Software Architecture: Software Architects, Architectural Characteristics - The "-ilities" (Availability (Confidentiality, Integrity - CIA Triad), Reliability, Testability, Scalability, Security, Agility, Fault Tolerance, Elasticity, Recoverability, Performance, Deployability, Learnability, Usability), Monolithic Architecture, Microservices Architecture, Service-Oriented Architecture (SOA), Event-Driven Architecture, Layered Architecture, Client-Server Architecture, Peer-to-Peer Architecture, Serverless Architecture, Cloud-Native Architecture, Domain-Driven Design (DDD), Hexagonal Architecture, Clean Architecture, Onion Architecture, CQRS (Command Query Responsibility Segregation), Event Sourcing, API Gateway Pattern, Backend for Frontend (BFF) Pattern, Database Sharding, Data Lake Architecture, Big Data Architecture, IoT Architecture, Blockchain Architecture, Artificial Intelligence and Machine Learning Architecture, High Availability Systems, Scalable Web Architecture, Security Architecture, Network Architecture, Infrastructure as Code (IaC), Continuous Integration/Continuous Deployment (CI/CD), DevOps Practices, Test-Driven Development (TDD), Behavior-Driven Development (BDD), System Design Principles, Design Patterns, Architectural Patterns, Performance Optimization, Load Balancing, Caching Strategies, Data Partitioning, Rate Limiting, API Design, Micro Frontends, Cross-Cutting Concerns, Versioning Strategies, Dependency Injection, Modular Design, Software Design Principles (SOLID), Reactive Systems, Distributed Systems Design, Failover Strategies, Disaster Recovery Planning, Data Consistency Models, Concurrency Models, Message Queuing, Stream Processing, Workflow Engines, Business Process Management (BPM), Enterprise Integration Patterns, Data Integration Patterns, Mobile App Architecture, Game Architecture, Virtual Reality (VR) Architecture, Augmented Reality (AR) Architecture, Content Delivery Networks (CDN), Edge Computing, Fog Computing, Hybrid Cloud Architecture, Multi-Tenant Architecture, OAuth and OpenID Connect, Web Security Architecture, Cryptographic Architecture, Compliance and Regulatory Frameworks, Architecture Review Processes, Technical Debt Management, Architectural Refactoring, Monitoring and Observability, Logging Strategies, Feature Toggling, A/B Testing, Blue-Green Deployments, Canary Releases, Service Mesh, Containerization and Orchestration, Kubernetes Architecture, Docker Architecture, Function as a Service (FaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), Software as a Service (SaaS), Blockchain as a Service (BaaS), Artificial Intelligence as a Service (AIaaS), Machine Learning Operations (MLOps), DataOps, Architecture Decision Records (ADR), Technical Writing for Architects, Stakeholder Management, Architecture Governance, Cost Optimization in Architecture, Sustainability in Software Architecture, Ethics in Software Architecture, Future Trends in Software Architecture
Software Architecture and DevOps - Software Architecture and SRE - Software Architecture of CI/CD, Cloud Native Software Architecture - Microservices Software Architecture - Serverless Software Architecture, Software Architecture and Security - Software Architecture and DevSecOps, Software Architecture and Functional Programming, Software Architecture of Concurrency, Software Architecture and Data Science - Software Architecture of Databases, Software Architecture of Machine Learning, Software Architecture Bibliography (Fundamentals of Software Architecture by Mark Richards and Neal Ford, Software Architecture - The Hard Parts), Software Architecture Courses, Software Architecture Glossary, Awesome Software Architecture, Software Architecture GitHub, Software Architecture Topics
SHORTEN THIS fork from navbar_golang_detailed:
Programming languages, abstraction, agile, ahead-of-time (AOT), AI, algebraic data types, algorithms, Android, anonymous functions, anonymous methods, AOP, AOT, APIs, arguments, ARM, arithmetic, arrays, aspect-oriented, assignment, associative arrays, async, asynchronous callbacks, asynchronous programming, automatic variables, automation, Avro, backend, backwards compatibility, block scoped, Booleans, Boolean expressions, buffer overflow, builds, built-in types, bytecode, cache, caching, call by reference, call by value, callbacks, call stack, casting, characters, Chocolatey, CI/CD, classes, CLI, client-side, closures, cloud (Cloud Native-AWS-Azure-GCP-IBM Cloud-IBM Mainframe-OCI), code smells, coercion, collections, command-line interface, commands, comments, compilers, complex numbers, composition, concurrency, concurrent programming, conditional expressions, conferences, constants, constructors, containers, control flow, control structures, coroutines, crashes, creators, currying, databases, data manipulation, data persistence, data science, data serialization, data structures, data synchronization, dates, dates and times, deadlocks, debugging, declarative, deferred callbacks, delegates, delegation, dependency injection, design patterns, designers, destructors, DevOps, dictionaries, dictionary comprehensions, DI, distributed software, distributions, distros, DL, Docker, do-while, DSL, duck typing, dynamic binding, dynamic scope, dynamically scoped, dynamically typed, dynamic variables, eager evaluation, embedded, encapsulation, encryption, enumerated types, enumeration, enums, environment variables, errors, error handling, evaluation strategy, event-driven, event handlers, event loops, exception handling, executables, execution, expressions, FaaS, Facebook, fibers, fields, file input/output, file synchronization, file I/O, filter, first-class functions, fold, foreach