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 "Canary Artifact Signature": Canary Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for small-scope production rollout. 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 Canary Artifact Signature when the first traffic slice received the build, so the team could trust deployed packages before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "CI Config Drift Check": CI Config Drift Check is a devops consistency check that finds differences between intended and live configuration for continuous integration workflows. 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 CI Config Drift Check when a pull request entered the build queue, so the team could avoid surprise environment behavior before the deployment window opened.”
Borrador de traduccion automatica (Spanish) 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.
“Ejemplo en borrador: 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.”
Borrador de traduccion automatica (Spanish) for "Environment Artifact Signature": Environment Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for configuration for a runtime stage. 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 Environment Artifact Signature when staging and production drifted, so the team could trust deployed packages before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Fine-Tuning Training Checkpoint": Fine-Tuning Training Checkpoint is a ml recovery artifact that saves model state during learning for adaptation of a model to a domain. 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 Fine-Tuning Training Checkpoint when the fine-tuning run used curated examples, so the team could resume or inspect training safely before the model moved into evaluation.”
Borrador de traduccion automatica (Spanish) for "CI Infra Plan": CI Infra Plan is a devops change preview that shows expected infrastructure changes before apply for continuous integration workflows. 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.
“Ejemplo en borrador: The DevOps team used CI Infra Plan when a pull request entered the build queue, so the team could review platform changes safely before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Fine-Tuning Provenance Ledger": Fine-Tuning Provenance Ledger is a ml record that tracks where data came from and how it changed for adaptation of a model to a domain. It uses hashes, source labels, and transformation history so teams can audit model inputs reliably while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Fine-Tuning Provenance Ledger when the fine-tuning run used curated examples, so the team could audit model inputs reliably before the model moved into evaluation.”
Borrador de traduccion automatica (Spanish) for "Artifact Infra Plan": Artifact Infra Plan is a devops change preview that shows expected infrastructure changes before apply for build output and package delivery. 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.
“Ejemplo en borrador: The DevOps team used Artifact Infra Plan when the container image was signed, so the team could review platform changes safely before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Environment Secret Rotation": Environment Secret Rotation is a devops credential workflow that replaces sensitive keys without service interruption for configuration for a runtime stage. It uses dual credentials, rollout steps, and revocation so teams can reduce credential exposure while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used Environment Secret Rotation when staging and production drifted, so the team could reduce credential exposure before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Pipeline Drift Monitor": Pipeline Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for automated data and model workflow. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Pipeline Drift Monitor when the pipeline missed a validation step, so the team could respond before quality drops before the model moved into evaluation.”