Glossary

Technology glossary

Clear, no-nonsense definitions of the software, AI, data and cloud concepts we use across our projects.

// 01 — Glossary48

01API: An Application Programming Interface is a defined set of rules that lets one software system request data or services from another. APIs let teams connect apps, reuse functionality, and integrate third-party tools without exposing internal code, accelerating development and enabling ecosystems of interoperable products.
02REST: REST is a widely used architectural style for web APIs that exposes data as resources accessed over standard HTTP methods like GET and POST. Its simplicity, statelessness, and broad tooling support make it the default choice for most public and internal web services.
03GraphQL: GraphQL is a query language and runtime for APIs that lets clients request exactly the data they need in a single call. It reduces over-fetching and round trips, making it valuable for complex apps and mobile clients where bandwidth and flexibility matter.
04gRPC: gRPC is a high-performance framework for service-to-service communication that uses HTTP/2 and compact binary messages. It offers low latency, streaming, and strongly typed contracts, making it well suited for microservices and internal systems that exchange large volumes of data efficiently.
05Webhook: A webhook is an automated message a system sends to a URL when an event happens, pushing data in real time instead of waiting to be asked. Webhooks power instant notifications and integrations, such as triggering workflows when a payment succeeds or an order ships.
06SDK: A Software Development Kit is a bundle of libraries, tools, and documentation that helps developers build on a specific platform or service. SDKs speed up integration by handling low-level details, so teams can adopt a product or API faster and with fewer errors.
07SaaS: Software as a Service delivers applications over the internet on a subscription basis, with the provider handling hosting, updates, and maintenance. SaaS removes installation and infrastructure burdens, giving businesses predictable costs and instant access from any device with a browser.
08PaaS: Platform as a Service provides a managed cloud environment for building, running, and deploying applications without managing the underlying servers. It handles infrastructure, scaling, databases, and runtimes, letting development teams focus on writing code, ship faster, and reduce the operational overhead of maintaining systems.
09IaaS: Infrastructure as a Service offers on-demand computing resources like servers, storage, and networking over the cloud. Companies rent only what they use instead of buying hardware, gaining flexibility, faster provisioning, and the ability to scale capacity up or down as needs change.
10Serverless: Serverless is a cloud model where the provider automatically runs and scales code without the team managing servers, billing only for actual execution. It lowers operational effort and cost for event-driven or variable workloads, though it can introduce cold starts and vendor dependencies.
11Cloud computing: Cloud computing delivers computing resources such as servers, storage, databases, and software over the internet on demand. It replaces large upfront hardware investments with flexible pay-as-you-go costs, enabling faster deployment, global reach, and elastic scaling for businesses of any size.
12Cloud migration: Cloud migration is the process of moving applications, data, and workloads from on-premises systems to cloud infrastructure. Done well, it can cut costs, improve scalability, and modernize operations, though it requires careful planning around security, compatibility, and minimizing downtime during the transition for the business.
13Kubernetes: Kubernetes is an open source platform that automates deploying, scaling, and managing containerized applications across clusters of machines. It handles load balancing, self-healing, and rollouts, helping teams run resilient, portable workloads consistently across cloud and on-premises environments while reducing manual operational effort.
14Docker: Docker is a platform that packages applications and their dependencies into lightweight, portable containers that run consistently across environments. It eliminates the classic works-on-my-machine problem, speeding up development, testing, and deployment, and uses system resources far more efficiently than traditional virtual machines.
15Microservices: Microservices is an architecture that structures an application as many small, independent services, each owning a specific function. Teams can develop, deploy, and scale them separately, improving agility and resilience, at the cost of added complexity in coordination and monitoring.
16Monolith: A monolith is an application built and deployed as a single, unified codebase where all features run together. It is simpler to develop and test early on, but can become harder to scale, update, and maintain as the system and team grow.
17CI/CD: CI/CD stands for Continuous Integration and Continuous Delivery or Deployment, an automated pipeline that builds, tests, and releases code changes frequently. It reduces manual errors and speeds up delivery, letting teams ship reliable software updates quickly and consistently with lower risk on every release.
18DevOps: DevOps is a set of practices and a culture that unites software development and IT operations to deliver software faster and more reliably. Through automation, collaboration, and continuous feedback, it shortens release cycles and improves the stability and quality of systems.
19DevSecOps: DevSecOps integrates security into every stage of the DevOps pipeline rather than treating it as a final check. By automating security testing and embedding it into development and operations, teams catch vulnerabilities earlier, reducing risk and cost without slowing delivery.
20MVP: A Minimum Viable Product is the simplest version of a product that delivers core value and can be released to gather real user feedback. It lets teams validate ideas quickly with less investment, learning what to build next before committing to full development.
21Technical debt: Technical debt is the future cost of choosing quick or easy solutions over better long-term ones. Like financial debt, it accrues interest: unaddressed shortcuts slow development, raise maintenance costs, and increase bugs until the underlying code is refactored or rewritten.
22Scalability: Scalability is a system's ability to handle growing workloads by adding resources without losing performance or reliability. It matters because scalable software can support more users, data, and transactions as a business grows, avoiding costly redesigns or outages under heavy demand.
23Vendor lock-in: Vendor lock-in occurs when switching away from a product or provider is difficult or costly due to proprietary technology, data formats, or deep integrations. It limits flexibility and bargaining power, so businesses weigh it carefully when choosing platforms and cloud services.
24Open source: Open source refers to software whose source code is publicly available to use, study, modify, and share, often under permissive licenses. It lowers costs, avoids vendor lock-in, and benefits from community contributions, though it requires diligence around support, security, and licensing terms.
