Certification and tech glossary
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50 terms from cloud, security, Kubernetes, AI, data and project management, each explained in plain English with an example and the ideas it is most often confused with.
50 of 50 terms
Cloud and networking
DHCPThe service that automatically gives devices an IP address and other network settings.DNSThe system that turns names like example.com into the IP addresses computers use.High availabilityDesigning a system so it keeps working when a part of it fails.IaaS, PaaS and SaaSThree ways to rent cloud computing, from raw servers (IaaS) to a platform for your code (PaaS) to a finished app (SaaS).OSI modelA seven-layer way of describing how data travels across a network.Shared responsibility modelThe cloud provider secures the cloud itself, and you secure what you put in it.SubnetA smaller network carved out of a larger IP range.
Security
CIA triadThree goals of information security: confidentiality, integrity and availability.Encryption at rest and in transitScrambling data so it is unreadable without a key, while it is stored and while it moves.IDS and IPSAn IDS detects suspicious traffic and raises an alert. An IPS sits in the path and can block it.Least privilegeGive every person and system only the access they need to do their job, and nothing more.Multi-factor authentication (MFA)Proving who you are with two or more different kinds of evidence.PhishingA scam message that tricks you into giving up a password, money or access.Zero trustA security approach that never assumes a request is safe just because it comes from inside the network.
Kubernetes and DevOps
CI/CDAutomatically building, testing and delivering code every time it changes.Container vs virtual machineA virtual machine includes a whole operating system. A container shares the host’s operating system kernel and packages only the app and what it needs.GitOpsUsing a Git repository as the single source of truth for what should be running, with software that keeps the live system matching it.Kubernetes DeploymentAn object that keeps a chosen number of identical pods running and updates them safely.Kubernetes ServiceA stable network address and name that sends traffic to a changing group of pods.Metrics, logs and tracesThe three main kinds of telemetry: numbers over time, event records, and the path of a single request.ObservabilityHow well you can understand what is happening inside a system from the data it produces.OpenTelemetry CollectorA vendor-neutral service that receives telemetry, processes it and sends it on to one or more tools.PodThe smallest unit you can deploy in Kubernetes, made of one or more containers that run together.PromQLThe query language used to read and calculate on Prometheus metrics.
AI and machine learning
AI agentAn AI system that pursues a goal by deciding on steps and using tools, not only by answering one question.Bias in AIResults that are systematically unfair to some people or groups.Embeddings and vector databasesLists of numbers that capture the meaning of text or images, stored so similar items can be found quickly.Fine-tuningTraining an existing model a little more on your own examples so it behaves in the way you want.Generative AIAI that creates new content, such as text, images, code or audio, from a prompt.HallucinationWhen an AI model states something false or invented as if it were true.Large language model (LLM)A very large neural network trained on huge amounts of text to predict and generate language.Model driftA model getting worse over time because the real world no longer looks like its training data.OverfittingWhen a model learns its training data too closely and does badly on new data.Prompt engineeringWriting instructions and context so an AI model gives a more useful answer.Responsible AIBuilding and using AI in ways that are fair, safe, private, transparent and accountable.Retrieval-augmented generation (RAG)Letting a model look up relevant documents first and answer using them.Supervised vs unsupervised learningSupervised learning trains on labelled examples. Unsupervised learning looks for structure in unlabelled data.TokensThe small chunks of text that a language model reads and writes, and that usage is measured in.
Data
Data governanceThe rules and responsibilities for how an organisation manages, protects and uses its data.Data warehouse vs data lakeA warehouse stores cleaned, structured data for reporting. A lake stores raw data of any kind cheaply.ETL vs ELTETL transforms data before loading it. ELT loads it first and transforms it inside the destination.
Project management and Agile
Critical pathThe longest chain of dependent tasks in a project, which sets the shortest possible project duration.Earned value managementA way to measure project progress by comparing planned work, completed work and actual cost.Product BacklogAn ordered list of everything that might be needed to improve the product.Product OwnerThe person accountable for maximising the value of the product and managing the Product Backlog.Scope creepUncontrolled growth in what a project is expected to deliver.Scrum MasterThe person accountable for helping a Scrum team understand and use Scrum well.SprintA fixed period of one month or less in which a Scrum team turns chosen work into a usable increment.StakeholderAnyone who can affect a project or is affected by it.Work breakdown structure (WBS)A hierarchy that breaks the total project scope into smaller, manageable pieces of deliverable work.
Written by the Be Ready Education team, last reviewed 2 November 2026. Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.