🗣4 best practices to improve efficiency from using the Google Cloud Translation API
A web service that dynamically translates between languages using Google ML models supports over 100 languages and is actively used in practice. And if you know useful life hacks, you can reduce costs, increase productivity, and improve the security of this translation API on websites.
1. Caching translated content not only reduces the number of calls to the Google Cloud Translation API, but also reduces the load and computation usage on internal web servers and databases. This optimizes application performance and reduces shipping costs. You can configure caching in an application architecture at different levels of the application. For example, at the proxy level (NGINX or HAProxy), the application itself in memory on web servers, or an external memory caching service, as well as through a CDN.
2. Secure access based on the principle of least privilege. When accessing the Google Cloud Translation API, it is recommended that you use a Google Cloud Service account rather than api keys. A service account is a special type of authentication that represents a non-human user and can be authorized to access data in the Google API. Service accounts are not assigned passwords and cannot be used to log in through a browser, minimizing this threat vector. By following the principle of least privilege, you can grant a least privileged role with a set of permissions to access the translation API.
3. Setting up translations. If your content includes domain and context terms, Google Cloud Translation API Advanced supports custom terminology through a glossary. You can create and use your own translation models using Google AutoML Translation. Customers understand the potential risks of errors and inaccuracies by alerting users that content has been automatically translated by Google.
4. Budget control. The costs associated with the Google Cloud Translation API mainly depend on the number of characters sent to the API. For example, at $ 10 per million characters, if a web page contains 20 million characters and needs to be translated into 10 languages, the cost would be $ 10 * 20 = $ 200. Setting up alerts in your work environment will help you keep track of your budget.
https://cloud.google.com/blog/products/ai-machine-learning/four-best-practices-for-translating-your-website