Azure Storage

Shared Storage Options in Azure: Part 2 – IaaS Storage Server

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Recently, I posted the “Shared Storage Options in Azure: Part 1 – Azure Shared Disks” blog post, the first in the 5-part series. Today I’m posting Part 2 – IaaS Storage Server. While this post will be fairly rudimentary insofar as Azure technical complexity, this is most certainly an option when considering shared storage options in Azure and one that is still fairly common with a number of configuration options. In this scenario, we will be looking at using a dedicated Virtual Machine to provide shared storage through various methods. As I write subsequent posts in this series, I will update this post with the links to each of them.

 

Virtual Machine Configuration Options:

Compute:

While it may not seem vitally important, the VM SKU you choose can impact your ability to provide storage capabilities in areas such as Disk Type, Capacity, IOPS, or Network Throughput. You can view the list of VM SKUs available on Azure at this link. As an example, I’ve clicked into the General Purpose, Dv3/Dvs3 series and you can see there are two tables that show upper limits of the SKUs in that family.

VM SKU Sizes in Azure

VM Performance Metrics in Azure

In the limits for each VM you can see there are differences between Max Cached and Temp Storage Throughput, Max Burst Cached and Temp Storage Throughput, Max uncached Disk Throughput, and Max Burst uncached Disk Throughput. All of these represent very different I/O patterns, so make sure to look carefully at the numbers.

Below are a few links to read more on disk caching and bursting:

 

You’ll notice when you look at VM SKUs that there is an L-Series which is “storage optimized”. This may not always be the best fit for your workload, but it does have some amazing capabilities. The outstanding feature of the L-Series VMs are the locally mapped NVMe drives which as of the time of writing this post on the L80s_v2 SKU can offer 19.2TB of storage at 3.8 Million IOPS / 20,000 MBPS.

Azure LS Series VM Specs

The benefits of these VMs are the extremely low latency, and high throughput local storage, but the caveat to that specific NVMe storage is that it is ephemeral. Data on those disks does not persist a reboot. This means it’s incredibly good at serving from a local cache, tempdb files, etc. though its not storage that you can use for things like a File Server backend (without some fancy start-up scripts, please don’t do this…). You will note that the maximum uncached throughput is 80,000 IOPS / 2,000 MBPS for the VM, which is the same as all of the other high spec VMs. As I am writing this, no Azure VM allows for more than that for uncached throughput – this includes Ultra Disks (more on that later).

For more information on the LSv2 series, you can read more here: Lsv2-series – Azure Virtual Machines | Microsoft Docs

Additional Links on Azure VM Storage Design:

Networking:

Networking capabilities of the Virtual Machine are also important design decisions when considering shared storage, both in total throughput and latency. You’ll notice in the VM SKU charts I posted above when talking about performance there are two sections for networking, Max NICs and Expected network bandwidth Mbps. It’s important to know that these are VM SKU limitations, which may influence your design.

Expected network bandwidth is pretty straight forward, but I want to clarify that the number of Network Interfaces you mount to a VM does not change this number. For example, if your expected network bandwidth is 3200 Mbps and you have an SMB share running on that single NIC, adding a second NIC and using SMB multi-channel WILL NOT increase the total bandwidth for the VM. In that case you could expect each NIC to potentially run at 1,600 Mbps.

The last networking feature to take into consideration is Accelerated Networking.  This feature allows for SR-IOV (Single Root I/O Virtualization), which by bypassing the host CPU and offloading the network traffic directly to the Network Interface can dramatically increase performance by reducing latency, jitter, and CPU utilization.  

Accelerated Networking Comparison in Azure

Image Reference: Create an Azure VM with Accelerated Networking using Azure CLI | Microsoft Docs  

Accelerated Networking is not available on every VM though, which makes it an important design decision. It’s available on most General Purpose VMs now, but make sure to check the list of supported instance types. If you’re running a Linux VM, you’ll also need to make sure it’s a supported distribution for Accelerated Networking.  

Storage:

In an obvious step, the next design decision is the storage that you attach to your VM. There are two major decision types when selecting disks for you VM – disk type, and disk size.

Disk Types:

Azure VM Disk Types

Image Reference: https://docs.microsoft.com/en-us/azure/virtual-machines/disks-types  

As the table above shows, there are three types of Managed Disks (https://docs.microsoft.com/en-us/azure/virtual-machines/managed-disks-overview ) in Azure. At the time of writing this, Premium/Standard SSD and Standard HDD all have a limit of 32TB per disk. The performance characteristics are very different, but I also want to point out the difference in the pricing model because I see folks make this mistake very often.  

