em outubro, 1 mês depois de tomar essa decisão, tive a oportunidade de conhecer a Vibbra, na época uma "plataforma freelancer", onde pude juntar o que eu tinha de conhecimento como psicóloga, entrando como recrutadora, e aliando a um grande interesse que sempre tive: tecnologia. Foram desafios inimagináveis no caminho: força tarefa, runaway minúsculo, estratégias que não funcionaram. Mas eu sempre soube que tinha jeito de fazer as coisas darem certo, e contando com a confiança que o Leandro Oliveira e a Juliana Nascimento depositaram em mim, pude assumir novos desafios dentro da empresa para contribuir mais. Pude assumir em 2021 a liderança da área de recrutamento e seleção, e em 2023 a liderança do time estratégico, com desafios que iam além do que eu dominava: dados, integrações, ferramentas e processos. E, ainda, o plus: eu pedi para gerir também nosso produto, e hoje sigo também como PO. Os estudos e aprendizados não param. E a evolução é gritante! O mercado de TI não é simples, a concorrência é grande, e cenário de startup quem já passou por uma conhece bem: os sonhos são altíssimos, mas o orçamento não acompanha. Então temos que ser criativos. E se tem uma coisa que esse time tem de sobra é criatividade! É incrível poder trabalhar numa empresa que de fato faz o que se proprõe: respeitar as pessoas. Todos que passam pelo time exaltam a flexibilidade, a sincronia e trabalho em equipe aqui dentro. Tanto que o turnover na Vibbra, em comparação ao mundo de startups, é muito baixo. E sem esse time incrível, a tão esperada virada de chave não poderia ter acontecido. E está acontecendo. 2025 que nos aguarde, porque estamos com tudo. E obrigada novamente pela confiança. Podem ter certeza de que não medirei esforços para continuarmos ganhando espaço e iremos muito além. 🩵Mario Cesar Costa Junior gostou disso4 anos de empresa, muita dedicação e um impacto inegável no nosso negócio. É com grande orgulho que anunciamos nossa mais nova #sócia e C-Level da Vibbra, a Chief Strategy Officer, Fernanda Barcelos 🎉 Em meio às incertezas que marcaram o início da pandemia em 2020, enquanto “gurus”, conselheiros e investidores sugeriam segurar investimentos e esperar, decidimos ir na contramão: #acelerar. E, em um dos primeiros passos dessa jornada audaciosa, fomos buscar as contratações mais desafiadoras de todas: pessoas que pudessem assumir operações críticas para que a Juliana Nascimento e eu pudéssemos focar no #crescimento. Foi fácil? Deu tudo certo de primeira? Claro que não. Erramos, tropeçamos e enfrentamos obstáculos imensos. Mas também acertamos o suficiente para, hoje, sermos uma empresa sólida e lucrativa. E, nesse caminho, algo ficou claro: Alguns desistiram. Mas não ela. Não a Fer. Ela ficou. Persistiu ao nosso lado, mesmo nos momentos mais difíceis. Quando decidimos enfrentar desafios maiores do que nós mesmos. Quando encaramos gigantes sem investimentos ou um longo runway. Quando vimos concorrentes pivotarem e sucumbirem enquanto nós seguíamos firmes. A Fer não apenas sobreviveu ao caos. Ela #prosperou nele. E nos fez prosperar também. • A Fer nos ajudou a crescer: de 700 profissionais na plataforma para 3.500 em um ano e, depois, para 10.000. • A Fer trouxe visão estratégica: implantou uma cultura data-driven do zero e elevou a qualidade de nossas decisões. • A Fer manteve o fator humano: aliando análises precisas à essência da nossa cultura. • E agora, a Fer está nos levando além: otimizando toda a operação da Vibbra com inteligência artificial. Se tudo isso ainda não é motivo suficiente para torná-la nossa sócia e #c-level, talvez seja hora de rever seus conceitos. 😉 Seja bem-vinda novamente, Fer! Agora, como sócia e líder #estratégica. Estamos prontos para continuar essa jornada incrível ao seu lado.
