Azure already gives you plenty of storage options,
blob, files, disk.
So why does Azure NetApp files even exist?
That's the first question people ask when they hear about it.
And it's a fair one.
Microsoft keeps adding storage services
and it can feel like a new option appears every quarter.
So why another one?
Here's the thing.
Most Azure storage handles general use just fine.
Web apps, file shares, backups,
the everyday things that keep a business running,
but some workloads don't fit that mold.
They need ridiculous speed.
They need consistent performance under pressure,
and they can't afford extra milliseconds of delay.
Azure NetApp files is built specifically
for those workloads.
By the end of this episode,
you'll know exactly what A and F is,
when to use it, and when to stick with something simpler.
We'll cover what it actually is,
the three main use cases where it shines
and how it compares to Azure files.
Let's start with a simple definition.
What Azure NetApp files actually is.
Azure NetApp files is a managed,
high performance enterprise file storage service
that lives right inside Azure.
This is not some third party add-on
or something you bolt on later.
It's the first party Microsoft service
fully built into the Azure portal,
but what sets it apart?
Under the hood, it runs on NetApp technology.
The same storage system that's been powering
on premises data centers for decades,
NetApp has been doing enterprise file storage
since the 1990s.
They understand fast and reliable data.
Microsoft partnered with them to bring that expertise
into Azure as a managed service.
So what does that mean for you?
A and F supports both SMB and NFS protocols
right out of the box.
Windows workloads, Linux workloads,
it handles both.
You don't have to choose one or the other.
The same volume can serve both types of clients
if you need it.
Performance is where it really stands out.
We're talking sub millisecond latency
and massive throughput, not fast enough.
It's genuinely blazing fast.
Here's an analogy.
If Azure files is the reliable family sedan
that gets you where you need to go,
Azure NetApp files is the sports car,
built for speed and it handles unlike anything else
in the garage.
And the best part, it's fully managed.
No patching service, no replacing hardware.
You just create a volume,
choose your performance tier and start using it.
Azure and NetApp take care of the rest,
but why would you need a sports car for storage?
Let's look at the problems regular storage can't solve.
The problems, regular storage can't solve.
Most cloud storage handles everyday IT, just fine.
Web apps, file shares, backups.
For most people that's enough,
you don't need a Formula One engine
to drive to the grocery store.
But some workloads are different.
Think of them like demanding athletes
who need every millisecond and can't afford to wait.
Here's the problem.
High latency kills database performance.
A few extra milliseconds on a log ride
can slow down an entire transaction system.
Low throughput chokes simulations,
turning jobs that should take hours into days.
Inconsistent IOPS is another issue.
It frustrates VDI users the most.
One minute everything's fine.
The next, the desktop lags because storage can't keep up.
Let me give you a concrete example.
A 2.3 terabyte, SAP HANA database backup
on regular storage might take an hour.
That's an hour of waiting and potential issues.
On Azure NetApp files,
the same backup completes in two minutes.
Not a typo, two minutes.
The issue isn't that Azure files is bad.
It's a great service for what it's designed to do.
But it's optimized for cost.
Not peak performance.
It gives you good enough speed at a reasonable price
and that's fine for most workloads,
but not all Azure NetApp files fills that gap.
It's built for workloads that can't compromise
on speed or consistency.
When every millisecond counts, ANF is the answer.
So who actually needs this kind of performance?
Let's start with one of the biggest users.
SAP HANA.
Use case number one, SAP HANA.
Let's talk about SAP HANA.
If you're not in the enterprise database world,
you might not have heard of it.
But it's one of the most demanding workloads
you can run in the cloud.
SAP HANA is an in-memory database,
meaning it keeps all its data in RAM for speed.
But even though data lives in memory,
HANA still needs ultra-fast storage
for logs, backups, and snapshots.
Those rights have to happen quickly and reliably.
If storage can't keep up, the whole database slows down.
That's why Azure NetApp files is SAP certified.
