{"action":"created","issue":{"url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/183","repository_url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements","labels_url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/183/labels{/name}","comments_url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/183/comments","events_url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/183/events","html_url":"https://github.com/UnitedIncome/serverless-python-requirements/issues/183","id":318688612,"number":183,"title":"How to speed up packaging with multiple lambda functions and package individually set to True?","user":{"login":"skeller88","id":5506306,"avatar_url":"https://avatars3.githubusercontent.com/u/5506306?v=4","gravatar_id":"","url":"https://api.github.com/users/skeller88","html_url":"https://github.com/skeller88","followers_url":"https://api.github.com/users/skeller88/followers","following_url":"https://api.github.com/users/skeller88/following{/other_user}","gists_url":"https://api.github.com/users/skeller88/gists{/gist_id}","starred_url":"https://api.github.com/users/skeller88/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/skeller88/subscriptions","organizations_url":"https://api.github.com/users/skeller88/orgs","repos_url":"https://api.github.com/users/skeller88/repos","events_url":"https://api.github.com/users/skeller88/events{/privacy}","received_events_url":"https://api.github.com/users/skeller88/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-04-29T04:17:26Z","updated_at":"2018-04-30T18:50:16Z","closed_at":null,"author_association":"NONE","body":"This library has been helpful, but I'm running into performance limits. At 5 lambda functions with per package requirements and the `dockerizePip` option, the `package` step is taking 5 minutes. With \"package individually\" set to \"True\", that step takes 1.5 minutes. That's great, but I need the individual packaging to stay under the lambda deployment package size limit. How can I speed up the package step? \r\n\r\nCreating a docker image with all of the dependencies would probably help. I'm going to try that. \r\n\r\nIs there a way to just package a single lambda function? It doesn't seem like there is. Is there a way to parallelize the packaging of lambda functions? Also doesn't seem like there is. "},"comment":{"url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/comments/385493123","html_url":"https://github.com/UnitedIncome/serverless-python-requirements/issues/183#issuecomment-385493123","issue_url":"https://api.github.com/repos/UnitedIncome/serverless-python-requirements/issues/183","id":385493123,"user":{"login":"skeller88","id":5506306,"avatar_url":"https://avatars3.githubusercontent.com/u/5506306?v=4","gravatar_id":"","url":"https://api.github.com/users/skeller88","html_url":"https://github.com/skeller88","followers_url":"https://api.github.com/users/skeller88/followers","following_url":"https://api.github.com/users/skeller88/following{/other_user}","gists_url":"https://api.github.com/users/skeller88/gists{/gist_id}","starred_url":"https://api.github.com/users/skeller88/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/skeller88/subscriptions","organizations_url":"https://api.github.com/users/skeller88/orgs","repos_url":"https://api.github.com/users/skeller88/repos","events_url":"https://api.github.com/users/skeller88/events{/privacy}","received_events_url":"https://api.github.com/users/skeller88/received_events","type":"User","site_admin":false},"created_at":"2018-04-30T18:50:16Z","updated_at":"2018-04-30T18:50:16Z","author_association":"NONE","body":"Right. How has the lambda process scaled for you guys then? I would assume you have dozens of lambdas or more at this point. \r\n\r\nOne way to get around the Serverless packaging slowness could be to have several build processes, each of which does a different subset of the lambdas. "}}
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