Disk Type: Capacity Cost: Transaction Cost:
Standard HDD Low Low
Standard SSD Medium Medium
Premium SSD High None
Ultra SSD Highest (Capacity/Throughput) None

Transaction costs can be important on a machine whose sole purpose is to function as a storage server. Make sure you look into this before a passing glance shows the price of a Standard SSD lower than a Premium SSD. For example, here is the Azure Calculator output of a 1 TB disk across all four types that averages 10 IOPS * ((10*60*60*24*30)/10,000) = 2,592 transaction units.

Sample Standard Disk Pricing:

Azure Calculator Disk Pricing  

 

Sample Standard SSD Pricing:

Azure Calculator Disk Pricing  

Sample Premium SSD Pricing:

Azure Calculator Disk Pricing

Sample Ultra Disk Pricing:

Azure Calculator Disk Pricing

 

The above example is just an example, but you get the idea. Pricing gets strange around Ultra Disk due to the ability to configure performance (more on that later). Though there is a calculable break-even point for disks that have transaction costs versus those that have a higher provisioned cost.

For example, if you run an E30 (1024 GB) Standard SSD at full throttle (500 IOPS) the monthly cost will be ~$336, compared to ~$135 for a P30 (1024 GB) Premium SSD, with which you get x10 the performance. The second design decision is disk capacity. While this seems like a no-brainer (provision the capacity needed, right?) it’s important to remember that with Managed Disks in Azure, the performance scales with, and is tied to, the capacity of the disk.

Image Reference: https://docs.microsoft.com/en-us/azure/virtual-machines/disks-types#disk-size-1

You’ll note in the above image the Disk Size scales proportionally with both the Provisioned IOPS and Provisioned Throughput. This is to say that if you need more performance out of your disk, you scale it up and add capacity.

The last note on capacity is this, if you need more than 32TB of storage on a single VM, you simply add another disk and use your mechanism for combining that storage (Storage Spaces, RAID, etc.). This same method can be used to further tweak your total IOPS, but make sure you take into consideration the cost of each disk, capacity, and performance before doing this – most often it’s an insignificant cost to simply scale-up to the next size disk. Last but not least, I want to briefly talk about Ultra Disks – these things are amazing!

Ultra Disk Configuration in Azure

Unlike with the other disk types, this configuration allows you to select your disk size and performance (IOPS AND Throughput) independently! I recently worked on a design where the customer needed 60,000 IOPS, but only needed a few TB of capacity, this is the perfect scenario for Ultra Disks. They were actually able to get more performance, for less cost compared to using Premium SSDs.

To conclude this section, I want to note two design constraints when selecting disks for your VM.

  1. The VM SKU is still limited to a certain number of IOPS, Throughput and Disk Count. Adding together the total performance of your disks, cannot exceed the maximum performance of the VM. If the VM SKU supports 10,000 IOPS and you add 3x 60,000 IOPS Ultra Disks, you will be charged for all three of those Ultra Disks at their provisioned performance tiers but will only be able to get 10,000 IOPS out of the VM.
  2. All of the hardware performance may still be subject to the performance of the access protocol or configuration, more on this in the next section.

Additional Reading on Storage:

 

Software Configuration and Access Protocols:

As we come to the last section of this post, we get to the area that aligns with the purpose of this blog series – shared storage. In this section I’m going to cover some of the most common configurations and access types for shared storage in IaaS. This is by no means an exhaustive list, rather what I find most common.

Scale-Out File Server (SoFS):

First up is Sale-Out File Server, this is a software configuration inside Windows Server that is typically used with SMB shares. SoFS was introduced in Windows 2012, uses Windows Failover Clustering, and is considered a “converged” storage deployment. It’s also worth noting that this can run on S2S (Storage Space Direct), which is the method I recommend using with modern Windows Server Operating Systems. Scale-Out File Server is designed to provide scale-out file shares that are continuously available for file-based server application storage. It provides the ability to share the same folder from multiple nodes of the same cluster. It can be deployed in two configuration options, for Application Data or General Purpose. See the additional reading below for the documentation on setup guidance.

Additional reading:

SMB v3:

Now into the access protocols – SMB has been the go-to file services protocol on Windows for quite some time now. In modern Operating Systems, SMB v3.* is an absolutely phenomenal protocol. It allows for incredible performance using things like SMB Direct (RDMA), Increasing MTU, and SMB Multichannel which can use multiple NICs simultaneously for the same file transfer to increase throughput. It also has a list of security mechanisms such as Pre-Auth Integrity, AES Encryption, Request Signing, etc. There is more information on the SMB v3 protocol below, if you’re interested, or still think of SMB in the way we did 20 years ago – check it out. The Microsoft SQL Server team even supports SQL hosting databases on remote SMB v3 shares.