It's listed in the official SAP HANA hardware directory,
meaning it's been tested and approved by SAP themselves.
That's not a small thing.
SAP doesn't certify just any storage solution.
They test it thoroughly and only the ones that pass make the list.
What kind of performance are we talking about?
Submily second latency consistently,
and up to four times 500 might be per second of throughput per volume.
To put that in perspective,
SAP's minimum requirement for HANA log rights
is under one millisecond of latency
and ANF lives comfortably below that threshold.
That matters because latency above one millisecond
can slow down database transactions.
When you're processing thousands of transactions
per second, every extra millisecond adds up.
Microsoft even built a special deployment tool
called Application Volume Group for HANA.
It optimizes volume layout by spreading them
across multiple storage endpoints,
so no single endpoint becomes a bottleneck.
Think of it like having multiple lanes on a highway
instead of one narrow road.
And the backup numbers are worth talking about.
A 2.3 terabyte HANA backup completes in about two minutes
on ANF.
On conventional storage, that same backup could take 30 to 60 minutes.
That's not just a convenience.
It changes what's possible with your backup windows.
The cost side is interesting too.
With flexible service levels,
you can match performance exactly
to what HANA needs without over-provisioning.
You're not paying for extra capacity
just to get the throughput you need.
SAP is one big use case, but ANF also powers
a very different kind of workload, high performance computing.
High performance computing, HPC.
High performance computing covers a lot of ground.
Simulations, rendering, financial modeling, scientific research,
anything where you're running massive parallel jobs
across hundreds or even thousands of compute nodes.
These workloads have a very specific need.
They need shared file access with high throughput and low latency.
Multiple nodes must read and write the same data sets
at the same time.
If your storage can't keep up, your compute nodes
sit idle waiting for data.
And idle compute time is wasted money.
Azure NetApp files delivers up to 652,000 IOPS
with under 2 milliseconds of latency in benchmark tests.
That's a lot of input output operations.
And it's fast enough that storage rarely
becomes the bottleneck anymore.
For really large data sets, there's
the large volumes feature.
It supports capacities up to two petabytes per volume.
That's 2,000 terabytes in a single volume.
Think about what that means for a research team
working with massive simulation outputs,
or a media studio rendering a feature film.
Then this breakthrough mode, it pushes throughput up
to 50 gigabits per second from a single large volume.
That's enough bandwidth to move enormous data sets quickly.
Here's a real world example, electronic design automation,
or EDA in the chip design industry.
Companies like Nvidia and AMD run thousands of simulations
at once to verify chip designs before manufacturing.
Each simulation reads and writes shared data.
The storage system has to handle that concurrent load
without slowing down.
ANF is built for exactly that pattern.
So why not just use Azure files for this?
Because Azure files has file level throughput caps,
300 megabytes per second, egress per file.
That means even if your storage back end has more capacity,
a single large file can't push past that limit.
ANF has no file level caps.
Each file can saturate the network connection.
For workloads dealing with large simulation files,
that difference matters.
Microsoft's own guidance recommends ANF for HBC workloads
up to about 4,000 cores and 6.5 gigabytes per second
of throughput.
Beyond that, you might need a different architecture,
but for the vast majority of HBC scenarios,
ANF fits the bill.
Third major use case, virtual desktop infrastructure,
where user experience is everything.
Virtual desktop infrastructure, VDI.
Now let's talk about something almost everyone deals with.
The desktop experience.
Virtual desktop infrastructure or VDI
means hosting Windows desktops in the cloud,
think as you are virtual desktop or Citrix.
Instead of running a full PC on your desk,
the desktop lives on a server somewhere
and you connect to it remotely.
Here's the challenge.
User profiles and app data must be stored centrally
and accessed quickly.
Every time someone logs in, their profile has to load,
settings, files, application data.
If that storage is slow, the login is slow,
and slow logins make people unhappy very fast.