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Mario Cesar Costa Junior gostou dissoMario Cesar Costa Junior gostou dissoHow can Cache Systems go wrong? The diagram below shows 4 typical cases where caches can go wrong and their solutions. 1. Thunder herd problem This happens when a large number of keys in the cache expire at the same time. Then the query requests directly hit the database, which overloads the database. There are two ways to mitigate this issue: one is to avoid setting the same expiry time for the keys, adding a random number in the configuration; the other is to allow only the core business data to hit the database and prevent non-core data to access the database until the cache is back up. 2. Cache penetration This happens when the key doesn’t exist in the cache or the database. The application cannot retrieve relevant data from the database to update the cache. This problem creates a lot of pressure on both the cache and the database. To solve this, there are two suggestions. One is to cache a null value for non-existent keys, avoiding hitting the database. The other is to use a bloom filter to check the key existence first, and if the key doesn’t exist, we can avoid hitting the database. 3. Cache breakdown This is similar to the thunder herd problem. It happens when a hot key expires. A large number of requests hit the database. Since the hot keys take up 80% of the queries, we do not set an expiration time for them. 4. Cache crash This happens when the cache is down and all the requests go to the database. There are two ways to solve this problem. One is to set up a circuit breaker, and when the cache is down, the application services cannot visit the cache or the database. The other is to set up a cluster for the cache to improve cache availability. Over to you: Have you met any of these issues in production? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior gostou dissoMario Cesar Costa Junior gostou disso🎨 Introducing Prompt Canvas — a novel UX for prompt engineering Building LLM applications requires new and dedicated tools for prompt engineering. With Prompt Canvas in LangSmith, you can: • Collaborate with an AI agent to draft, refine, and edit your prompts • Define custom quick actions to standardize prompting strategies used across the org ✍️ Learn more: https://lnkd.in/g4pJB2NH ➡️ Try it out: https://lnkd.in/gQqGyH33
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Mario Cesar Costa Junior gostou dissoMario Cesar Costa Junior gostou dissoThe Payments Ecosystem How do fintech startups find new opportunities among so many payment companies? What do PayPal, Stripe, and Square do exactly? Steps 0-1: The cardholder opens an account in the issuing bank and gets the debit/credit card. The merchant registers with ISO (Independent Sales Organization) or MSP (Member Service Provider) for in-store sales. ISO/MSP partners with payment processors to open merchant accounts. Steps 2-5: The acquiring process. The payment gateway accepts the purchase transaction and collects payment information. It is then sent to a payment processor, which uses customer information to collect payments. The acquiring processor sends the transaction to the card network. It also owns and operates the merchant’s account during settlement, which doesn’t happen in real-time. Steps 6-8: The issuing process. The issuing processor talks to the card network on the issuing bank’s behalf. It validates and operates the customer’s account. I’ve listed some companies in different verticals in the diagram. Notice payment companies usually start from one vertical, but later expand to multiple verticals. -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social #systemdesign #coding #interviewtips .
