A Fine Slice Of SQL Server
Dany Hoter performs some troubleshooting:
A customer approached me and complained that a page in a PBI report was taking a very long time to refresh. (> 100 seconds)
An investigation showed that one chart was sending 273 queries to the ADX cluster.
Was it a coincidence that the chart showed a distinct count of customers in each one of 273 points of sale?
Spoiler: no, no it wasn’t.
Comments closedKumar Ashwin Hubert and Rajesh Singh share an architecture with us:
This reference architecture describes the deployment of secured Azure Container Registry for consuming docker images and artifacts by customer applications over external (public internet) network.
This architecture builds on Microsoft’s recommended security best practices to expose private applications for external access. It utilizes the ACR’s token and scope map feature to provide granular access control to ACR’s repositories. Also, ACR internally uses the Docker APIs, and it is recommended to be familiar with these concepts before deploying this architecture.
I think this is a great example of the good and the bad of Azure architectures. The good is that you get a thoughful, well-explained, thorough description of the services you need and how they fit together, and there are a lot of those in the Azure Architecture Center. The bad is that, if I want to secure one container registry, I need a dozen different services. If we didn’t have this particular architecture diagram, I doubt 1 in 50 cloud specialists would come up with all of these services.
Comments closedKendra Little provides some guidance:
Whether or not you use Azure SQL Managed Instance, you will likely be asked for an opinion on it eventually if you’re a SQL Server person.
While the architecture is documented, it can be a bit of a long read and some of the gotchas are spread out over different pages – so I’m drawing up the architecture of each service tier along with notable implications for the design on performance and cost. Here’s the scoop on General Purpose.
Click through for Kendra’s thoughts.
Comments closedDavid Klee offers up some advice:
You might be able to shave off thousands – or more – in your monthly cloud bills for your critical SQL Servers, all while maintaining or even improving performance.
Public cloud providers charge organizations for everything they deploy, and while a few items in the cloud are based on a pay-by-consumption model, most of the services that really stack up, namely SQL Server licensing, are charged on a pay-by-allocation model. If you provision a SQL Server VM with eight cores and promptly forget about it, you will be shocked at the end of the month when you receive your cloud subscription bill. If you provision a 32-core VM, and your workload only uses four cores, you are still paying for all 32 cores, regardless of the low utilization rates. The same goes for memory and storage. A large memory footprint and lots of high-speed attached managed disks all add up.
Read on for some advice around figuring out the right server size for your workload.
Comments closedThe most popular feature in any application is an easy-to-find button saying “Export to CSV.” If this button is not visibly available, a simple right-click of your mouse should present such an option. You really should not be forced to spend any additional time on this Earth looking for a way to export your data to a CSV file.
Well, in Azure ML Studio, exporting to a CSV file should be simple, but is not, unless you already know what you are doing and where to look. I was reminded of this recently, and decided to write a quick post in case a person new to ML Studio was wondering how to export data to a CSV file.
Click through for one false start and then the correct answer.
Comments closedDaniel Hutmacher saves a buck:
R2 is Cloudflare’s own implementation of AWS S3 storage, with some big benefits – one of them being no egress fees, which is great if you want to publish or distribute a lot of data (like I did with this demo database). In this post, I thought I’d briefly document how to set up R2, and how to use it to back up and restore your SQL Server databases.
You’ll need a Cloudflare account to follow along. The account and a lot of their services are free, but R2 storage obviously comes with a small cost. For scale, I’m running an almost-terabyte bucket at just a couple of dollars per month.
Given the number of times I’ve pushed Daniel’s excellent Chicago parking tickets database (including right now—it’s a great database that I’ve used in several presentations and videos!), the lack of egress charges is pretty big.
Comments closedTom LaRock shows us where the hidden data is:
Recently I was working inside of Azure ML Studio and wanted to browse the sample datasets provided. Except I could not find them. I *knew* they existed, having used them previously, but could not remember if that was in the original ML Studio (classic) or not.
After some trial and error, I found them and decided to write this post in case anyone else is wondering where to find the sample datasets. You’re welcome, future Tom!
Click through to see where those sample datasets are. And yeah, they don’t get updated that frequently. And that’s probably a good thing, as it means when you run the demo two years after someone created it, you’ll still get predictable results.
Comments closedReitse Eskens enters austerity mode:
If you’ve been having fun with Microsoft Fabric, chances are you’ve been playing around with the F64 capacity trial. This one is given to you by Microsoft for free but, since the GA data, the timer attached to it is counting down the days until you need to buy your own.
Read on to see what happens when you lose out on that sweet F64 goodness. I actually do appreciate the way that Fabric works: it’s not a linear scale of “F2 means you get 1/32 the processing power of F64.” Rather, it’s closer to time slices on a mainframe: F64 gets you a bigger slice. So if you’re a small shop without an enormous amount of data, F2 really does work pretty well.
Comments closedDustin Vannoy has an updated video:
This is an updated video and writeup on setting up and using Log Analytics with your Azure Databricks logs. Some of the content overlaps with what I shared in the past, but these instructions are valid for Databricks Runtimes 11.3+.
Read on for notes, demo data, and instructions on how to follow along.
Comments closedAWS has notified customers of its Amazon Aurora Serverless v1 service that it will cease supporting the offering at the end of 2024. Replacing v1 in the Aurora Serverless range, which supports Postgres and MySQL databases, will be v2, which offers some advantages but also one big disadvantage: It doesn’t scale all the way down to zero.
Click through for more information.
Comments closed