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
機械支援の翻訳下書き (Japanese) for "Pipeline Evaluation Harness": Pipeline Evaluation Harness is a ml test system that runs repeatable checks against model behavior for automated data and model workflow. It uses fixtures, metrics, thresholds, and regression reports so teams can compare releases with evidence while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The machine learning team used Pipeline Evaluation Harness when the pipeline missed a validation step, so the team could compare releases with evidence before the model moved into evaluation.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: The DevOps team used Environment Secret Rotation when staging and production drifted, so the team could reduce credential exposure before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Pipeline Calibration Curve": Pipeline Calibration Curve is a ml diagnostic that compares predicted confidence with observed outcomes for automated data and model workflow. It uses bucketed predictions, reliability diagrams, and threshold analysis so teams can make confidence scores useful while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The machine learning team used Pipeline Calibration Curve when the pipeline missed a validation step, so the team could make confidence scores useful before the model moved into evaluation.”
機械支援の翻訳下書き (Japanese) for "CD Rollout Guard": CD Rollout Guard is a devops release control that limits exposure during gradual deployment for deployment automation and promotion. It uses traffic slices, health checks, and automatic pause rules so teams can reduce blast radius while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used CD Rollout Guard when the release moved toward production, so the team could reduce blast radius before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Rollback Approval Step": Rollback Approval Step is a devops workflow control that requires review before a sensitive change proceeds for recovery from a bad deployment. It uses role checks, comments, and audit logs so teams can keep high-risk automation accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Rollback Approval Step when the error budget started burning, so the team could keep high-risk automation accountable before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Environment Config Drift Check": Environment Config Drift Check is a devops consistency check that finds differences between intended and live configuration for configuration for a runtime stage. 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.
“例文の下書き: The DevOps team used Environment Config Drift Check when staging and production drifted, so the team could avoid surprise environment behavior before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Pipeline Provenance Ledger": Pipeline Provenance Ledger is a ml record that tracks where data came from and how it changed for automated data and model workflow. 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.
“例文の下書き: The machine learning team used Pipeline Provenance Ledger when the pipeline missed a validation step, so the team could audit model inputs reliably before the model moved into evaluation.”
機械支援の翻訳下書き (Japanese) for "CI Secret Rotation": CI Secret Rotation is a devops credential workflow that replaces sensitive keys without service interruption for continuous integration workflows. It uses dual credentials, rollout steps, and revocation so teams can reduce credential exposure while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used CI Secret Rotation when a pull request entered the build queue, so the team could reduce credential exposure before the deployment window opened.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”