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 "Artifact Artifact Signature": Artifact Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for build output and package delivery. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used Artifact Artifact Signature when the container image was signed, so the team could trust deployed packages before the deployment window opened.”
Borrador de traduccion automatica (Spanish) 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.
“Ejemplo en borrador: 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.”
Borrador de traduccion automatica (Spanish) for "Artifact Incident Timeline": Artifact Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for build output and package delivery. 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.
“Ejemplo en borrador: The DevOps team used Artifact Incident Timeline when the container image was signed, so the team could learn from outages without guesswork before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "CI Artifact Signature": CI Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for continuous integration workflows. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used CI Artifact Signature when a pull request entered the build queue, so the team could trust deployed packages before the deployment window opened.”
Borrador de traduccion automatica (Spanish) 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.
“Ejemplo en borrador: 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.”
Borrador de traduccion automatica (Spanish) for "CI Incident Timeline": CI Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for continuous integration workflows. 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.
“Ejemplo en borrador: The DevOps team used CI Incident Timeline when a pull request entered the build queue, so the team could learn from outages without guesswork before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Metric Embedding Refresh": Metric Embedding Refresh is a ml index workflow that updates vector representations after source data changes for measurement of model behavior. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Metric Embedding Refresh when the metric changed after data cleanup, so the team could keep retrieval results current before the model moved into evaluation.”
Borrador de traduccion automatica (Spanish) for "Artifact Release Manifest": Artifact Release Manifest is a devops delivery record that lists versions, artifacts, routes, and checks for a release for build output and package delivery. 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 Artifact Release Manifest when the container image was signed, so the team could make releases auditable before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Fine-Tuning Hyperparameter Sweep": Fine-Tuning Hyperparameter Sweep is a ml optimization process that searches over model settings to improve a target metric for adaptation of a model to a domain. It uses bounded search spaces, trial tracking, and early stopping so teams can find better configurations while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Fine-Tuning Hyperparameter Sweep when the fine-tuning run used curated examples, so the team could find better configurations before the model moved into evaluation.”
Borrador de traduccion automatica (Spanish) for "Pipeline Data Split": Pipeline Data Split is a ml experimental control that separates examples for training, validation, and testing for automated data and model workflow. It uses randomization rules, leakage checks, and seed tracking so teams can measure generalization honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Pipeline Data Split when the pipeline missed a validation step, so the team could measure generalization honestly before the model moved into evaluation.”