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Category: Cloud

Azure Redis Cache Geo-Replication

Arun Sirpal shows how to set up geo-replication in Azure Redis Cache:

The concept of a geo-replicated partnership between a primary and secondary node is very similar to that of something you may have seen with Azure SQL DB, where the primary handles all R/W and then the changes are pushed to secondary ( async). This is no different with Redis.

Read on to see what limitations exist and how you can set up geo-replication.

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Azure SQL DB ARM Template Conflicts with Azure AD Administration

Joao Antunes points out a potential timing issue around combining Azure Active Directory administration with Azure SQL Database ARM templates:

ARM templates are widely used when we need to repeatedly deploy solutions/infrastructures in the cloud. Leveraging the concept of infrastructure as code ARM templates are a powerful resource to ease our daily job, however we might face some challenges when using them.

When we are creating several resources within the same template – using Json or Bicep – it’s crucial to make sure that all resources are created in the right order, ensuring that all depending on resources are fully provisioned before you move to the next operation.

Error (internal server errors) and conflicts  can occur during our ARM template deployment and it could be difficult to troubleshoot or understand the root cause of them.

Read on for one annoying error and its fix.

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Data Products in Data Mesh

Paul Andrew takes us through a thought process:

In the context of an idealistic data mesh architecture, establishing a working definition of a data product seems to be very real problem for most. What constitutes a data product seems to be very subjective, circumstantial in terms requirements and interlaced with platform technical maturity. AKA, a ‘minefield’ to navigate in definitional terms.

To help get my thoughts in order (as always) here is my currently thinking and definition for a data mesh – data product.

Read on for Paul’s thoughts.

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Finding Azure SQL DB Backup History

Taiob Ali takes us through a new DMV:

There is a new DMV currently in preview which returns information about backups of Azure SQL databases except for the Hyperscale tier. Microsoft official documentation is here.

If you run the example query as-is from the above documentation some of the columns do not make sense.

Taiob includes a better query which provides the type of information you’re used to in on-premises SQL Server.

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Comparing Databricks to Synapse Spark Pools

Corrinna Peters makes comparisons:

There are different cases for using both depending on the specific needs and requirements, Synapse and Databricks are similar, but both have their own areas of specialities or rather areas where they are above the other.

Data Lake – they both allow you to query the data from the data lake, Synapse uses either the SQL on demand pool or Spark and Databricks uses the Databricks workspace once you have mounted the data lake. If you are predominately a SQL user and prefer the code and the BI developer feel then Synapse would be the correct choice whereas if you are a Data Scientist and prefer to code in Python or R then Databricks would feel more at home.

Read on for a nuanced take. My less nuanced take is, Databricks beats the pants off of Synapse Spark pools in terms of performance. Synapse has a much better overall ecosystem, expanding beyond Spark and into T-SQL (in two flavors) and log/event analytics with KQL. If you’re spending 100% of your time in Spark and don’t care about the rest, use Databricks; if Spark is a relatively small part of your warehousing work, use Synapse.

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Transparent Data Encryption in RDS

Tom Collins enables Transparent Data Encryption in AWS’s RDS:

Does AWS RDS SQL Server support built-in SQL Server Transparent Data Encryption (TDE)?  Yes , is the short answer , but there are some limitations  . 

Before I dive into the AWS SQL Server RDS TDW limitations , in this post  we’re discussing SQL Server TDE as opposed to RDS Encryption covering Aurora, MySQL, MariaDB, PostgreSQL, Oracle, SQL Server

Read on for the limitations Tom mentions.

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Using Extended Events with AWS RDS

Grant Fritchey tries out extended events in Amazon’s RDS:

AWS has posted the documentation on what you have to do in order to enable the collection of Extended Events within RDS. Normallly, I’d follow along with the documentation. However, I’m going to approach this like I knew that Extended Events support was there, but I wasn’t aware of the docs. So, I’m starting in SSMS and I’m just going to try plugging in the Extended Events GUI to see what happens. Further, I’m going to use the simplest method for launching Extended Events, XEvent Profiler. 

Read on for Grant’s findings.

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Alerting on Azure Budget Thresholds

Daron Yondem makes a budget:

You can’t imagine how many of us forget to set up the proper alerting mechanisms for our cloud subscription consumption. Here is how to do it in Azure in under 2 minutes.

Read on for the answer. I do like Azure’s budgeting tools except for one big thing: you can’t set a cap. Alerting is great but I want to have a “break glass in case of emergency” capability to stop spend altogether if you hit a certain point. I wouldn’t use it in production but for personal or development accounts, that’s big. And you can do it but only when you have a subscription which uses Azure credits—as soon as dollars are involved, there are no caps.

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Securing Azure Storage

Craig Porteous continues a series on Azure Data Platform security:

This is the third in a series where I look at all of the resources common to a Data Lakehouse platform architecture and what you need to think about to get it past your security team.

Building upon Azure Databricks, I’ll move from the compute engine to our blob and data lake storage. Things are a little simpler to secure but the plethora of options available can have significant impacts on usability and cost so it’s important to understand the impact before baking them into your design.

Read on for some good advice around securing Azure storage accounts.

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