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Category: Cloud

Event Hub Performance Tips

Published 2018-06-07 by Kevin Feasel

Vincent-Philippe Lauzon has a few tips for improving Azure Event Hub performance:

Here are some recommendations in the light of the performance and throughput results:

  • If we send many events:  always reuse connections, i.e. do not create a connection only for one event.  This is valid for both AMQP and HTTP.  A simple Connection Pool pattern makes this easy.
  • If we send many events & throughput is a concern:  use AMQP.
  • If we send few events and latency is a concern:  use HTTP / REST.
  • If events naturally comes in batch of many events:  use batch API.
  • If events do not naturally comes in batch of many events:  simply stream events.  Do not try to batch them unless network IO is constrained.
  • If a latency of 0.1 seconds is a concern:  move the call to Event Hubs away from your critical performance path.

Let’s now look at the tests we did to come up with those recommendations.

Read the whole thing.

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Databricks MLflow

Published 2018-06-06 by Kevin Feasel

Matai Zaharia announces a new Databricks offering:

MLflow is inspired by existing ML platforms, but it is designed to be open in two senses:

  1. Open interface: MLflow is designed to work with any ML library, algorithm, deployment tool or language. It’s built around REST APIs and simple data formats (e.g., a model can be viewed as a lambda function) that can be used from a variety of tools, instead of only providing a small set of built-in functionality. This also makes it easy to add MLflow to your existing ML code so you can benefit from it immediately, and to share code using any ML library that others in your organization can run.
  2. Open source: We’re releasing MLflow as an open source project that users and library developers can extend. In addition, MLflow’s open format makes it very easy to share workflow steps and models across organizations if you wish to open source your code.

Mlflow is still currently in alpha, but we believe that it already offers a useful framework to work with ML code, and we would love to hear your feedback. In this post, we’ll introduce MLflow in detail and explain its components.

Even in alpha, it looks nice.

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The Basics Of Azure Stream Analytics

Published 2018-06-06 by Kevin Feasel

Chris Seferlis gives us an overview of Azure Stream Analytics:

Here’s how it works. It starts with a data source such as Event Hub, IoT Hub or Azure Blob Storage, and it uses SQL-like query language that allows transformation on the fly. It helps you process operations like filtering, sorting, aggregating and joining the data together to make it more useable—turning data into information.

From there, when you identify the data that you want/need to use, you can then send that data downstream to be sent to a queue for triggering workflows or further processing of the data. You can also send that data to Power BI for real-time visualization. For example, let’s say you’re looking at a data quality stream and you want to pull certain key words out of Twitter to see how they’re used and watch how that’s being done. By connecting to the Twitter API, you can capture that data, stream it, and then report from it with a Power BI report.

Chris also has a video which you can watch.

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Lookups And Conditionals In Azure Data Factory V2

Published 2018-06-06 by Kevin Feasel

Alex Whittles shows us how to perform lookups and operations with IF clauses in Azure Data Factory V2:

Azure Data Factory v2 (ADFv2) has some significant improvements over v1, and we now consider ADF as a viable platform for most of our cloud based projects. But things aren’t always as straightforward as they could be. I’m sure this will improve over time, but don’t let that stop you from getting started now.

This post provides a walk through of using the ‘Lookup’ and ‘If Condition’ activities to do some basic conditional logic depending on the results of a database query.

Assumptions: You already have an ADF pipeline created. If you want to hook into SSIS then you’ll also need the SSIS Integration Runtime set up – although this is not relevant just for the if condition.

Read on for an example.

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Connecting To Azure SQL Database From On-Prem

Published 2018-06-06 by Kevin Feasel

Arun Sirpal shows how to set up a linked server instance between an on-prem SQL Server instance and Azure SQL Database:

You may (or may not) have a requirement to setup a linked server to Azure SQL Database from a locally installed SQL Server. One reason could be to pull down some reports from an Azure SQL Database to a local file share. Whatever your reason is hopefully you will find this blog post useful because I ran into some complications on the way.

