flask-rest-example | flask rest api + blueprint + sqlalchemy + marshmallow + | SQL Database library

The MongoDB version can be acquired by running a command, specifically the buildInfo command.

Using the shell, this is how you could do it:

You can print out the sql for that migration to see specifically whats wrong, but defining db_type to return "enum" is definitely not the right way to approach it.

I came across the same issue trying to scaffold an existing MySQL database. It looks like the latest version of MySql.EntityFrameworkCore (6.0.0-preview3.1) still uses the EFCore 5.0 libraries and has not been updated to EFCore 6.0.

It also seems Microsoft.EntityFrameworkCore.Diagnostics was last implemented in EFCore 5 and removed in 6.

When I downgraded all the packages to the 5 version level, I was able to run the scaffold command without that error.

The RDS proxy sits between your application and the database & should not result in any application change other than using the proxy endpoint.

Should I close the connection after executing my queries or leave it open for the RDS Proxy to handle?

You should not leave database connections open regardless of if you use or don't use a database proxy.

Connections are a limited and relatively expensive resource.

The rule of thumb is to open connections as late as possible & close DB connections as soon as possible. Connections that are not explicitly closed might not be added or returned to the pool. Closing database connections is being a good database client.

Keep DB resources tied up with many open connections & you'll find yourself needing more vCPUs for your DB instance which then results in a higher RDS proxy price tag.

And if I should close the connection, then what's the point of using an RDS Proxy in the first place?

The point is that your Amazon RDS Proxy instance maintains a pool of established connections to your RDS database instances for you - it sits between your application and your RDS database.

The proxy is not responsible for closing local connections that you make nor should it be.

It is responsible for helping by managing connection multiplexing/pooling & sharing automatically for applications that need it.

An example of an application that needs it is clearly mentioned in the AWS docs:

Many applications, including those built on modern serverless architectures, can have a large number of open connections to the database server, and may open and close database connections at a high rate, exhausting database memory and compute resources.

To prevent any doubt, also feel free to check out an AWS-provided example that closes connections here (linked to from docs), or another one in the AWS Compute Blog here.

AUTOINCREMENT is not a valid option for CREATE TABLE in Postgres

You can use SERIAL or BIGSERIAL:

Instead of manually monitoring the DB health, as you have also hinted, ideally we subscribe to failover events published by AWS RDS Aurora.

There are multiple failover events listed here for the DB cluster: Amazon RDS event categories and event messages

You can use and test to see which one of them is the most reliable in your use case for triggering poolCluster.end() though.

Maybe a solution. Source : https://dba.stackexchange.com/questions/8239/how-to-easily-convert-utf8-tables-to-utf8mb4-in-mysql-5-5

Change your CHARACTER SET AND COLLATE to utf8mb4.

For each database:

This answer is accurate as of 19th January 2022.

Upon manual debug of this dataflow, I found that the issue is due to the dataflow job is looking for a schema with the exact same name as the value passed for the parameter databaseName and there was no other input parameter for the job using which we could pass a schema name. Therefore for this job to work, the tables will have to be created/imported into a schema with the same name as the database.

However, as @Iñigo González said this dataflow is currently in Beta and seems to have some bugs as I ran into another issue as soon as this was resolved which required me having to change the source code of the dataflow template job itself and build a custom docker image for it.

You can move database and filestore separately. Move your Odoo PostgreSQL database with normal Postgres backup/restore cycle (not the Odoo UI backup/restore), this will copy the database to your new server. Then move your Odoo filestore to new location as filesystem level copy. This is enough to get the new environment running.

I assume you mean moving to a new server, not just moving to a new location on same filesystem on the same server.