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 "Fine-Tuning Label Review": Fine-Tuning Label Review is a ml quality workflow that checks annotations for consistency and usefulness for adaptation of a model to a domain. It uses agreement metrics, reviewer queues, and adjudication so teams can improve supervised learning data while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The machine learning team used Fine-Tuning Label Review when the fine-tuning run used curated examples, so the team could improve supervised learning data before the model moved into evaluation.”
Rascunho de traducao automatica (Portuguese) for "Artifact Config Drift Check": Artifact Config Drift Check is a devops consistency check that finds differences between intended and live configuration for build output and package delivery. 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.
“Exemplo em rascunho: The DevOps team used Artifact Config Drift Check when the container image was signed, so the team could avoid surprise environment behavior before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Metric Model Card": Metric Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for measurement of model behavior. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The machine learning team used Metric Model Card when the metric changed after data cleanup, so the team could publish model behavior honestly before the model moved into evaluation.”
Rascunho de traducao automatica (Portuguese) for "Rollback Infra Plan": Rollback Infra Plan is a devops change preview that shows expected infrastructure changes before apply for recovery from a bad deployment. 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.
“Exemplo em rascunho: The DevOps team used Rollback Infra Plan when the error budget started burning, so the team could review platform changes safely before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Rollback Release Manifest": Rollback Release Manifest is a devops delivery record that lists versions, artifacts, routes, and checks for a release for recovery from a bad deployment. It uses commit IDs, checksums, and deployment URLs so teams can make releases auditable while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The DevOps team used Rollback Release Manifest when the error budget started burning, so the team could make releases auditable before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Artifact Build Gate": Artifact Build Gate is a devops quality gate that blocks promotion when required checks fail for build output and package delivery. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The DevOps team used Artifact Build Gate when the container image was signed, so the team could prevent broken releases before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Metric Training Checkpoint": Metric Training Checkpoint is a ml recovery artifact that saves model state during learning for measurement of model behavior. It uses weights, optimizer state, and run metadata so teams can resume or inspect training safely while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The machine learning team used Metric Training Checkpoint when the metric changed after data cleanup, so the team could resume or inspect training safely before the model moved into evaluation.”
Rascunho de traducao automatica (Portuguese) for "CI Trace Link": CI Trace Link is a devops observability link that connects a deployment or workflow to runtime evidence for continuous integration workflows. It uses trace IDs, span metadata, and release identifiers so teams can debug production changes faster while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The DevOps team used CI Trace Link when a pull request entered the build queue, so the team could debug production changes faster before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Canary Rollback Plan": Canary Rollback Plan is a devops recovery plan that defines how to return to a known good version for small-scope production rollout. 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 Canary Rollback Plan when the first traffic slice received the build, so the team could recover quickly from bad changes before the deployment window opened.”
Rascunho de traducao automatica (Portuguese) for "Rollback Secret Rotation": Rollback Secret Rotation is a devops credential workflow that replaces sensitive keys without service interruption for recovery from a bad deployment. It uses dual credentials, rollout steps, and revocation so teams can reduce credential exposure while keeping evidence, reliability, and public-safe operational boundaries clear.
“Exemplo em rascunho: The DevOps team used Rollback Secret Rotation when the error budget started burning, so the team could reduce credential exposure before the deployment window opened.”