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How to check your SQL Server Quota in Azure?

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New Microsoft Azure Certifications

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Microsoft Certification by Solution Area
Handy overview of the new Microsoft Azure Certifications.
More details can be found here

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Azure Purview Public Preview Starts billing

Billing for Azure Purview(Public Preview)As of January 20th 2021 0:00 UTC Azure Purview will starts billing.Preview From January 20 ,2021 Azure Purview will start billing. During the Public Preview, you will only be billed if you exceed the 4 capacity units for Azure...

10 Days of Azure Synapse Analytics

10 Days of Azure Synapse AnalyticsFor the next 10 days, every day a different topic is explained about Azure Synapse Analytics. The shortest and easiest way to see how Azure Synapse Analytics can help you, to make decisions within your data landscape.Day 1...

Calculate the Last Day of the Month using SQL

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Enable Pattern Rules in Azure Purview

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SQLBits session: Microsoft Purview Data Policy App

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Azure Purview MSIgnite Spring 2021 Announcements

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Custom comments in Azure Synapse Analytics

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Parameterize Linked Services in ADF

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Azure SQL Data Warehouse: How to setup Reserved Capacity

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Purchase your Azure SQL Datawarehouse Reservation

Since a few weeks you can buy Reserved Capacity for an Azure SQL Datawarehouse (SQLDW). This Reservation can save you up to 65% on the normal Pay as You go rates with a 3 year pre-commit. A pre-commit of 1 year will be discounted up to 35%.
These savings will only effect the compute power. You will charged separately for the storage with the normal Pay as You go rates.
To purchase a reservation, you need to sign-in to the Azure Portal first and then search for reservations.

After you have clicked on Purchase Now, you will need to choose the Azure SQLDW option.

Select the Region, be aware that if you want to run Several SQLDW’s (Dev/Test/Prod) and you want to make use of the benefits of the reserved capacity that these SQLDW’s must all be created in the Region in which the reservation is made.
When you’re running a Enterprise Subscription and you have more then 1 Subscription you can change the Scope to “Shared”. With this option selected you can use the Reserved Capacity across all subscription within the same EA Enrollment.

Select 1 or 3 year Term.

Choose a quantity. The reserved capacity is calculated by 100 cDWU(Data Warehouse units). Choose the quantity you want to reserved. In case you select 5 cDWU, you will have 500 cDWU of reserved capacity every hour.

The last step is to Purchase your Reservation.

Reserved Capacity nice to know’s
Storage and Network are charged separately, for these Azure Services the Reserved Capacity Discount will not be applied.
The Reserved Capacity Discount is applied on running Azure SQLDW Instances on a hourly basis.
If you don’t have a Azure SQLDW Instance deployed for an hour, then the reserved capacity is wasted for that hour. It doesn’t carry over. Unless you have more then 1 Azure SQLDW Instance running, the reservation is automatically applied to other matching instances in that hour.
Some Examples:
1 – Running 1 Azure SQLDW Instance:
You have purchased 5 units of 100 cDWU.
On the moment you scale to 1000 cDWU, you will be charged with a Pay as You go rates for 700 cDWU.
2 – Running 2 Azure SQLDW Instances:
You have purchased 15 units of 100 cDWU.
1 Azure SQLDW Instance is running 500 cDWU and the other one 1000 cDWU.
No extra cost will be applied.
3 – Running 2 Azure SQLDW Instances:
You have purchased 15 units of 100 cDWU.
1 Azure SQLDW Instance is running 500 cDWU from 9 am to 5 pm and the other one 1500 cDWU the whole day.
You will be charged for a Pay as You go rates for 500 cDWU from 9 am to 5 pm.

Thank you for reading this article and hopefully it will make things clear to you.
Within a few days I will publish a new article in which I describe how much you could possibly save if you still want to scale up or down during certain periods of the day. If there are any questions left about this article, don’t hesitate to ask them to me.
UPDATE 6th May
Reserved Capacity versus Pas as You go
Azure SQL Data Warehouse: How to setup Reserved Capacity

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Azure SQL Data Warehouse: Reserved Capacity versus Pay as You go

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How do I use my Reserved Capacity correctly?
Update 11-11-2020: This also applies to Azure Synapse SQL Pools.
In my previous article you were introduced, how to create a Reserved Capacity for an Azure SQL Datawarehouse (SQLDW). Now it’s time to take a look at how this Reserved Capacity differs from an already working environment with an Azure SQLDW Pay as You go model where we already scale up and down during certain time periods.

