#deployment

機械支援の翻訳下書き (Japanese) for "Inference": The act of running a trained machine learning model on new input data to generate predictions or outputs. Inference is distinct from training — it is the "serving" phase where the model is used in production, and its speed and cost are critical for real-world applications.

“例文の下書き: Inference latency dropped from 2 seconds to 200ms after switching to a quantized model.”

機械支援の翻訳下書き (Japanese) for "CI/CD": Continuous Integration / Continuous Delivery — a set of software engineering practices and tools that automate the process of testing, building, and deploying code changes. CI automatically validates every commit; CD deploys validated code to production frequently and reliably without manual intervention.

“例文の下書き: The team ships 20 times a day safely because their CI/CD pipeline catches regressions automatically.”

機械支援の翻訳下書き (Japanese) for "DevOps": A set of practices, tools, and cultural philosophies that unite software development (Dev) and IT operations (Ops) teams. DevOps breaks down silos, automates repetitive tasks, and instills shared responsibility for the full software lifecycle from code to production monitoring.

“例文の下書き: After adopting DevOps, their release cycle went from monthly to daily.”