Find a term
Understand the metrics, models, and methods behind modern engineering. Clear definitions, practical examples, and a closer look at what the numbers actually mean.
Terms beginning with G
22 termsGame day
Game day is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.
Reliability and observabilityGateway adapter
Gateway adapter is a model-routing or gateway concept used to manage interface consistency for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.
Model routing and gatewaysGateway configuration
Gateway configuration is a model-routing or gateway concept used to manage interface consistency for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.
Model routing and gatewaysGateway endpoint
Gateway endpoint is a model-routing or gateway concept used to manage interface consistency for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.
Model routing and gatewaysGateway metrics
Gateway metrics is a model-routing or gateway concept used to manage interface consistency for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.
Model routing and gatewaysGateway request lifecycle
The gateway request lifecycle is the ordered set of stages an AI request passes through before a response reaches the application. It commonly includes authentication, admission, policy evaluation, routing, provider execution, retries or fallback, response handling, and usage recording.
Model routing and gatewaysGauge metric
Gauge metric is a value that can rise or fall, such as queue depth, memory, or active connections.
Reliability and observabilityGeneralization
Generalization is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.
LLM fundamentalsGitOps
GitOps is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsGoal setting
Goal setting is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.
Developer productivityGolden path
Golden path is a way to organize, support, or evaluate software work so that teams can make useful progress with less avoidable friction. It is most valuable when connected to a concrete outcome and the local conditions of the team using it.
Developer productivityGolden signals
The golden signals are latency, traffic, errors, and saturation. They are a monitoring framework that focuses attention on the most useful high-level indicators of service health from a user's and operator's perspective.
Reliability and observabilityGoodhart's law
Goodhart's law is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.
Engineering analyticsGPU memory utilization
GPU memory utilization is the serving concept concerned with gpu memory utilization during AI inference.
Inference performanceGraceful degradation
Graceful degradation is a model-routing or gateway concept used to manage traffic selection for AI requests. It describes a distinct decision, control, interface, or observation point between an application and one or more model providers.
Model routing and gatewaysGraceful shutdown
Graceful shutdown is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.
DORA and DevOpsGradient accumulation
Gradient accumulation is a language-model concept about evaluation design and failure analysis. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.
LLM fundamentalsGradient clipping
Gradient clipping is a language-model concept about training behavior and measurement. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.
LLM fundamentalsGrammar-constrained generation
Grammar-constrained generation is a language-model concept about generation behavior and sampling. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.
LLM fundamentalsGraph of thoughts
Graph of thoughts is a language-model concept about representation and similarity. It names a mechanism, representation, prompting pattern, decoding control, or context behavior that can change how an AI system processes input and produces output.
LLM fundamentalsGray-box testing
Gray-box testing is a software testing or test-design practice used to gather evidence about a defined risk, behavior, boundary, or operating condition. It makes the question under test explicit, identifies the inputs and observations that matter, and gives a team a repeatable basis for deciding whether the result is acceptable.
Code quality and technical debtGrouped-query attention
Grouped-query attention is a language-model concept about serving behavior and operational tradeoffs. It names a mechanism, representation, training practice, or operational behavior that can change how an AI system processes input and produces output.
LLM fundamentals