loops, fork-join, floating-point, FP, frameworks, FreeBSD, frontend, functions, functional, functional programming, function overloading, garbage collection, generators, generator expressions, generics, generic programming, GitHub, global variables, GraphQL, gRPC, GUI, hashing, heap, heap allocation, hello world, higher-order functions, history, Homebrew, HTTP, idempotence, IDEs, import, imperative, immutable values, immutability, inheritance, influenced, influenced by, installation, integers, integration testing, interfaces, internationalization, interpreters, interprocess communication (IPC), iOS, IoT, IPCs, ISO Standard, iteration, JetBrains, JIT, JSON, JSON-RPC, JSON Web Tokens, JSON Web Token (JWT), Just-in-time (JIT), JWT, K8S, keywords, lambdas, lambda expressions, lambda functions, language spec, lazy evaluation, lexically scoped, lexical scoping, libraries, linters, Linux, lists, list comprehensions, literals, localization, local variables, locks, logging, logo, looping, loosely typed, loose typing, macOS, map, mascot, math, member variables, memoization, memory addressing, memory allocation, malloc, memory management, memory safety, message queues, metaclasses, meta-programming, methods, method overloading, MFA, ML, microservices, Microsoft, mobile dev, modules, modulo operators, monitoring, multiprocessing, multi-threaded, mutable values, mutability, mutex (mutual exclusion), namespaces, natural language processing (NLP), networking, network programming, NLP, non-blocking, non-blocking I/O, null, null reference, null coalescing operators, numbers, number precision, OAuth, objects, object code, object comparisons, object creation, object creators, object destruction, object destructors, object lifetime, object-oriented constructors, object-oriented programming, object serialization, observability, OOP, operators, operator overloading, optimizations, organizations, ORMs, packages, package managers, pass by reference, pass by value, parallel computing, parallel programming, parallelism, parameters, people, performance, persistence, pipelines, pointers, polymorphism, primitives, primitive data types, probability, procedural, processes, producer-consumer, programmers, programming, programming paradigm, program structure, program termination, Protocol Buffers (Protobuf), Protocol Buffers, Protobuf, proxies, public-key encryption, PKI, pure functions, race conditions, random, reactive, readability, records, recursion, reentrancy, refactoring, reference counting, reference types, referential transparency, reflection, regex, remote procedure calls (RPC), REPL, reserved words, REST, REST APIs, RHEL, RPCs, runtimes, safe navigation operators, SDK, secrets, security, serialization, serverless, server-side, sets, set comprehensions, side effects, signed integers, SMTP, Snapcraft, social media, sockets, source code, source-to-source compiler, SQL, SSL - SSL-TLS, Single sign-on (SSO), SSO, StackOverflow, stack, stack allocation, Stack overflow, standards, standard errors, standard input, standard library, standard operators, standard output, state, statements, strings, string concatenation, string functions, string operations, scheduling, scientific notation, scope, scope rules, scoping, scripting, static analyzers, statically scoped, static scoping, statically typed, static variables, statistics, strongly typed, structural typing, synchronization, syntax, systems programming, TCP/IP, TDD, testing, test frameworks, threads, thread-local storage (TLS), TLS, thread locking, thread locks, thread safety, thread scheduling, thread synchronization, times, timers, to JavaScript, tools, toolchain, transpiler, transpiling to JavaScript, truth values, tuples, type checking, type conversion, type inference, type safety, type system, web dev, while loops, work stealing, values, value types, variables, variable lifetime, variable scope, versions, virtual environments, virtual machine, Ubuntu, Unicode, unit testing, unsigned integers, usability, weak typing, weakly typed, Windows, wrappers, written using, x86-64-AMD64, XML, YAML;
. (navbar_software_architecture - see also navbar_microservices, navbar_design_patterns, navbar_programming_detailed - Based on MASTER navbar_golang_detailed. navbar_programming is the shorter one.
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Scalability is the ability of a system, network, or process to handle a growing amount of work or its potential to accommodate growth. It is a critical aspect in various domains, including computing, business operations, and infrastructure. Scalability ensures that a system remains effective and efficient as demands increase.
Scalability refers to the ability of a system, network, or process to handle growing amounts of work in a capable and efficient manner. It is a critical aspect in various domains including technology, business, and infrastructure, ensuring that as demands increase, the system can accommodate them without compromising performance or stability. The concept is particularly pertinent in the realm of technology, where digital systems must often contend with rapidly expanding data volumes, user bases, and computational requirements.
One key aspect of scalability in technology is horizontal scalability, also known as scale-out, which involves adding more resources such as servers to distribute the workload. This approach contrasts with vertical scalability, or scale-up, which involves enhancing the capabilities of existing resources, such as upgrading a single server's hardware. Horizontal scalability is often favored in modern distributed systems due to its flexibility and potential for greater resilience against failures.
