Define the new internet.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
2,337 definitions
機械支援の翻訳下書き (Japanese) for "TLS Resolver Cache": TLS Resolver Cache is a networking performance layer that stores DNS answers for reuse until they expire for encrypted transport setup. It uses TTL rules, cache keys, and invalidation so teams can reduce lookup latency while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The network engineering team used TLS Resolver Cache when a certificate neared expiration, so the team could reduce lookup latency before traffic crossed a service boundary.”
機械支援の翻訳下書き (Japanese) for "Infrastructure Approval Step": Infrastructure Approval Step is a devops workflow control that requires review before a sensitive change proceeds for cloud resources and platform wiring. It uses role checks, comments, and audit logs so teams can keep high-risk automation accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Infrastructure Approval Step when a new region was added, so the team could keep high-risk automation accountable before the deployment window opened.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”
機械支援の翻訳下書き (Japanese) for "Edge Autoscaling Policy": Edge Autoscaling Policy is a compute control loop that changes capacity based on demand signals for globally distributed runtime. It uses metrics, thresholds, and cooldowns so teams can match resources to load while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Edge Autoscaling Policy when the request arrived near a user, so the team could match resources to load before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Storage Workload Priority": Storage Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for persistent data and object access. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Storage Workload Priority when the workload read a large dataset, so the team could protect critical paths before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "DNS Traffic Shaper": DNS Traffic Shaper is a networking control mechanism that limits or prioritizes flows across links for name resolution and delegation. It uses queues, rate limits, and quality-of-service rules so teams can protect important traffic while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The network engineering team used DNS Traffic Shaper when a resolver returned stale data, so the team could protect important traffic before traffic crossed a service boundary.”
機械支援の翻訳下書き (Japanese) for "DNS Ingress Rule": DNS Ingress Rule is a networking boundary rule that controls how external traffic enters a service for name resolution and delegation. It uses hostnames, paths, protocols, and policy checks so teams can keep entry points predictable while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The network engineering team used DNS Ingress Rule when a resolver returned stale data, so the team could keep entry points predictable before traffic crossed a service boundary.”
機械支援の翻訳下書き (Japanese) for "GPU Placement Strategy": GPU Placement Strategy is a compute scheduling rule that chooses where workloads should run for accelerated compute for parallel workloads. It uses affinity, topology, availability, and cost signals so teams can improve reliability and efficiency while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used GPU Placement Strategy when the training job requested more memory, so the team could improve reliability and efficiency before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Memory Autoscaling Policy": Memory Autoscaling Policy is a compute control loop that changes capacity based on demand signals for volatile runtime storage. It uses metrics, thresholds, and cooldowns so teams can match resources to load while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Memory Autoscaling Policy when the process approached its memory limit, so the team could match resources to load before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Queue Image Hardening": Queue Image Hardening is a compute security practice that reduces risk inside packaged runtime images for asynchronous work buffer. It uses minimal bases, patching, and vulnerability checks so teams can ship safer workloads while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Queue Image Hardening when the queue depth increased, so the team could ship safer workloads before the workload scaled up.”