Additional reading:

NFS:

NFS has been a similar staple as a file server protocol for a long while also, and whether you’re running Windows or Linux can be used in your Azure IaaS VM for shared storage. For organizations that prefer an IaaS route compared to PaaS, I’ve seen many use this as a cornerstone configuration for their Azure Deployments. Additionally, a number of HPC (High Performance Compute) workloads, such as Azure CycleCloud (HPC orchestration) or the popular Genomics Workflow Management System, Cromwell on Azure prefer the use of NFS.

Additional Reading:

iSCSI:

While I would not recommend the use of custom block storage on top of a VM in Azure if you have a choice, some applications do still have this requirement in which case iSCSI is also an option for shared storage in Azure.

Additional Reading:

That’s it! We’ve reached the end of Part 2. Okay, here we go with the Pros and Cons for using an IaaS Virtual Machine for your shared storage configuration on Azure.

Pros and Cons:

 

Pros:

  • More control, greater flexibility of protocols and configuration.
  • Depending on the use case, potentially greater performance at a lower cost (becoming more and more unlikely).
  • Ability to migrate workloads as-is and use existing storage configurations.
  • Ability to use older, or more “traditional” protocols and configurations.
  • Allows for the use of Shared Disks.

Cons:

  • Significantly more management overhead as compared to PaaS.
  • More complex configurations, and cost calculations compared to PaaS.
  • Higher potential for operational failure with the higher number of components.
  • Broader attack surface, and more security responsibilities.

  Alright, that’s it for Part 2 of this blog series – Shared Storage on IaaS Virtual Machines. Please reach out to me in the comments, on LinkedIn, or Twitter with any questions about this post, the series, or anything else!

 

Shared Storage Options in Azure: Part 1 – Azure Shared Disks

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In an IaaS world, shared storage between virtual machines is a common ask. “What is the best way to configure shared storage?”, “What options do we have for sharing storage between these VMs?”, both are questions I’ve answered several times, so let’s go ahead and blog some of the options! The first part in this blog series titled “Shared Storage Options in Azure”, will cover Azure Shared Disks.

As I write subsequent posts in this series, I will update this post with the links to each of them.

 

When shared disks were announced in July of 2020, there was quite a bit of excitement in the community. There are so many applications that still leverage shared storage for things like Windows Server Failover Clustering, on which many applications are built like SQL Server Failover Cluster Instances. Also, while I highly recommend using a Cloud Witness, many customers migration workloads to Azure still rely on a shared disk for quorum as well. Additionally, many Linux applications leverage shared storage that were previously configured to use a shared virtual disk, or even RAW LUN mappings, for applications such as GFS2 or OCFS2.

Additional sample workloads for Azure Shared Disks can be found here: Shared Disk Sample Workloads.

There are a few limitations of shared disks, the list of which is constantly getting smaller. For now, though, let’s just go ahead and jump into it and see how to deploy them. After which, we’ll do a quick “Pros” and “Cons” list before moving on to the other shared storage options. I deployed Shared Disks in my lab using the portal first (screenshots below), but also created a Github Repository (https://github.com/matthansen0/azure-shared-storage-options) with the Azure PowerShell script and an ARM template to deploy a similar environment – feel free to use those if you’d like!

As a prerequisite (not pictured below) I created the following resources:

  • A Resource Group in the West US region
  • A Virtual Network with a single subnet
  • 2x D2s v3, Windows Server 2016 Virtual Machines (VM001, VM002) each with a single OS disk

Now that those are created, I deployed a Managed Disk (named “sharedDisk001”) just like you would if you were deploying a typical data disk.

On the “advanced” tab you will see the ability to configure the managed disk as a “shared disk”, here is where you set the max shares which specifies the maximum number of VMs that can attach that particular disk type.

After the disk is finished deploying, we head over to the first VM and attach an existing disk. You’ll note that the disk shows up as a “shared disk” and shows the number of shares left available on that disk. Since this is the first time it’s being mounted it shows 0.

After attaching the disk to the first VM, we head over and do the same thing on VM002. You’ll note that the number of shares has increased by 1 since we have now mounted the disk on VM001.

Great, now the disk is attached to both VMs! Heading over to the managed disk itself you’ll notice that the overview page looks a bit different from typical managed disks, showing information like “Managed by” and “Max Shares”.

In the properties of the disk, we can see the VM owners of that specific disk, which is exactly what we wanted to see after mounting it on each of the VMs.

Although I setup this configuration using Windows machines, you’ll notice I didn’t go into the OS. This is to say that the process, from an Azure perspective, is the same with Linux as it is with Windows VMs. Of course, it will be different within the OS, but there is nothing Azure-specific from that aspect.