Cloud computing has significantly impacted scalability by providing on-demand access to vast computational resources. Cloud platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform offer scalable infrastructure services such as virtual machines, storage, and databases. This allows businesses to dynamically adjust their resource allocation based on demand fluctuations, thereby achieving cost-efficiency and agility.
Containerization technologies such as Docker and Kubernetes have also revolutionized scalability by enabling the deployment and management of applications in lightweight, portable containers. Containers encapsulate an application and its dependencies, making it easier to scale horizontally by deploying multiple instances across various environments consistently. Kubernetes, in particular, automates container orchestration and scaling, facilitating the efficient utilization of resources.
Scalability is crucial for web applications experiencing unpredictable traffic spikes, such as those driven by viral content or seasonal events. Content delivery networks (CDNs) enhance scalability by caching content across distributed edge servers, reducing latency and offloading traffic from origin servers. CDNs like Cloudflare, Akamai, and Amazon CloudFront enable websites to handle surges in user requests more effectively.
Database scalability is another critical consideration, especially as data volumes continue to grow exponentially. Traditional relational databases may struggle to cope with the scalability demands of modern applications. As a result, NoSQL (Not Only SQL) databases have gained popularity for their ability to scale horizontally and handle diverse data types. Examples include MongoDB, Cassandra, and Apache CouchDB.
In addition to technological considerations, achieving scalability often involves architectural design principles such as loose coupling, service-oriented architecture (SOA), and microservices. These approaches promote modularization and decoupling of components, allowing them to be scaled independently. Microservices, in particular, advocate for breaking down monolithic applications into smaller, independently deployable services, which can be scaled individually based on demand.
Scalability challenges may arise from various factors including bottlenecks, resource contention, and architectural constraints. Identifying and mitigating these challenges requires thorough performance testing, capacity planning, and continuous monitoring of system metrics. Tools such as load balancers, auto-scaling groups, and performance monitoring platforms play a crucial role in achieving and maintaining scalability in dynamic environments.
Scalability is not only a technical concern but also a business imperative, particularly for startups and rapidly growing companies. The ability to scale efficiently can directly impact competitiveness, customer satisfaction, and revenue growth. Investors and stakeholders often assess a company's scalability potential as part of their due diligence process, recognizing its significance in long-term sustainability and value creation.
In summary, scalability is a fundamental aspect of modern technology and business operations, encompassing various strategies, technologies, and architectural principles aimed at accommodating growing demands effectively and efficiently. From cloud computing and containerization to database scalability and architectural design, organizations must adopt scalable solutions to remain competitive in today's dynamic and fast-paced digital landscape.
Sources:
Scalability is the property of a system to handle a growing amount of work. One definition for software systems specifies that this may be done by adding resources to the system.
In an economic context, a scalable business model implies that a company can increase sales given increased resources. For example, a package delivery system is scalable because more packages can be delivered by adding more delivery vehicles. However, if all packages had to first pass through a single warehouse for sorting, the system would not be as scalable, because one warehouse can handle only a limited number of packages.
In computing, scalability is a characteristic of computers, networks, algorithms, networking protocols, programs and applications. An example is a search engine, which must support increasing numbers of users, and the number of topics it indexes. Webscale is a computer architectural approach that brings the capabilities of large-scale cloud computing companies into enterprise data centers.
In distributed systems, there are several definitions according to the authors, some considering the concepts of scalability a sub-part of elasticity, others as being distinct.
In mathematics, scalability mostly refers to closure under scalar multiplication.
In industrial engineering and manufacturing, scalability refers to the capacity of a process, system, or organization to handle a growing workload, adapt to increasing demands, and maintain operational efficiency. A scalable system can effectively manage increased production volumes, new product lines, or expanding markets without compromising quality or performance. In this context, scalability is a vital consideration for businesses aiming to meet customer expectations, remain competitive, and achieve sustainable growth. Factors influencing scalability include the flexibility of the production process, the adaptability of the workforce, and the integration of advanced technologies. By implementing scalable solutions, companies can optimize resource utilization, reduce costs, and streamline their operations. Scalability in industrial engineering and manufacturing enables businesses to respond to fluctuating market conditions, capitalize on emerging opportunities, and thrive in an ever-evolving global landscape.
Scalability: Cloud scalability, Auto Scaling Groups, Container Orchestration, Content Delivery Networks (CDNs), Cost Optimization in Scalable Cloud Architectures, Database Sharding, Distributed Computing and Scalability, Elastic Load Balancing, Fault Tolerance and High Availability, Horizontal Scaling vs Vertical Scaling, Infrastructure as Code (IaC), Multi-Region Deployment Strategies, Scaling Big Data Analytics Workloads, Scalability Testing in Cloud Environments, Scalable AI and Machine Learning Services, Scalable Message Queues and Event Streaming, Scalable Networking, Scalability in Microservices Architecture, Scalability in Serverless Computing, Scalable Storage Solutions, Serverless Computing. (navbar_scalability - see also nabvbar_load_balancing)