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.

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 managing external HTTP/HTTPS routing rules to cluster-internal Services.

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.

Workload controller managing stateful applications requiring unique network IDs and ordered volume provisioning.

Mathematical operation computing context weights by comparing Query, Key, and Value vector dot-products.

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.

Hyperparameter scaling logit probabilities before softmax to tune generation randomness and entropy.

Sampling strategy filtering candidate tokens to the smallest set whose cumulative probability reaches threshold P.

Process of updating LLM weights on specialized task datasets to adjust domain behavior or response formats.

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.

State persistence architecture dividing context into short-term working context, long-term vector memory, and episodic logs.