This is what your linked server creation screens in SSMS (SQL Server Management Studio) should look like.

Take advantage of Arun’s hard-earned experience and read his post.

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Resizing Azure Managed Instances

Published 2018-06-01 by Kevin Feasel

Jovan Popovic shows how to resize Azure SQL managed instances with Powershell:

Azure SQL Managed Instance is fully-managed SQL Server Database Engine hosted in Azure cloud. With Managed Instance you can easily add/remove cores associated to the instance and change the reserved size of the instance. You can use PowerShell to easily manage size of the instance and automate this process.

As a prerequisite, you need to have Azure SQL PowerShell libraries to configure Managed Instance. You would need to install Azure RM PowerShell and  AzureRm.Sql module that contains the commands for updating properties of Managed Instance.

Read on for a demo.

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Azure Data Factory V2 Pricing

Published 2018-05-29 by Kevin Feasel

Chris Seferlis gives us the details on how Azure Data Factory V2 pricing works:

2. Volume of data moved – this is measured in DMUs (data movement units). This is one you should be aware of as this will default to auto, which is basically using all the DMUs it can use and this is paid for by the hour. Let’s say you specify and use 2 DMUs and it takes an hour to move that data. The other option is you could use 8 DMUs and it takes 15 minutes, this price is going to end up the same. You’re using 4X the DMUs but it’s happening in a quarter of the time.

This is good to look at and do some comparisons since how many DMUs you’re using is where the bulk of your spend if going to be.

There are a few moving parts here, so the calculation is not trivial.  But Chris makes good sense of it all.

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Picking An Azure SQL Database Tier

Published 2018-05-25 by Kevin Feasel

Esat Erkec has various methods you can use to figure out your Azure SQL Database tier:

When we are beginning to think of migrating our on-premises databases to Azure SQL, we have to decide on a proper purchase model, a service tier, and a performance level. Before starting the Azure SQL migration process, we have to find logical and provable answers to the following questions:

  • Which purchase model is suitable for my apps and business requirements?
  • How much budget do I need?
  • Which performance level meets my requirements?
  • Can I achieve the acceptable performance of my apps?

The purchase model and service tiers will certainly affect the Azure bills. On the other hand, we have to achieve the maximum performance with the selected service tier.

It’s a good article with helpful tips for people thinking of moving to Azure SQL Database.

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Gartner’s Cloud IaaS Magic Quadrant Changes

Published 2018-05-25 by Kevin Feasel

Bruno Aziza analyzes Gartner’s Magic Quadrant for Cloud Infrastructure as a Service offerings:

The first and most drastic change that occurred over the last year is the number of players that Gartner decided to highlight in its report: the number of vendors went from 14 to just 6 this year.  

Why is that?! Have the big become bigger and the small smaller?! Or has the space shrunk?   The latter is highly improbable.  All the contrary: earlier last year, forecasted that the highest growth in the cloud market would be coming from the sector this MQ covers: Gartner predicted that the cloud system infrastructure services would grow over 36% to reach $34B+ in 2017.

So, what gives?!

Read on to learn what gives.  As far as the rankings themselves go, I think it’s reasonable:  AWS and Azure can generally go head-to-head on features though Amazon does have the advantage.  Google is a distant third and the rest aren’t major players.

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Don’t Forget Those Paused Indexes

Published 2018-05-23 by Kevin Feasel

Arun Sirpal tries to create a new index on his Azure SQL Database:

I was creating some demo non-clustered indexes in one of my Azure SQL Databases and received the following warning when I executed this code:

CREATE NONCLUSTERED INDEX [dbo.NCI_Time]
ON [dbo].[Audit] ([UserId])
INCLUDE ([DefID],[ShopID])

Msg 10637, Level 16, State 3, Line 7

Cannot perform this operation on ‘object’ with ID 1093578934 as one or more indexes are currently in resumable index rebuild state. Please refer to sys.index_resumable_operations for more details.

How intriguing!

Fortunately, the error message is clear and helpful, two terms which rarely go in conjunction with “error message.”

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