This is where ANF makes a real difference.
Slow profile load times have been the number one complaint
in VDI deployments for years.
Users compare it to their old on-premises desktop.
And if the cloud version feels slower, they notice immediately.
Azure NetApp files solves this with high IOPS and low latency.
And I'm not talking about theoretical improvements.
Real-world results show logon times dropping
from 20 to 30 seconds down to under five seconds
when organizations switch from Azure files
to ANF for their profile storage.
That's the kind of improvement users actually feel.
Why does it work so well?
Because ANF supports up to 450,000 IOPS per volume,
that matters when hundreds of users
all log on at the same time in the morning.
That's the logon storm.
Everyone arrives at nine,
and suddenly every profile needs to load simultaneously.
A storage system that can't handle that concurrency
will slow everyone down.
ANF handles it.
There's another feature that's incredibly useful for VDI.
ANF supports up to 255 snapshots per volume.
That means you can instantly revert
a user's profile to yesterday's state.
If someone's profile gets corrupted
or a bad update breaks something,
you don't have to restore from backup.
You just point to yesterday's snapshot and it's done.
That saves hours of support time
and the reliability piece matters too.
ANF comes with a 99.99% availability SLA.
For mission-critical VDI deployments
where downtime means lost productivity,
that level of reliability is essential.
Here's a cost angle you might not expect
because ANF is so fast you can actually use smaller,
cheaper virtual machines and still get good performance.
The storage handles the heavy lifting
so your compute doesn't have to.
That can offset some of the premium storage cost.
And you now see the three pillars SAP HPC VDI.
But how does ANF actually compare to its cousin Azure files?
How Azure NetApp files compares to Azure files?
So both Azure NetApp files and Azure files
are managed file shares in Azure.
That means you don't patch servers or replace hardware.
The real difference comes down to performance and price.
Let's compare the raw numbers.
Azure files premium caps at 100,000 IOPS per share,
which is plenty for many workloads.
But ANF hits up to 450,000 IOPS per volume,
more than four times that ceiling.
When you're running workloads that need serious concurrent access,
that gap really matters.
Latency tells a similar story.
Azure files standard runs around 10 milliseconds
and premium brings that down to two to three milliseconds.
That's respectable.
But ANF delivers sub millisecond latency
around 0.5 milliseconds on the ultra tier.
That's the difference between storage being a minor factor
and storage being essentially invisible.
Throughput is where the gap gets even wider.
Azure files has file level caps.
300 megabytes per second egress
and 200 megabytes per second egress per file.
So even if your backend has more capacity,
a single large file can't push past that limit.
ANF has no file level caps.
Each file can use as much throughput as the network allows.
And maximum share size,
Azure files tops out at 100 terabytes per share.
ANF goes up to two petabytes with large volumes.
That's 20 times the capacity.
So when do you use each one?
Azure files is the right choice for general file sharing,
department shares, backup targets,
and cost sensitive workloads.
Think of it as the sedan.
Reliable affordable gets the job done.
ANF is for workloads where latency and throughput are critical.
SAPI Hana, Oracle, SQL Server, HPC, VDI.
Any scenario where sub millisecond latency
and high IOPS make a real difference
to application performance.
Now here's the thing about cost.
Azure files is cheaper for most use cases and that's by design.
But ANF can actually save money in specific scenarios.
If it lets you use smaller VMs because the storage is faster,
you save on compute costs.
If it prevents over provisioning capacity,
just to get enough throughput, you save on storage costs.
So the total cost picture isn't always straightforward.
There's one feature that changes the cost equation entirely,
the flexible service level.
The flexible service level, right sizing performance.
Here's a feature that changes the cost equation.
Traditionally, ANF capacity pools had a fixed ratio.
The bigger your pool, the more throughput you got,
and the smaller your pool, the less throughput you got.
That sounds reasonable on the surface,
but it created a real problem.
Imagine you have a small database, say one terabyte,
but it needs high throughput to run properly.
