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 "Observability Incident Timeline": Observability Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for logs, metrics, traces, and events. It uses timestamps, owners, and evidence links so teams can learn from outages without guesswork while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Observability Incident Timeline when latency increased after deploy, so the team could learn from outages without guesswork before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Infrastructure Config Drift Check": Infrastructure Config Drift Check is a devops consistency check that finds differences between intended and live configuration for cloud resources and platform wiring. 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.
“例文の下書き: The DevOps team used Infrastructure Config Drift Check when a new region was added, so the team could avoid surprise environment behavior before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Memory Backpressure Control": Memory Backpressure Control is a compute stability pattern that slows incoming work when downstream capacity is limited for volatile runtime storage. 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 Memory Backpressure Control when the process approached its memory limit, so the team could avoid overload cascades before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Cluster Image Hardening": Cluster Image Hardening is a compute security practice that reduces risk inside packaged runtime images for group of machines acting as one platform. 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 Cluster Image Hardening when the cluster added a node pool, so the team could ship safer workloads before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Cluster Autoscaling Policy": Cluster Autoscaling Policy is a compute control loop that changes capacity based on demand signals for group of machines acting as one platform. 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 Cluster Autoscaling Policy when the cluster added a node pool, 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 "Container Workload Priority": Container Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for packaged application runtime. 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 Container Workload Priority when the image started on a new node, so the team could protect critical paths before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Serverless Resource Quota": Serverless Resource Quota is a compute limit that sets how much compute a workload may consume for event-driven function execution. It uses policy, reservations, and usage tracking so teams can protect shared capacity while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Serverless Resource Quota when the function received a traffic burst, so the team could protect shared capacity before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Container Cold Start Budget": Container Cold Start Budget is a compute latency target that limits startup delay for newly scheduled execution for packaged application runtime. It uses prewarming, smaller packages, and runtime tuning so teams can keep first requests responsive while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Container Cold Start Budget when the image started on a new node, so the team could keep first requests responsive before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "Edge Cold Start Budget": Edge Cold Start Budget is a compute latency target that limits startup delay for newly scheduled execution for globally distributed runtime. It uses prewarming, smaller packages, and runtime tuning so teams can keep first requests responsive while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used Edge Cold Start Budget when the request arrived near a user, so the team could keep first requests responsive before the workload scaled up.”
機械支援の翻訳下書き (Japanese) for "CPU Runtime Profile": CPU Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for general-purpose processor scheduling. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The platform engineering team used CPU Runtime Profile when the service hit a compute ceiling, so the team could target optimization work before the workload scaled up.”