@Scott Davies here's my understanding, based on what you've described: - because you have ONE F64 capacity, then it will act like any other capacity and be throttled if you go above the thresholds. You won't be charged more - your reservation should cover it, because you have only got an F64. - if you were to have an F64 and an F4, then you'd pay extra for the F4 (because you're using equivalent of F68

@Scott Davies So they are saying you won't experience throttling when you have a capacity reservation? Hmm, I'm not sure that's correct tbh 🤔 my understanding is that throttling works the same regardless of whether you have capacity reservation. You pay PAYG rates for any total SKU over your overage. e.g. if you have an F64 active at the same time as an F8, you'll PAYG the F8 PAYG rate - both the F64 and F8 experience the same throttling thresholds as a traditional PAYG capacity. I could be wrong though 😂

Hi there @Nikolay Tuschiev - yes i've done quite a bit with all of these things. Fabric CICD is useful is your targeting Option 2 from Microsoft's CICD options - where you want/ need explicit build and release steps and you need to do the parameter substitution in the build step. If you don't need a build step, I like using Variable Libraries with the notebookutils library. Plus now they support SPN. For migrations, if you're using Data Warehouse, you can use the SQL Database Project (DACPAC), otherwise it's likely you'll have to build your own migration scripts and deploy them with your Lakehouse 👍 I think they're working on improving the deployment of Lakehouse items, but currently it's very limited.

Great to have you here @Nyashadzaishe Mazhindu

@Azra Tuni Welcome Azra!!

Excellent work - well done @Saleem Mirza !!

@Amier musstaqim Sawalludin I don't think there's a unified logging solution yet in Fabric. There is the Monitor tab which shows the basics (each run is monitored and you can see the status of all jobs in fabric). I think what you're asking about is more of a custom solution. What I tend to do is create a separate Lakehouse to write custom logs to. It you want to maintain the raw JSON for a log, point it to the Lakehouse Files area, and then you might want to try/ take a look at the new Shortcut File Transformations which autoconverts the JSON into a structured delta table. That feature is in Preview still though, so be careful with it.

@Amier musstaqim Sawalludin Normally, I just create a custom python function that captures the details I want to log, and add it into each notebook I use!