If you're not sure which Azure virtual machine
is the right fit for your app or workload,
in the next few minutes, I'll break down your options.
Azure, with its vast compute infrastructure
spanning 70-plus global regions,
gives you the flexibility
to choose from one of the broadest selections of VM types
among major cloud providers to run any workload.
A portfolio of hundreds of VM options has been designed
to scale to the performance, cost,
and specific technical requirements your workload needs,
while providing access
to the latest CPU technologies from Intel,
plus Microsoft's custom Cobalt CPUs,
with their power efficient, Arm-based design,
integrated systems from our close partnership with AMD,
and, of course, NVIDIA for the very latest
in GPU innovation.
And you can deploy Windows Server-based applications
or use your favorite Linux distro on Azure.
Our Azure-tuned Linux kernels incorporate new features
and performance improvements at a faster cadence
compared to default or generic kernels,
meaning there's no need to repackage your apps and services.
And for SUSE and Red Hat Linux,
our engineers are co-located for integrated support
to streamline and accelerate the resolution of any issues
you might encounter in the least amount of time.
So let's break down your core options
to select the right VMs for your workloads.
Azure VM families are optimized
to run any size of workload,
from general purpose to memory, compute,
and storage intensive workloads,
in addition to high-performance computing and AI scenarios.
Now, when you're looking at Azure VM sizes,
there's a structured format
that helps you understand the characteristics of each VM.
It starts with the family,
followed by an optional subfamily,
the number of vCPUs,
the processor type and additive features,
and the version of the VM.
Importantly, an a signifies AMD-based processes
and p signifies that the VM is powered
by Arm-based processes.
If you don't see an a or a p,
the underlying processor is Intel based.
And then a set of lowercase letters
represent additive features,
for example, s for premium storage.
Now, to learn more, you can refer to aka.ms/VMnames,
and you can leverage free tools like Azure Migrate
to assess the requirements of your on-prem workloads
and right-size your infrastructure on Azure.
Then your choice of VM will depend on the workload
as each series has different characteristics.
So let's start with our entry level B-series,
or Burstable VMs,
which are useful for workloads
that typically run at a low to moderate CPU baseline,
but sometimes need to burst
to significantly higher CPU utilization
when the demand rises.
An example would be a web front end,
like a check in/check out application at a hotel
where you need to plan for sporadic compute capacity
to handle traffic spikes.
That said, most of your general purpose workloads,
such as app servers or small to medium relational databases,
are best run on the D family of Azure virtual machines.
These VMs offer the vCPUs, memory, and temporary storage
to meet the requirements of most production workloads.
Or you can opt for no local temporary data disc
to reduce your TCO.
The latest D-series VMs
include fast, larger local NVMe SSD storage
and are designed for applications
that benefit from low-latency, high-speed local storage,
such as applications that require fast reads and writes
to temporary storage.
Conversely, memory-optimized VM sizes
that are part of our E series
offer high memory-to-CPU ratios.
These VMs are ideal
for large relational databases, data analytics,
as well as other large
in-memory business-critical workloads
and applications like SAP NetWeaver.
Then, depending on your requirements,
you can select E-series VM sizes
that include large and fast local NVMe SSD disk storage
for applications that benefit from low latency
and high-speed local storage,
or, again, the no local temporary data disk option
is available to reduce your TCO.
Now, for workloads demanding
the cutting edge of network performance,
such as network virtual appliances, large-scale e-commerce,
and media processing,
network optimized variants, identified by the n,
are available for both general purpose D-series
and memory optimized E-series VMs.
Next, for compute-intensive applications,
F and FX-series VMs have high vCPU performance
and are great for compute-intensive workloads,
such as video encoding and rendering,
electronic design automation,
and gaming applications.
Alternatively, if you need to run Big Data, NoSQL databases,
or large data warehousing solutions on Azure,
L-series VMs are optimized for storage-intensive workloads
and are built for the speed of data access
And they feature ultra-fast, low-latency NVMe storage
that's physically mapped to the host.
This local storage layer is ideal
for handling temporary data with high throughput,
making it perfect for storage-intensive workloads.
These VMs give you access
to terabytes of storage and millions of IOPS.
Then taking things to the next level,
the M-series VMs are designed for applications
that process large amounts of data in memory.
They offer the largest memory of any VM series on Azure.
M-series VMs are ideal for extremely large databases
or other applications like SAP HANA
that benefit from massive memory footprints
and extremely high vCPU counts.
Also, because some software is charged on a per core basis,
to reduce the cost of software licensing
for memory and storage-intensive workloads,
we also provide the option of constrained vCPU-capable VMs
across a number of VM series.
Some database workloads, for example,
may not need as many cores.
So, with this option, we limit the vCPU count
all while leaving memory, storage,
and I/O bandwidth unchanged.
Next, switching gears for more specialized workloads,
the H-series VMs support
high-performance computing workloads
where the speed of memory is critical,
like scientific workloads such as weather forecasting
where tracking dangerous storms requires
the highest precision forecasts
with precise computations at speed.
And there are many more critical everyday workload examples
where these VMs can apply,
from designing safer cars or planes and buildings
to cheaper energy
and even to studying the fluid dynamics
of, for example, beer.
Adding to this, if high-performance computing power
for graphics-intensive and parallel processing tasks
is more your thing,
the N-series family of VMs are GPU-enabled
and are ideal for AI model training, inference workloads,
along with model fine-tuning and distillation,
as well as digital twins,
video rendering, predictive analytics, and more.
Combined with NVIDIA NVLink and InfiniBand technologies
to connect multiple GPUs and CPUs,
you can build your own multi-VM supercomputer
for the most demanding tasks.
Importantly, powering all the latest generation Azure VMs
is a key infrastructure technology called Azure Boost,
which enhances Azure virtual machine performance
by offloading storage, networking, and host management tasks
to purpose-built hardware and software,
freeing up computing resources for workloads.
At the same time, it enforces code integrity
so that only verified code can run on the system
as well as strict isolation of workloads
for additional security.
And, across a number of these VM options,
if you need more security,
Azure Confidential VMs and GPUs are backed by Intel TDX
and AMD SEV-SNP technologies.
These use hardware-based
Trusted Execution Environments, TEEs,
across both CPUs and GPUs
to protect data while it's being processed.
These ensure only verified and authorized code
can access sensitive data,
which is ideal for secure collaboration
in regulated industries
like healthcare, finance, and government.
These confidential VMs are available
for the D, E, and N series.
So now you know your options.
As you go to deploy your VMs,
you also have options to do so at scale.
Azure Virtual Machine Scale Sets let you create
thousands of virtual machines in one go
and increase or decrease
the number of VMs needed automatically
based on load or schedule.
And with another option, Azure Compute Fleet,
you can launch even larger groups of VMs
based directly on workload or cost requirements
with options to select many VM types in the same fleet.
So that was a quick tour of your options
for Azure Core Compute.
Whether you have basic or advanced compute needs,
we give you a huge range of VMs to choose from.
You can find more resources on the topic
at aka.ms/VMAzure.
And as always, thanks for watching.