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
Brouillon de traduction automatique (French) for "Serverless Capacity Forecast": Serverless Capacity Forecast is a compute planning model that estimates future resource needs for event-driven function execution. It uses traffic history, growth assumptions, and utilization trends so teams can avoid surprise shortages while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Serverless Capacity Forecast when the function received a traffic burst, so the team could avoid surprise shortages before the workload scaled up.”
Brouillon de traduction automatique (French) for "Infrastructure Incident Timeline": Infrastructure Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for cloud resources and platform wiring. 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.
“Exemple en brouillon: The DevOps team used Infrastructure Incident Timeline when a new region was added, so the team could learn from outages without guesswork before the deployment window opened.”
Brouillon de traduction automatique (French) for "Secret Rollout Guard": Secret Rollout Guard is a devops release control that limits exposure during gradual deployment for credential and sensitive configuration. 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.
“Exemple en brouillon: The DevOps team used Secret Rollout Guard when a token rotated, so the team could reduce blast radius before the deployment window opened.”
Brouillon de traduction automatique (French) for "Scheduler Cache Invalidation": Scheduler Cache Invalidation is a compute freshness process that removes or refreshes stale cached data for placement of work onto resources. It uses keys, tags, timestamps, and purge events so teams can serve current results while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Scheduler Cache Invalidation when the cluster needed to place a job, so the team could serve current results before the workload scaled up.”
Brouillon de traduction automatique (French) 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.
“Exemple en brouillon: 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.”
Brouillon de traduction automatique (French) for "Virtual Machine Backpressure Control": Virtual Machine Backpressure Control is a compute stability pattern that slows incoming work when downstream capacity is limited for isolated guest compute. It uses queues, retry budgets, and admission control so teams can avoid overload cascades while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Virtual Machine Backpressure Control when the VM migrated hosts, so the team could avoid overload cascades before the workload scaled up.”
Brouillon de traduction automatique (French) for "Cache Image Hardening": Cache Image Hardening is a compute security practice that reduces risk inside packaged runtime images for fast temporary data layer. It uses minimal bases, patching, and vulnerability checks so teams can ship safer workloads while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Cache Image Hardening when the cache missed during peak traffic, so the team could ship safer workloads before the workload scaled up.”
Brouillon de traduction automatique (French) for "Memory Capacity Forecast": Memory Capacity Forecast is a compute planning model that estimates future resource needs for volatile runtime storage. It uses traffic history, growth assumptions, and utilization trends so teams can avoid surprise shortages while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Memory Capacity Forecast when the process approached its memory limit, so the team could avoid surprise shortages before the workload scaled up.”
Brouillon de traduction automatique (French) for "Observability Infra Plan": Observability Infra Plan is a devops change preview that shows expected infrastructure changes before apply for logs, metrics, traces, and events. It uses resource graphs, policy checks, and cost notes so teams can review platform changes safely while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The DevOps team used Observability Infra Plan when latency increased after deploy, so the team could review platform changes safely before the deployment window opened.”
Brouillon de traduction automatique (French) for "Container Cache Invalidation": Container Cache Invalidation is a compute freshness process that removes or refreshes stale cached data for packaged application runtime. It uses keys, tags, timestamps, and purge events so teams can serve current results while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemple en brouillon: The platform engineering team used Container Cache Invalidation when the image started on a new node, so the team could serve current results before the workload scaled up.”