Technical Glossary

Isolated user-space process tree bounded by Linux namespaces and cgroups sharing the host kernel.

Immutable read-only tarball bundle containing root filesystem layers, binary dependencies, and OCI runtime metadata.

Linux kernel mechanism metering and limiting hardware resource allocations (CPU, memory, disk I/O) for process groups.

Kernel abstraction restricting what system resources (processes, network interfaces, mounts) a process tree can observe.

Declarative plain-text build manifest consumed by BuildKit to assemble container image layers sequentially.

CLI command delegating Dockerfile parsing and layer assembly to the BuildKit engine.

CLI command instantiating and launching a container with specified isolation boundaries, volumes, and ports.

CLI command spawning a new process inside the existing namespaces of a running container.

Smallest deployable unit in Kubernetes, grouping co-located containers sharing network namespaces and storage volumes.

Worker machine (physical or VM) running kubelet, container runtime, and kube-proxy in a Kubernetes cluster.

Declarative controller managing stateless Pod replicas, progressive rollouts, and automatic rollbacks.

Abstract network endpoint presenting a stable virtual IP and DNS name across a dynamic pool of Pods.

API object binding non-confidential key-value configuration data to Pod container environment variables or volume mounts.

API object storing base64-encoded confidential credentials, certificates, or keys separately from image code.

CLI command declaratively updating cluster resources using 3-way strategic merge patches against etcd.

CLI command querying and displaying summary tables of specified Kubernetes API resources.

CLI command establishing interactive shell sessions inside a specific container in a cluster Pod.

Sub-word atomic chunk created by tokenizers (e.g. BPE) mapping text strings to numerical vocabulary IDs.

Dense numerical vector representing semantic meaning of text tokens in a continuous high-dimensional vector space.

Maximum token capacity an LLM can digest in a single forward pass, spanning system prompts, history, and responses.

Autonomous software loop leveraging an LLM as its core reasoning engine to observe environments, plan, and execute tool calls.

Mechanism enabling LLMs to emit structured JSON payload calls invoking external APIs, scripts, or database queries.

Agent prompting framework interleaving explicit step-by-step reasoning thoughts with action tool calls and observation inputs.