Continuous Delivery for Machine Learning
Automating the end-to-end lifecycle of Machine Learning applications Machine Learning applications are becoming popular in our industry, however the process for developing, deploying, and continuously improving them is more complex compared to more traditional software, such as a web service or a mobile application. They are subject to change in three axis: the code itself, the model, and the data
Feature Flag & Toggle Management Blog | LaunchDarkly
LaunchDarkly makes it easier for developers to swap between AI models based on application contexts, such as user email domain and other identifying factors such as device, zip code, region, or other custom context you may develop. In this tutorial, we will build a streamlined example demonstrating how to switch between different AssemblyAI model tiers with ...
Common pitfalls of dark launches and how to work around them | Google Cloud Blog
Accelerate State of DevOps ReportGet a comprehensive view of the DevOps industry, providing actionable guidance for organizations of all sizes. Download Editor's note: This is the second of a two-part series on dark launches. You can read the first post here. In the first part of this series, we introduced you to the concept of dark launches. In a dark launch, you take a copy of your incoming traf
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Accelerate: Software Delivery Performance
Secret to Facebook's Hacker Engineering Culture | LaunchDarkly
このページを見るには、ログインまたは登録してください
Jupyter(Python)とBigQueryによるデータ分析基盤のDevOps #pyconjp // Speaker Deck
