[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2024-11-09 UTC。"],[[["\u003cp\u003eThe Google Play EMM API has a default limit of 60,000 queries per minute per EMM, exceeding which results in an HTTP 429 Too Many Requests error.\u003c/p\u003e\n"],["\u003cp\u003eTo avoid exceeding the usage limit, randomize device sync intervals and job start times to distribute the request load.\u003c/p\u003e\n"],["\u003cp\u003eImplement exponential backoff to retry requests with increasing wait times after receiving HTTP 429 errors.\u003c/p\u003e\n"],["\u003cp\u003eFor batch processes, utilize a rate limiter to adjust the request rate dynamically and prevent consistently hitting the usage limit, ensuring low latency for user actions.\u003c/p\u003e\n"]]],[],null,["# Usage Limits\n\nThe Google Play EMM API has a default limit of 60,000 queries per minute for each EMM.\n\nIf you exceed the quota, then the Google Play EMM API returns `HTTP 429 Too Many Requests`.\nTo help ensure that you don't exceed the stated usage limits and offer an optimal experience for\nyour users, consider implementing some of the best practices described in the section below.\n\nRecommendations for staying below the API usage limits\n------------------------------------------------------\n\nWhen using the Google Play EMM API, there are some best practices that you can implement to\ndistribute requests and reduce your risk of exceeding the usage limits.\n\n### Randomize start times and intervals\n\nActivities such as syncing or checking-in devices at the same time are likely to result in a\nsignificant increase in request volume. Instead of performing these activities at regularly\nscheduled intervals, you can distribute your request load by randomizing these intervals. For\nexample, rather than syncing each device every 24 hours, you can sync each device at a randomly\nchosen time period between 23 and 25 hours. This helps spread out the number of requests.\n\nSimilarly, if you run a daily job that makes many API calls in quick succession, consider\nstarting the job at a random time each day to prevent making a high volume of requests for all\nyour enterprise customers at the same time.\n\n### Use exponential backoff to retry requests\n\nIf you run jobs that consists of many API calls, use an exponential backoff strategy in\nresponse to reaching the quota. Exponential backoff is an algorithm that retries requests\nexponentially. An example flow for implementing simple exponential backoff is as follows:\n\n1. Make a request to the Google Play EMM API.\n2. Receive an `HTTP 429` response.\n3. Wait 2 seconds + `random_time`, then retry the request.\n4. Receive an `HTTP 429` response.\n5. Wait 4 seconds + `random_time`, then retry the request.\n6. Receive an `HTTP 429` response.\n7. Wait 8 seconds + `random_time`, then retry the request.\n\nThe `random_time` is typically a random number ranging from ***-0.5 \\* wait time***\nto ***+0.5 \\* wait time*** . Redefine a new `random_time` each time you retry your\nrequest. API calls that are required to complete user-facing actions can be retried on a more\nfrequent schedule (0.5s, 1s, and 2s, for example).\n\n### Rate-limit batch processes\n\nEach time a batched process reaches the quota, the latency of user actions that call the API\nincreases. In situations like these, strategies such as exponential backoff may not be effective\nenough in maintaining low latency for user actions.\n\nTo avoid reaching the API's usage limits repeatedly and increasing latency for user-facing\nactions, consider using a rate limiter for your batched processes (see [Google's RateLimiter](https://google.github.io/guava/releases/19.0/api/docs/index.html?com/google/common/util/concurrent/RateLimiter.html)).\nWith a rate limiter you can adjust the rate of your API requests so that you consistently remain\nbelow the usage limits.\n\nFor example, start a batched process with a default rate limit of 50 QPS. As long as the API\ndoesn't return an error, increase the rate limit slowly (1% every minute). Each time you reach\nthe quota, reduce your request rate by 20%. This adaptive approach results in a more optimal\nrequest rate while reducing latency for user-facing actions."]]