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Mario Cesar Costa Junior gostou dissoMario Cesar Costa Junior gostou disso✂️Chunking Data for RAG Applications Learn about how to transform your data for retrieval-augmented generation (RAG) applications using different chunking strategies. Covers: recursive splitting, document-specific splitting, and semantic splitting https://lnkd.in/gXubkP6d
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Muhammad Usman Asif
Alexa Translations • 930 seguidores
Avoiding NestJS Performance Bottlenecks NestJS is one of my go-to frameworks for Node.js development. Its dependency injection, modular design, and Angular/Java-like structure make it a great choice for scalable apps. But with all its power, it’s easy to hit performance bottlenecks if we’re not careful. ✅ Upgrade regularly – newer versions of Node.js & NestJS often bring noticeable performance wins. ✅ Use efficient loggers – replace the default logger with nestjs-pino or nest-winston, and remember to use bufferLogs: true at startup. ✅ Be mindful of injection scopes – request-scoped providers can kill performance if overused. AsyncLocalStorage (built into NestJS now) is often a better choice. ✅ Switch to Fastify – NestJS works with Fastify out of the box, and it’s often faster than Express. ✅ Measure first – many bottlenecks come from inefficient DB queries or misuse of third-party libs, not NestJS itself. ⚡ NestJS sacrifices a bit of raw performance to give us a strong developer experience—but with the right setup, you can minimize bottlenecks and still get the best of both worlds. ⚡ Bonus tips: Avoid unnecessary global middlewares/pipes, use lazy loading for serverless, and cache environment variables. 👉 Curious to hear: what’s the biggest performance improvement you’ve made in a NestJS app? #NestJS #NodeJS #BackendDevelopment #Performance #FullStackDevelopment
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Bhaskara Satya Prasad
Genpact • 1 mil seguidores
🚀 Node.js: Still Evolving, Still Powerful Node.js continues to be a top choice for building fast, scalable, and modern backend applications, and recent updates make it even more developer-friendly. 🔹 What’s New & Improved in Node.js ⚡ Improved performance with faster startup times and better V8 optimizations 🔐 Built-in test runner for writing and running tests without external libraries 🌐 Native Fetch API for making HTTP requests without extra packages 📦 Better ES Modules support for modern JavaScript development 🧵 Enhanced worker threads for CPU-intensive tasks 🛡️ Stronger security updates and long-term support (LTS) stability 🔹 Why Developers Love Node.js Event-driven, non-blocking I/O Perfect for APIs, microservices, and real-time apps Same language on frontend & backend (JavaScript) Huge ecosystem and active community 💡 Final Thought With continuous improvements and a strong focus on performance, security, and developer experience, Node.js remains a future-ready platform for backend development. #NodeJS #JavaScript #BackendDevelopment #WebDevelopment #TechUpdates #SoftwareEngineering
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Nodezee Solutions
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The Clean Architecture Manifesto for Node.js How to structure enterprise applications for 5+ years of growth and maintainability. The Cost of Technical Debt In the rapid lifecycle of startup development, architectural integrity is often sacrificed for speed. However, at Nodezee, our decade of experience has taught us that the "Monolithic Spaghetti" pattern is the leading cause of project failure. We implement Clean Architecture (Uncle Bob's principles) adapted for the asynchronous nature of Node.js. 1. The Dependency Rule The core of our systems is the Domain Layer (Entities and Use Cases). This layer contains the pure business logic and has zero knowledge of the database, the web server, or external APIs. By ensuring that dependencies only point inwards, we can swap out a PostgreSQL database for MongoDB or move from Express to Fastify without touching the core logic. This is essential for maintaining the 150+ systems we have deployed. 2. Interface Adapters and Controllers We use Controllers to bridge the gap between the HTTP request and our Use Cases. By using Dependency Injection, we inject repository interfaces into our services. In Node.js, this is achieved through class constructors or lightweight DI containers. This makes our code 100% unit-testable, as we can easily mock the database layer during Jest testing suites. 3. Scalability through Decoupling Clean Architecture allows our team of 30+ developers to work on separate modules of the same application without merge conflicts. One team can optimize the data persistence layer while another refines the UI logic. The result is a system that isn't just built for today, but engineered to evolve for the next 5 to 10 years. https://lnkd.in/dNQaAFZj
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🐔 Guilherme Dalla Rosa
MerCloud • 3 mil seguidores
Just got my hands on the early access of "Node.js Design Patterns" 4th edition by 🦁 Luciano Mammino and Mario Casciaro, and it's the most straightforward path I've seen to production-grade Node.js. Having worked with Luciano on multiple projects, I can tell you this book captures exactly the kind of pragmatic wisdom he brings to real-world architectural discussions. This new edition brings fantastic updates on TypeScript integration, Web Streams, and a new testing chapter that alone is worth the upgrade. What I love most? The authors don't just throw patterns at you - they show you when NOT to use them, which is honestly just as valuable. The real-world examples hit different when you've been burned by the exact anti-patterns they warn against (looking at you, callback hell survivors 😅). Whether you're scaling your first Node.js app or you're a seasoned dev looking to solidify your architectural game, this book delivers. Can't recommend it enough! #NodeJS #JavaScript #DesignPatterns #SoftwareArchitecture #Backend #Packt
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