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id ▼ | html_url | issue_url | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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938171377 | https://github.com/simonw/datasette/issues/1480#issuecomment-938171377 | https://api.github.com/repos/simonw/datasette/issues/1480 | IC_kwDOBm6k_c4361vx | ghing 110420 | 2021-10-07T21:33:12Z | 2021-10-07T21:33:12Z | CONTRIBUTOR | Thanks for the reply @simonw. What services have you had better success with than Cloud Run for larger database? Also, what about my issue description makes you think there may be a workaround? Is there any instrumentation I could add to see at which point in the deploy the memory usage spikes? Should I be able to see this whether it's running under Docker locally, or do you suspect this is Cloud Run-specific? | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Exceeding Cloud Run memory limits when deploying a 4.8G database 1015646369 | |
947196177 | https://github.com/simonw/datasette/issues/1480#issuecomment-947196177 | https://api.github.com/repos/simonw/datasette/issues/1480 | IC_kwDOBm6k_c44dRER | ghing 110420 | 2021-10-20T00:05:10Z | 2021-10-20T00:05:10Z | CONTRIBUTOR | I was looking through the Dockerfile-generation code to see if there was anything that would cause memory usage to be a lot during deployment. I noticed that the Dockerfile [runs `datasette --inspect`](https://github.com/simonw/datasette/blob/main/datasette/utils/__init__.py#L354). Is it possible that this is using a lot of memory usage? Or would that come into play when running `gcloud builds submit`, not when it's actually deployed? | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Exceeding Cloud Run memory limits when deploying a 4.8G database 1015646369 | |
947203725 | https://github.com/simonw/datasette/issues/1480#issuecomment-947203725 | https://api.github.com/repos/simonw/datasette/issues/1480 | IC_kwDOBm6k_c44dS6N | ghing 110420 | 2021-10-20T00:21:54Z | 2021-10-20T00:21:54Z | CONTRIBUTOR | This StackOverflow post, [sqlite - Cloud Run: Why does my instance need so much RAM?](https://stackoverflow.com/questions/59812405/cloud-run-why-does-my-instance-need-so-much-ram), points to [this section of the Cloud Run docs](https://cloud.google.com/run/docs/troubleshooting) that says: > Note that the Cloud Run container instances run in an environment where the files written to the local filesystem count towards the available memory. This also includes any log files that are not written to /var/log/* or /dev/log. Does datasette write any large files when starting? Or does the [`COPY` command in the Dockerfile](https://github.com/simonw/datasette/blob/main/datasette/utils/__init__.py#L349) count as writing to the local filesystem? | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Exceeding Cloud Run memory limits when deploying a 4.8G database 1015646369 |
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