In the example below I’m running an Azure SQLDW with the following capacity during the day.

Weekdays:

12:00 AM
4:00 AM
100 cDWU

5:00 AM
7:00 AM
3000 cDWU

8:00 AM
6:00 PM
1500 cDWU

7:00 PM
12:00 AM
100 cDWU

Weekenddays:

12:00 AM
4:00 AM
100 cDWU

5:00 AM
7:00 AM
3000 cDWU

8:00 AM
6:00 PM
500 cDWU

7:00 PM
12:00 AM
100 cDWU

We have separated the weekdays from the weekend days. The SQLDW is used less heavily during the weekend than during the week.
In our calculation we assume that we will purchase a Reserved Capacity of 3 years with 15 units of 100 cDWU. On the left site you will see the Pay as You go model and on the right site the Reserved Capacity.
The amount of Storage will be 8 TB.
As you can see in the example below.

Conclusions:
In the example we see that we have to pay extra if we exceed our Reserved Capacity. These extras are billed with the normal Pay as You go rate.

If we use the Reserved Capacity, we have 1500 cDWU available throughout the day so we don’t longer need to turn it off or scale it down during weekends or outside office hours. Otherwise the Reserved Capacity is wasted for that hour, it doesn’t carry over.
So we actually get more capacity and we pay less for it, sounds great or not! More details can be found here.

In this example, we save nearly 2,750 euros a month, which is almost 33,000 euros a year and 100,000 euros during the 3-year Reserved Capacity period. And that is a considerable amount that you can use to develop new solutions.

Reserved Capacity
Years
Discount
Month
Year
Total Period

Reserved Capacity
Year
Discount
month
year
Total Period

1500 cDWU
3
65
2742
32914
98739,648

1500 cDWU
1
35
-2319,41
-27832,9
-27832,896

1000 cDWU
3
65
2261,952
27143,42
81430,272

1000 cDWU
1
35
-1112,83
-13354
-13353,984

In this situation we achieve the largest saving with 1500 cDWU with a Reservation of 3 years. When purchasing 10 units of 100 cDWU, we still save but slightly less. When purchasing Reserved Capacity for 1 year, a Pay as You go model will be cheaper.

Calculation Sheet
Since every situation is different, you will have to play with these quantities/units yourself. I have added the Excel form so that you can download it, on which I have based this article. With this form you can fill in your own situation as well as possible. And finally you can take your own conclusions for your customer or environment.

In the sheet only change the Green Marked cells. Prices are in Euro’s.

SQLDWH_-_pay-as-you-go_vs_reservedcapcity

This form has been created together with my colleague Maurice Veltman and we have used it for a solid calculation for 1 of our customers.

If you have any questions or comments about this article or the form, just let me know.

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SSMS 18.1: Schedule your SSIS Packages in Azure Data Factory

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Schedule your SSIS Packages with SSMS in Azure Data Factory(ADF)
This week SQL Server Management Studio version 18.1 was released, which can be downloaded from here.
In version 18.1 the Database diagrams are back and from now on we can also schedule SSIS Packages in ADF via SSMS.

Select the package you want to schedule in your Integration Services Catalog,

Create the schedule you want to create and click on OK.
Your schedule will be created in Azure Data Factory.

Azure Data Factory
In Azure Data Factory a pipeline and trigger are created automatically

Azure Dev Ops
Scheduling your SISS packages is not working fine when you have Azure Dev Ops Enabled. Pipeline and Trigger are published to the Data Factory instead of Azure DevOps GIT as you can see below.
My advice will be to build your schedule/trigger directly in Azure Data Factory when you ‘re using Azure Dev Ops.

In case you have any questions left, do not hesitate to ask them. I’m more then happy to answer them.

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