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
Borrador de traduccion automatica (Spanish) for "Scheduler Cold Start Budget": Scheduler Cold Start Budget is a compute latency target that limits startup delay for newly scheduled execution for placement of work onto resources. 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.
“Ejemplo en borrador: The platform engineering team used Scheduler Cold Start Budget when the cluster needed to place a job, so the team could keep first requests responsive before the workload scaled up.”
Borrador de traduccion automatica (Spanish) for "Runbook Release Manifest": Runbook Release Manifest is a devops delivery record that lists versions, artifacts, routes, and checks for a release for documented operational procedure. It uses commit IDs, checksums, and deployment URLs so teams can make releases auditable while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used Runbook Release Manifest when a responder needed the recovery steps, so the team could make releases auditable before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Observability Config Drift Check": Observability Config Drift Check is a devops consistency check that finds differences between intended and live configuration for logs, metrics, traces, and events. 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.
“Ejemplo en borrador: The DevOps team used Observability Config Drift Check when latency increased after deploy, so the team could avoid surprise environment behavior before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Cluster Runtime Profile": Cluster Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for group of machines acting as one platform. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The platform engineering team used Cluster Runtime Profile when the cluster added a node pool, so the team could target optimization work before the workload scaled up.”
Borrador de traduccion automatica (Spanish) for "BGP Failover Policy": BGP Failover Policy is a networking resilience policy that defines when traffic should move to another path or region for interdomain routing. It uses health signals, priorities, and cooldown windows so teams can recover from outages predictably while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The network engineering team used BGP Failover Policy when a route advertisement changed, so the team could recover from outages predictably before traffic crossed a service boundary.”
Borrador de traduccion automatica (Spanish) for "TLS Traffic Shaper": TLS Traffic Shaper is a networking control mechanism that limits or prioritizes flows across links for encrypted transport setup. 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.
“Ejemplo en borrador: The network engineering team used TLS Traffic Shaper when a certificate neared expiration, so the team could protect important traffic before traffic crossed a service boundary.”
Borrador de traduccion automatica (Spanish) 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.
“Ejemplo en borrador: 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.”
Borrador de traduccion automatica (Spanish) for "Storage Placement Strategy": Storage Placement Strategy is a compute scheduling rule that chooses where workloads should run for persistent data and object access. 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.
“Ejemplo en borrador: The platform engineering team used Storage Placement Strategy when the workload read a large dataset, so the team could improve reliability and efficiency before the workload scaled up.”
Borrador de traduccion automatica (Spanish) for "GPU Resource Quota": GPU Resource Quota is a compute limit that sets how much compute a workload may consume for accelerated compute for parallel workloads. It uses policy, reservations, and usage tracking so teams can protect shared capacity while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The platform engineering team used GPU Resource Quota when the training job requested more memory, so the team could protect shared capacity before the workload scaled up.”
Borrador de traduccion automatica (Spanish) for "Edge Isolation Boundary": Edge Isolation Boundary is a compute security boundary that separates workloads so one cannot affect another unexpectedly for globally distributed runtime. It uses namespaces, sandboxes, and access controls so teams can reduce cross-workload risk while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The platform engineering team used Edge Isolation Boundary when the request arrived near a user, so the team could reduce cross-workload risk before the workload scaled up.”