25Low-code: Low-code platforms let developers build applications mainly through visual interfaces and prebuilt components, with minimal hand-written code. They speed up delivery and let smaller teams produce working software faster, while still allowing custom code to handle complex, specialized, or highly tailored business requirements.
26No-code: No-code platforms enable people to build applications entirely through visual tools and drag-and-drop interfaces, without writing code. They empower non-technical users to automate tasks and create apps quickly, though they offer less flexibility than traditional or low-code development for complex needs.
27Machine learning: Machine learning is a branch of AI in which systems learn patterns from data to make predictions or decisions without being explicitly programmed for each task. It powers recommendations, fraud detection, and forecasting, improving as it is exposed to more relevant data.
28AI: Artificial Intelligence is the field of building systems that perform tasks normally requiring human intelligence, such as understanding language, recognizing images, or making decisions. In business, AI automates work, surfaces insights from data, and enables new products and customer experiences.
29LLM: A Large Language Model is an AI system trained on vast text data to understand and generate human-like language. LLMs power chatbots, content generation, summarization, and coding assistants, helping businesses automate knowledge work, though outputs require review for accuracy and bias.
30RAG: Retrieval-Augmented Generation improves AI answers by retrieving relevant information from a trusted knowledge base and feeding it to a language model before it responds. It grounds outputs in your own data, reducing made-up answers and keeping responses current and verifiable.
31Big Data: Big Data refers to datasets so large, fast, or varied that traditional tools cannot process them effectively. Specialized technologies store and analyze this data to reveal patterns and insights, helping organizations make better decisions in areas like marketing, operations, and risk.
32Data warehouse: A data warehouse is a central repository that stores structured data from many sources, optimized for analysis and reporting. It gives organizations a consistent, query-friendly source of truth for business intelligence, helping leaders analyze trends and make informed, data-driven decisions.
33Data lake: A data lake is a large storage repository that holds raw data in its native format, whether structured, semi-structured, or unstructured. It offers flexibility and low-cost storage for analytics and machine learning, but needs governance to avoid becoming an unusable data swamp.
34ETL: ETL stands for Extract, Transform, Load, a process that pulls data from sources, cleans and reshapes it, then loads it into a target system like a data warehouse. It ensures data is consistent and analysis-ready, forming the backbone of reliable analytics.
35Business Intelligence: Business Intelligence is the practice of collecting, analyzing, and visualizing data to support better business decisions. Through dashboards and reports, BI turns raw data into actionable insights, helping organizations track performance, spot trends, and respond faster to opportunities and risks.
36KPI: A Key Performance Indicator is a measurable value that shows how effectively a team or organization is achieving a specific goal. KPIs focus attention on what matters, enabling leaders to track progress, compare performance, and make decisions grounded in clear, agreed-upon metrics.
37Predictive analytics: Predictive analytics uses historical data, statistics, and machine learning to forecast likely future outcomes. Businesses apply it to anticipate demand, detect risks, and target customers, turning past patterns into proactive decisions that improve planning, efficiency, and competitiveness across operations and revenue.
38IoT: The Internet of Things is a network of physical devices embedded with sensors and connectivity that collect and exchange data. From smart factories to connected vehicles, IoT enables real-time monitoring and automation, helping businesses improve efficiency, safety, and decision-making across distributed physical operations.
39Digital twin: A digital twin is a virtual replica of a physical object, system, or process, kept in sync using real-time data. It lets organizations simulate, monitor, and optimize performance without disrupting the real asset, supporting predictive maintenance and smarter operational decisions.
40ERP: Enterprise Resource Planning software integrates core business processes such as finance, inventory, HR, and supply chain into one unified system. By centralizing data and workflows, ERP improves visibility, reduces duplication, and helps organizations operate more efficiently and consistently across every department.
41CRM: Customer Relationship Management software helps businesses manage interactions with customers and prospects across sales, marketing, and support. By centralizing contact data and history, CRM improves follow-up, personalizes communication, and helps teams build stronger relationships, retain clients, and close more deals.
42PWA: A Progressive Web App is a website built to behave like a native app, with offline support, fast loading, and the option to install on a device. PWAs reach users across platforms from a single codebase, lowering development cost and friction.
43Native app: A native app is software built specifically for one platform, such as iOS or Android, using its dedicated languages and tools. It delivers the best performance and full access to device features, but requires separate development and maintenance for each platform.
44Cross-platform: Cross-platform development builds apps that run on multiple operating systems from a single shared codebase. It cuts development time and cost compared to building separate native apps, though it may trade some performance or access to platform-specific capabilities in exchange for that efficiency.
45SQL: SQL, or Structured Query Language, is the standard language for managing and querying relational databases organized into tables. It lets users store, retrieve, update, and analyze structured data reliably and precisely, making it foundational to most business applications and enterprise data systems.
46NoSQL: NoSQL refers to databases that store data in flexible formats beyond traditional tables, such as documents, key-value pairs, or graphs. They excel at scaling and handling large, varied, or rapidly changing data, making them popular for modern web and real-time applications.
47GDPR: The General Data Protection Regulation is a European Union law governing how organizations collect, store, and use personal data. It grants individuals strong privacy rights and imposes strict obligations and fines, so any business handling EU residents' data must ensure compliance.
48Penetration testing: Penetration testing is an authorized simulated cyberattack that probes systems, networks, or applications to find security weaknesses before real attackers do. It helps organizations understand their real-world exposure, prioritize fixes, and meet compliance requirements, strengthening overall security posture and reducing breach risk.

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