When a transaction spans across multiple microservices (e.g., processing an e-commerce order, charging a credit card, and updating inventory), you cannot use traditional ACID database transactions.
Node.js is a popular JavaScript runtime built on Chrome's V8 engine that allows developers to build scalable and efficient server-side applications. With its event-driven, non-blocking I/O model, Node.js is well-suited for building distributed systems.
Scaling Node.js horizontally involves running multiple instances of the application across various processes or physical machines. The Node.js Cluster Module
: Understanding how to deploy and scale services using modern tooling like Docker and Kubernetes . Distributed Systems With Node.js Pdf Download
What specific (REST, gRPC, or Message Brokers) you plan to implement.
To maintain strict boundaries between services, avoid allowing multiple microservices to query the same database instance. Shared databases create tight coupling and schema migration gridlocks. Instead, give each service its own dedicated database and communicate data changes via events. The Saga Pattern
[ CAP Theorem ] /\ / \ / \ Consistency /______\ Availability (C) Network (A) Partition (P) Fallacies of Distributed Computing When a transaction spans across multiple microservices (e
The book provides an in-depth exploration of distributed systems, focusing on the Node.js ecosystem. It covers the fundamental concepts, design principles, and practical implementation details necessary for building robust and scalable distributed systems.
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Node.js is highly efficient for distributed architectures due to its structural design. The Event Loop and Asynchronous I/O Scaling Node
Node.js is traditionally celebrated for its asynchronous, event-driven architecture, making it a premier choice for building fast, I/O-intensive web applications. However, as applications scale to serve millions of users, a single monolithic Node.js instance inevitably encounters physical CPU and memory limitations. To scale beyond these constraints, engineering teams must transition to distributed systems—architectures where independent components run on multiple machines, communicating over a network to achieve a common goal.
Distributed orchestrators like Kubernetes rely on health endpoints ( /healthz/liveness and /healthz/readiness ) to monitor your Node.js processes. If a process hangs due to an unhandled exception or memory leak, the orchestrator terminates and replaces the container automatically. 5. Distributed Data and State Management