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
Automatischer Uebersetzungsentwurf (German) for "Environment Trace Link": Environment Trace Link is a devops observability link that connects a deployment or workflow to runtime evidence for configuration for a runtime stage. 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.
“Beispielentwurf: The DevOps team used Environment Trace Link when staging and production drifted, so the team could debug production changes faster before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) for "Artifact Approval Step": Artifact Approval Step is a devops workflow control that requires review before a sensitive change proceeds for build output and package delivery. 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.
“Beispielentwurf: The DevOps team used Artifact Approval Step when the container image was signed, so the team could keep high-risk automation accountable before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) for "Rollback Runbook Check": Rollback Runbook Check is a devops operational test that confirms that documented procedures still work for recovery from a bad deployment. It uses dry runs, screenshots, and command validation so teams can keep response playbooks current while keeping evidence, reliability, and public-safe operational boundaries clear.
“Beispielentwurf: The DevOps team used Rollback Runbook Check when the error budget started burning, so the team could keep response playbooks current before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) for "CD Infra Plan": CD Infra Plan is a devops change preview that shows expected infrastructure changes before apply for deployment automation and promotion. 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.
“Beispielentwurf: The DevOps team used CD Infra Plan when the release moved toward production, so the team could review platform changes safely before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) for "Environment Incident Timeline": Environment Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for configuration for a runtime stage. 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.
“Beispielentwurf: The DevOps team used Environment Incident Timeline when staging and production drifted, so the team could learn from outages without guesswork before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) for "CD Rollback Plan": CD Rollback Plan is a devops recovery plan that defines how to return to a known good version for deployment automation and promotion. 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.
“Beispielentwurf: The DevOps team used CD Rollback Plan when the release moved toward production, so the team could recover quickly from bad changes before the deployment window opened.”
Automatischer Uebersetzungsentwurf (German) 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.
“Beispielentwurf: 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.”
Automatischer Uebersetzungsentwurf (German) 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.
“Beispielentwurf: 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.”
Automatischer Uebersetzungsentwurf (German) 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.
“Beispielentwurf: 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.”
Automatischer Uebersetzungsentwurf (German) 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.
“Beispielentwurf: 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.”