Comment by arjonagelhout
2 months ago
A little while back, I had a conversation with a colleague about sorting entries by "updated at" in the user interface, and to my surprise this was not added by the backend team.
Many of these "we are going to need it"s come from experience. For example in the context of data structures (DS), I have made many "mistakes" that I do correctly a second time. These mistakes made writing algorithms for the DS harder, or made the DS have bad performance.
Sadly, it's hard to transfer this underlying breadth of knowledge and intuition for making good tradeoffs. As such, a one-off tip like this is limited in its usefulness.
Database schemas being perfect out-of-the gate was replaced by reliable migrations.
If it's not data that's essential to serving the current functionality, just add a column later. `updated_at` doesn't have to be accurate for your entire dataset; just set it to `NOW()` when you run the migration.
Sure, migrations are bearable (especially ones that only add columns).
But for the example of the "updated_at" column, or "soft delete" functionality, you only find out you need it because the operations team suddenly discovered they needed that functionality on existing production rows because something weird happened.
In C#-land, we just have it as a standard that ~every table inherits from `ITrackable`, and we wrote a little EF plugin to automatically update the appropriate columns.
public interface ITrackable { DateTime CreatedOn {get; set;} DateTime ModifiedOn {get; set;} }
Saves so much time and hassle.
“Reliable migrations” almost seems like an oxymoron. Migrations are complicated, difficult and error prone. I think there’s a good takeaway here around good initial schema design practices. The less you have to morph your schema overtime, the less of those risky migrations need to run.
My experience over the last decade has been different.
Use a popular framework. Run it against your test database. Always keep backups in case something unforseen happens.
Something especially trivial like adding additional columns is a solved problem.
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Still depends on what the data represent: you could get yourself in a storm of phone calls from customers if after your latest release there's now a weird note saying their saved document was last updated today.
"HOW DARE YOU MODIFY MY DOCUMENTS WITHOUT MY..."
Somewhat related, but I suggest having both the record updated at, and some kind of "user editing updated at". As I've encountered issues where some data migration ends up touching records and bumping the updated at, which shocks users since they see the UI reshuffle and think they have been hacked when they see the records updated at a time they didn't update them.
I mean this is what audit logs are for I'd say: generally speaking you want to know what was changed, by who and why.
So really you probably just want a reference to the tip of the audit log chain.