Okay, here we go the Pros and Cons:

Pros:

  • Azure Shared disks allows for the use of what is considered to be “legacy clustering technology” in Azure.
  • Can be leveraged by familiar tools such as Windows Failover Cluster Manger, Scale-out File Server, and Linux Pacemaker/Corosync.
  • Premium and Ultra Disks are supported so performance shouldn’t be an issue in most cases.
  • Supports SCSI Persistent Reservations.
  • Fairly simple to setup.

Cons:

  • Does not scale well, similar to what would be expected with a SAN mapping.
  • Only certain disk types are supported.
  • ReadOnly host caching is not available for Premium SSDs with maxShares >1.
  • When using Availability Sets and Virtual Machine Scale sets, storage fault domain alignment with the VMs are not enforced on the shared data disk.
  • Azure Backup not yet supported.
  • Azure Site Recovery not yet supported.

Alright, that’s it for Azure Shared Disks! Go take a look at my Github Repository and give shared disks a shot!

Please reach out to me in the comments, LinkedIn, or Twitter with any questions or comments about this blog post or this series.  

Configure Azure Blob Archive Storage

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Reading Time: 4 minutesAzure storage is great. Good thought to open on right? Of course! This year Azure graced us with the ability to (preview) the new Azure Archive Storage. Obviously this is enticing, especially at it’s  (current) $0.0018/GB price point. For more cost informaiton on Azure Archive Storage you can visit the link below.

https://azure.microsoft.com/en-us/pricing/details/storage/blobs/

Now this is nice, but I found myself a bit perplexed. How do I configure a storage account as an “archive” storage account? As it turns out, you don’t. Let’s walk though configuring an archive blob tier.

First, obiously you need a storage account. The Archive access tier is currently available on either “Blob” or “General Purpose v2”.  General Purpose v2 will work the same way, you’ll just also have the ability to host non-blob storage (File, Queue, Table). I’m going to just choose Blob though for this purpose.

Account kind selected, I’ll create the storage account. You can choose whatever Access Tier you’d like, that’s the access tier all of your objects will inheret by default. I choose “Cool” here because you will have to upload data before you can archive it and the cool tier saves money initially.

Alright storage account created, let’s go open it up.

If you go to the “Configuration” tab you can see the default acces tier you selected durring creation. Here is where I was a bit confused, why don’t I have the ability to select archive? You’ll see in a bit.

Go ahead and create a container, and upload a file. I created a container with the very complex name of “container1”, and have uploaded my very important image file that I want to archive.

Can see above that the inhereted access tier is “Cool” which was set at the storage account level. If you go into the blob properties you can see at the bottom there is an option to select the access tier for that specific file. Ah! There is it, Archive!

I’ll go ahead and select Archive, and see the the following message.

Please be cognizant of this, they aren’t kidding when they say that rehydration can take a long time. We can now refresh and see that the file is set to an access tier of “archive”.

Fantastic, we’ve archived the file! Now here is where you have to be careful, while the file is in archive the only data you’re able to access is the file metadata. The file itself is NOT ACCESSABLE until rehydrated. If you try and download the file while archived you can see the following message.

Archive storage is designed to be very long-term storage that you don’t need to access immediately, thus the low cost point. If you do need to access your file, you simply go back to that object and change it’s access tier to either Cool or Hot. It will then go through the “rehydration” process to move the file back into an accessable access tier.

I urge you to take that message seriously, in this example it took about 8 hours for my 48k image file to be rehyrated. They say it takes longer for larger files, and I’m going to test that next. Though in the mean time, assume it will take quite some time to be accessable again. After which time, WHEW! I recovered my very, very important file.

There you go, how to configure Azure Blob Archive Storage.

I hope I’ve made your day at least a little bit easier.

Changing Azure Recovery Services Vault to LRS Storage

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Reading Time: 2 minutesBack in the classic portal with backup services it was an easy fix. Simply change the settings value of storage replication type. I’ve recently started moving my workloads to recovery serveries vaults in ARM, and noticed something peculiar. By default, the storage replication type of the vault is GRS.

 

If your needs require geographically redundant storage, that that’s perfectly fine. I however don’t have such needs, and trust in Microsoft’s ability to keep data generally available in a LRS replication topology. It should be just like it was in classic, as an option anyways, right? Strangely, the option to change the replication type for the storage configuration on the vault is grayed out.

 

 

Odd, right? I thought so, until I found this.

 

Okay, well it’s not optimal but it looks like I need to remove the backup data from the vault to change the storage replication types right? Well, I gave that a shot and no go. I had the same issue, the option was still grayed out.

I ultimately had to completely delete, and create a new recovery services vault. Once it’s initially created you can change the replication type.

 

 

Ah, finally! Then register the VM(s), run some backup jobs and voila! Confirmation that the vault is using LRS storage.

 

I hope this makes your day at least a little bit easier.

Thanks,