Scalability Patterns

Scalability patterns deal with effectively handling an increasing workload. They provide strategies for systems to maintain performance and resource utilization as demand grows, ensuring a positive user experience.

Wikipedia

Self-Contained Systems

architectural DDD scalability

Self-Contained Systems is an architectural pattern where an application is structured as a suite of independently deployable services, each with its own database and logic. These systems are designed to be loosely coupled, communicating with each other via well-defined APIs, but without sharing databases or internal …

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Distributed Cache

behavioral scalability

The Distributed Cache pattern addresses performance bottlenecks in applications that rely heavily on data retrieval. Instead of repeatedly querying a database or performing complex calculations on every request, frequently accessed data is stored in a fast, distributed key-value store. This reduces latency, increases …

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Sacrificial Architecture

resilience scalability operations

Sacrificial Architecture is a resilience pattern where non-critical components are intentionally designed as single points of failure, allowing them to be quickly replaced or rebuilt in the event of an outage. The goal isn’t to make these components reliable, but to make their failure cheap and fast, protecting …

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Geo-Replication

distributed systems scalability reliability

Geo-Replication is a technique used to distribute data across multiple geographically diverse locations. This is done to improve performance for users in those regions (by reducing latency), increase availability and fault tolerance (by having backups in different locations), and provide disaster recovery capabilities. …

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Open Host Service

architectural integration scalability

The Open Host Service pattern addresses the need for exposing functionality or data from an internal system (the Host) to external services (the Service) in a controllable and scalable way. It acts as an intermediary, preventing direct access to the Host and offering a standardized interface. This separation of …

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Cluster-based Architecture

architectural scalability reliability

A Cluster-based Architecture involves grouping multiple interconnected computers (nodes) together to work as a single system. This approach enhances performance, availability, and scalability by distributing workloads across the cluster. The nodes typically share resources and are managed by software that coordinates …

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Replication

distributed systems reliability scalability

The Replication pattern addresses the need for data consistency and availability across multiple systems. It involves creating and maintaining multiple copies of data, ensuring that if one copy fails, others are available to serve requests. This enhances fault tolerance, improves read performance by distributing load, …

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Sharding

scalability architecture database

Sharding is a database architecture pattern used to horizontally partition a dataset across multiple machines (shards). This is typically done when a single database instance can no longer handle the growing volume of data or the increasing number of read/write operations. Each shard contains a subset of the total …

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Shared-Nothing

architectural scalability distributed systems

The Shared-Nothing architecture is a distributed computing architecture where each node in the system has its own dedicated resources – CPU, memory, and disk – and does not share these resources with any other node. Nodes communicate with each other via a network, typically using message passing. This contrasts with …

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Gateway Offloading

architecture scalability performance

The Gateway Offloading pattern addresses scalability and performance issues in systems with a central gateway component. It involves distributing the load from the gateway to other services or infrastructure components – such as Content Delivery Networks (CDNs), alternative backend services, or dedicated processing …

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