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
Rascunho de traducao automatica (Portuguese) for "Cache Backpressure Control": Cache Backpressure Control is a compute stability pattern that slows incoming work when downstream capacity is limited for fast temporary data layer. It uses queues, retry budgets, and admission control so teams can avoid overload cascades while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The platform engineering team used Cache Backpressure Control when the cache missed during peak traffic, so the team could avoid overload cascades before the workload scaled up.”
Rascunho de traducao automatica (Portuguese) for "Serverless Cache Invalidation": Serverless Cache Invalidation is a compute freshness process that removes or refreshes stale cached data for event-driven function execution. It uses keys, tags, timestamps, and purge events so teams can serve current results while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The platform engineering team used Serverless Cache Invalidation when the function received a traffic burst, so the team could serve current results before the workload scaled up.”
Rascunho de traducao automatica (Portuguese) for "DNS Resolver Cache": DNS Resolver Cache is a networking performance layer that stores DNS answers for reuse until they expire for name resolution and delegation. It uses TTL rules, cache keys, and invalidation so teams can reduce lookup latency while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The network engineering team used DNS Resolver Cache when a resolver returned stale data, so the team could reduce lookup latency before traffic crossed a service boundary.”
Rascunho de traducao automatica (Portuguese) for "CPU Isolation Boundary": CPU Isolation Boundary is a compute security boundary that separates workloads so one cannot affect another unexpectedly for general-purpose processor scheduling. It uses namespaces, sandboxes, and access controls so teams can reduce cross-workload risk while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The platform engineering team used CPU Isolation Boundary when the service hit a compute ceiling, so the team could reduce cross-workload risk before the workload scaled up.”
Rascunho de traducao automatica (Portuguese) 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.
“Exemplo em rascunho: 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.”
Rascunho de traducao automatica (Portuguese) 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.
“Exemplo em rascunho: 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.”
Rascunho de traducao automatica (Portuguese) 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.
“Exemplo em rascunho: 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.”
Rascunho de traducao automatica (Portuguese) for "GPU Workload Priority": GPU Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for accelerated compute for parallel workloads. 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.
“Exemplo em rascunho: The platform engineering team used GPU Workload Priority when the training job requested more memory, so the team could protect critical paths before the workload scaled up.”
Rascunho de traducao automatica (Portuguese) for "Infrastructure Rollback Plan": Infrastructure Rollback Plan is a devops recovery plan that defines how to return to a known good version for cloud resources and platform wiring. It uses version pins, database notes, and operator steps so teams can recover quickly from bad changes while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The DevOps team used Infrastructure Rollback Plan when a new region was added, so the team could recover quickly from bad changes before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Queue Placement Strategy": Queue Placement Strategy is a compute scheduling rule that chooses where workloads should run for asynchronous work buffer. 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.
“Exemplo em rascunho: The platform engineering team used Queue Placement Strategy when the queue depth increased, so the team could improve reliability and efficiency before the workload scaled up.”