cloudstorage | Unified cloud storage API for storage services | Cloud Storage library

In general you can't nest aggregates within other aggregates. They can refer via the root to the other aggregate. You can make all access to a given aggregate be through another aggregate.

For instance the product aggregate might be like:

plotly_IMAGE is used to export graphs as static images using plotly chart studio. You need an api_key for this to work. See this or help(signup, package = 'plotly').

If you want to export static images on your local PC you can use plotly::save_image(p, "plot.png").

For save_image to work please consider the following:

kaleido() requires the kaleido python package to be usable via the reticulate package. Here is a recommended way to do the installation:

install.packages('reticulate') reticulate::install_miniconda() reticulate::conda_install('r-reticulate', 'python-kaleido') reticulate::conda_install('r-reticulate', 'plotly', channel = 'plotly') reticulate::use_miniconda('r-reticulate')

As an alternative you could use

htmlwidgets::saveWidget(partial_bundle(p), file = "plot.HTML", selfcontained = TRUE)

to save your chart as a standalone HTML file (e.g. as done here)

Refactor your code a bit so that the parts that you want to be potentially concurrent are in a separate asynchronous function, call that function for each element of the Stream, collect the resulting Futures, and use Future.wait to wait for them all to complete. For example:

You cannot access data from Firebase Storage in security rules of Firestore. You can try either of these:

• Make sure the add document function runs after the file has been uploaded (by awaiting promise in JS)
• Use Firebase Storage Triggers which will run a function when a file has been uploaded and then add the document from Cloud function. If you are using this method you can remove write access from users so only the Cloud function can add documents when that object is uploaded.

I'm still not sure why, but i've managed to work when moved the service to port 80 and kept the health check on 5000.

Service config:

According to this example, Secret is a special class that will handle creating volume mounts automatically. Looking at your code, seems that your own volume with mount /credentials is overriding /credentials mount created by Secret, and because you provide empty configs={}, that mount is empty as well.

Try supplying just secrets=[secret_jira_user,secret_storage_credentials] and removing manual volume_mounts.

• Code that generates secret volume mounts under the hood

Upon further research I think I have come across a possible answer that might work:

You can try installing typescript library for body-parser:

I've found the solution: to manage properly the package dependence, the google-cloud-storage library needs to be included via --properties=spark.jars.packages=, as shown in https://cloud.google.com/dataproc/docs/guides/manage-spark-dependencies . In my case this means