机器辅助翻译草稿 (Chinese) for "Endpoint Trust Boundary": Endpoint Trust Boundary is a security security boundary that defines where assumptions, identities, or permissions change for user device and server protection. It uses network edges, service roles, and data classifications so teams can avoid accidental privilege crossing while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Endpoint Trust Boundary when a workstation reported suspicious activity, so the team could avoid accidental privilege crossing before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Endpoint Evidence Chain": Endpoint Evidence Chain is a security audit record that preserves how security evidence was collected and handled for user device and server protection. It uses timestamps, hashes, owners, and storage controls so teams can support trustworthy investigation while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Endpoint Evidence Chain when a workstation reported suspicious activity, so the team could support trustworthy investigation before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Launch Thermal Margin": Launch Thermal Margin is a space safety metric that tracks how much temperature headroom remains before a component exceeds limits for launch vehicle and ascent operations. It uses sensor data, heat models, and operational constraints so teams can protect hardware during changing conditions while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Launch Thermal Margin when the launch window narrowed, so the team could protect hardware during changing conditions before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Zero Trust Trust Boundary": Zero Trust Trust Boundary is a security security boundary that defines where assumptions, identities, or permissions change for continuous verification model. It uses network edges, service roles, and data classifications so teams can avoid accidental privilege crossing while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Zero Trust Trust Boundary when a device changed posture, so the team could avoid accidental privilege crossing before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Training Embedding Refresh": Training Embedding Refresh is a ml index workflow that updates vector representations after source data changes for model learning and optimization workflows. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Training Embedding Refresh when the training job restarted, so the team could keep retrieval results current before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Satellite Fault Detection": Satellite Fault Detection is a space control that finds off-nominal behavior before it becomes a mission-impacting failure for commercial and civil satellite service delivery. It uses telemetry thresholds, trend checks, and operator review so teams can choose a safe response while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Satellite Fault Detection when the constellation shifted traffic between spacecraft, so the team could choose a safe response before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Guardrail Agent Trace": Guardrail Agent Trace is a ai observability record that captures the steps an AI workflow took for policy controls around model input and output. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Guardrail Agent Trace when the model tried to include private context, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Threat Intel Trust Boundary": Threat Intel Trust Boundary is a security security boundary that defines where assumptions, identities, or permissions change for external risk and indicator context. It uses network edges, service roles, and data classifications so teams can avoid accidental privilege crossing while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Threat Intel Trust Boundary when a new campaign indicator appeared, so the team could avoid accidental privilege crossing before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Zero Trust Policy Decision": Zero Trust Policy Decision is a security authorization decision that determines whether an action should be allowed for continuous verification model. It uses identity, resource, context, and policy evaluation so teams can enforce least privilege while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Zero Trust Policy Decision when a device changed posture, so the team could enforce least privilege before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Secret Config Drift Check": Secret Config Drift Check is a devops consistency check that finds differences between intended and live configuration for credential and sensitive configuration. It uses desired state, live state, and diff reports so teams can avoid surprise environment behavior while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Secret Config Drift Check when a token rotated, so the team could avoid surprise environment behavior before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Zero Trust Phishing Resistance": Zero Trust Phishing Resistance is a security identity control that reduces success of credential theft attacks for continuous verification model. It uses passkeys, hardware-backed factors, and origin checks so teams can protect sign-in flows while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Zero Trust Phishing Resistance when a device changed posture, so the team could protect sign-in flows before the risk review began.”
机器辅助翻译草稿 (Chinese) for "Inference Model Card": Inference Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for model prediction serving. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Inference Model Card when the endpoint handled burst traffic, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Container Backpressure Control": Container Backpressure Control is a compute stability pattern that slows incoming work when downstream capacity is limited for packaged application runtime. It uses queues, retry budgets, and admission control so teams can avoid overload cascades while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The platform engineering team used Container Backpressure Control when the image started on a new node, so the team could avoid overload cascades before the workload scaled up.”
机器辅助翻译草稿 (Chinese) for "Context Context Contract": Context Context Contract is a ai interface contract that defines what context may be passed into a model call for runtime memory and retrieved information. It uses schemas, redaction rules, source labels, and token budgets so teams can keep model inputs relevant and safe while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Context Context Contract when the context window filled with mixed sources, so the team could keep model inputs relevant and safe before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Dataset Feature Store": Dataset Feature Store is a ml service that serves consistent features to training and inference for labeled and unlabeled data used for learning. It uses versioned feature definitions, freshness checks, and access policies so teams can avoid training-serving skew while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Dataset Feature Store when the dataset received a new batch, so the team could avoid training-serving skew before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Read URL Field": The Read URL Field is a structured metadata field that describes the read url inside a PlatPhorm News article listing. It lets humans and agents scan stories quickly, compare sources, and choose whether to read the article or open its discussion.
“示例草稿: The Read URL Field helped the reader understand the article listing before opening the full story.”
机器辅助翻译草稿 (Chinese) for "Service Mesh Resolver Cache": Service Mesh Resolver Cache is a networking performance layer that stores DNS answers for reuse until they expire for east-west service communication. It uses TTL rules, cache keys, and invalidation so teams can reduce lookup latency while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The network engineering team used Service Mesh Resolver Cache when a service called another service, so the team could reduce lookup latency before traffic crossed a service boundary.”
机器辅助翻译草稿 (Chinese) for "Runbook Rollout Guard": Runbook Rollout Guard is a devops release control that limits exposure during gradual deployment for documented operational procedure. It uses traffic slices, health checks, and automatic pause rules so teams can reduce blast radius while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Runbook Rollout Guard when a responder needed the recovery steps, so the team could reduce blast radius before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Routing Human Approval": Routing Human Approval is a ai control step that requires a person to approve sensitive or high-impact actions for selection among models, tools, and workflows. It uses risk scoring, review UI, and audit logs so teams can keep protected decisions accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Routing Human Approval when the router selected a cheaper model, so the team could keep protected decisions accountable before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Rollback Build Gate": Rollback Build Gate is a devops quality gate that blocks promotion when required checks fail for recovery from a bad deployment. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Rollback Build Gate when the error budget started burning, so the team could prevent broken releases before the deployment window opened.”