A reference from Weave

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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 D

176 terms
  • Disaggregated serving

    Disaggregated serving is the serving concept concerned with disaggregated serving during AI inference.

    Inference performance
  • Disaster recovery testing

    Disaster recovery 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 debt
  • Discovery work

    Discovery work 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 productivity
  • Discussion resolution

    Discussion resolution is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review
  • Disk pressure

    Disk pressure is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability
  • Distance from main sequence

    An architecture signal that combines abstractness and instability to highlight potentially problematic component positions.

    Code quality and technical debt
  • Distributed trace

    Distributed trace is a record following one operation across multiple processes or services with linked spans.

    Reliability and observability
  • Distributed tracing

    Distributed tracing is a method for recording the path and timing of a request as it moves through multiple services, processes, or other components. A trace groups related spans that describe individual operations along that path.

    Reliability and observability
  • Divergent change

    A code smell in which one module changes for many unrelated reasons.

    Code quality and technical debt
  • Document representation

    Document representation is a language-model concept about instruction design and control. 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 fundamentals
  • Documentation as code

    Documentation as code 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 productivity
  • Documentation debt

    Documentation debt is a software maintenance concern describing a condition that can make future changes, verification, operation, or ownership harder. Its practical importance depends on supported behavior, rate of change, and the consequences of delay.

    Code quality and technical debt
  • Documentation review

    Documentation review is a practical concept in a pull-request workflow that shapes how people examine, discuss, own, or integrate a proposed change.

    Code review
  • Domain adaptation

    Domain adaptation 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
  • DORA metrics

    DORA metrics are a set of software delivery performance measures used to understand how quickly and reliably an application changes in production. The current model covers change lead time, deployment frequency, failed deployment recovery time, change fail rate, and deployment rework rate.

    DORA and DevOps
  • Downstream dependency

    Downstream dependency is a concept used in software delivery planning to describe a condition, relationship, estimate, or decision about engineering work.

    Flow and capacity planning
  • Draft pull request

    A draft pull request signals that a change is visible for early discussion but is not ready for final approval or merge.

    Code review
  • Drift detection

    Drift detection watches for changes in a signal's distribution or meaning.

    Engineering analytics
  • Dry-run routing

    Dry-run routing 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 gateways
  • Dual-environment deployment

    Dual-environment deployment is a release engineering and DevOps concept for controlling how software changes are prepared, introduced, or understood.

    DORA and DevOps
  • Duplicate events

    Duplicate events is an analytical risk or quality concern that can make an engineering analysis appear more certain, comparable, or causal than it is.

    Engineering analytics
  • Duplicate rate

    Duplicate rate measures records repeated under identity and timing rules.

    Engineering analytics
  • Duplicate request protection

    Duplicate request protection is a model-routing or gateway concept used to manage reliable request governance 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 gateways
  • Durable queue

    Durable queue is a reliability concept used to describe a specific condition, control, or decision in the operation of software services.

    Reliability and observability
  • Dynamic batching

    Dynamic batching is the serving concept concerned with dynamic batching during AI inference.

    Inference performance
  • Dynamic routing

    Dynamic routing 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 gateways