Uma Mahesh

Introduction In microservices architectures, managing workflows across multiple services is a critical challenge, particularly when ensuring data consistency, scalability, and loose coupling. Two primary approaches for coordinating distributed workflows are Service Orchestration and Service Choreography. Orchestration involves a central coordinator…

Introduction In microservices architectures, ensuring data consistency across independently deployable services is a critical challenge due to the distributed nature of the system. Unlike monolithic architectures, where a single database enforces strong consistency through ACID transactions, microservices employ decentralized data…

Introduction In microservices architectures, inter-service communication is a critical component that enables loosely coupled, independently deployable services to collaborate effectively to deliver cohesive application functionality. Unlike monolithic architectures, where components interact through in-memory function calls, microservices communicate over networks, introducing…

Introduction Microservices architecture has become a cornerstone for building scalable, flexible, and resilient distributed systems, enabling organizations to develop applications that can handle dynamic workloads and evolve independently. Unlike monolithic architectures, microservices decompose applications into small, autonomous services, each responsible…

Introduction Event-Driven Architecture (EDA) is a powerful design paradigm that facilitates loosely coupled, asynchronous communication in distributed systems, particularly within microservices architectures. By using events—discrete records of significant state changes or occurrences—EDA enables microservices to interact without direct dependencies, promoting…

Introduction The choice between monolithic and microservices architectures is a pivotal decision in distributed systems design, shaping an application’s scalability, maintainability, fault tolerance, and operational complexity. A monolithic architecture encapsulates all application components—user interface, business logic, data access, and persistence—within…

Introduction In distributed messaging systems, delivery semantics define how messages are guaranteed to be delivered and processed between producers and consumers. Two critical semantics are exactly-once and at-least-once, each balancing reliability, performance, and complexity in event-driven architectures. These semantics are…

Introduction to Data Pipelines Data pipelines represent structured workflows in distributed systems that facilitate the ingestion, transformation, and delivery of data from diverse sources to target destinations. These pipelines are fundamental for enabling data-driven decision-making, supporting real-time analytics, and ensuring…

Introduction In streaming systems, backpressure refers to the buildup of data when the rate of incoming events exceeds the processing capacity of downstream components, potentially leading to resource exhaustion, increased latency, or system failures. Backpressure handling is a critical mechanism…