Under the old model, you'd have to over provision capacity
just to get enough performance.
You might need to buy 64 terabytes of storage on the standard tier
just to get the throughput that one terabyte actually needs
with the other 63 terabytes sitting empty.
You're paying for space you don't use.
That's not efficient and it's not cheap.
Flexible service level changes that completely.
It decouples capacity from throughput,
two independent knobs instead of one.
You decide how much storage you need
and separately how much performance you need.
They don't have to match.
So now you can have a one terabyte pool
with one gigabyte per second of throughput.
Under the old model,
that same performance on the standard tier
would have required 64 terabytes of capacity.
That's a 64 to one difference.
With flexible service level,
you pay for exactly what you need.
The cost savings are real.
In many scenarios, you're looking at 30% or more
compared to using the ultra tier for the same performance.
And that's before you factor in reserve capacity discounts.
The disaster recovery scenario makes this even clearer.
Say you need 100 terabytes of capacity for a DR side,
but you don't need much throughput
until an actual failover happens.
Under the old model,
you'd have to provision for the performance
you might need someday.
With flexible service level,
you pay for capacity only.
128 megabytes per second baseline throughput and nothing more.
When failover happens,
you scale throughput up on demand.
When it's over, you scale it back down
after a 24 hour cool down period.
Speaking of scaling,
you can increase throughput whenever you need it
within limits and after 24 hours,
you can scale back down.
That's perfect for handling peak loads.
Month and processing migration windows, seasonal spikes,
without permanently paying for that extra capacity.
This feature is currently available in preview
across all A and F regions.
It's one of the most requested additions to the service
and it's already changing how customers think
about storage cost.
That's the flexible service level in a nutshell,
a simple change that solves a big problem.
Connection section, putting it all together.
So here's the aha moment.
Azure NetApp files doesn't compete with Azure files.
It fills a specific performance gap,
a gap that matters for the right workloads.
Now those three use cases we covered,
SAP HANA, HPC, VDI, they all share one thing.
They need consistent low latency,
high throughput, file access.
That's the common thread through all of them.
Whether it's a database transaction,
a simulation job, or a user logging into their desktop,
the storage has to deliver without hesitation.
No waiting around.
Flexible service level makes that performance affordable.
Instead of over provisioning capacity you don't need,
you pay only for what you use.
That changes the whole economics of high performance storage.
It makes speed accessible.
On top of that, ANF integrates with the rest of the Azure ecosystem.
It uses EntraID for access control,
snapshots handle backups,
and replication covers disaster recovery.
It's not an isolated tool, it's part of the broader platform.
The real power lies in the combination,
not in any single feature.
Performance, flexibility, and managed simplicity altogether,
you get enterprise grade storage
without the enterprise grade overhead.
Think of ANF as the specialized tool in your storage toolbox.
You don't use it for everything, but when you need it,
nothing else works as well.
That's its job.
Two things you can do right now.
First, if you have a workload that complains about storage speed,
like slow backups, laggy VDI, or long simulation times,
take a closer look.
Evaluate whether ANF could solve that bottleneck.
It might be the fix you've been searching for.
Second, head to the Azure website
and use the Azure NetApp files cost calculator.
Model your workload, especially with the flexible service level option.
You might find that the performance you need costs less than you think.
That's often the surprise.
One caution though, don't migrate everything to ANF just because it's fast.
Use it where it matters most.
For general file shares and everyday workloads,
Azure files is still the right choice.
Save the sports car for the racetrack.
That analogy works here.
So what's the bottom line?
Azure NetApp files is Azure's high performance file storage
for workloads that can't compromise on speed.
It's the specialized tool for the jobs that need it most.
If this episode made ANF click for you,
subscribe to Microsoft Knowledge Nuggets
for more plain English explanations.
Share it with someone starting their Azure journey.
And drop a comment if something clicked.
We always read them.
I'm Mirko Peters.