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>> Hello. My name is Mihaela Blendea.
I'm a Program Manager in SQL Server team.
I'm currently focusing on
management scenarios for big data clusters.
So in this video,
I'm going to go through few deployment options that you have for
big data clusters and what you need to
know to have a successful deployment.
Let's get started with an overview of few choices you
must decide on when you are planning a BDC deployment.
Some of these decisions will
depend on the infrastructure you have available,
like the type of Kubernetes cluster you are planning to use
or if you're planning to deploy
On-Premise or in Azure, for example.
But you will also need to consider
the type of workloads you are planning to run,
and this is where sizing and
scaling decisions will come into play.
For example, a PoC,
or just to learn about BDC capabilities,
will require just a single node of
a Kubernetes cluster as long as it
has the minimum resources and
storage configurations that are documented.
Once you have the target Kubernetes cluster available,
next step is to think about
how you will deploy BDC on top of that.
From tooling perspective,
one option is to use Azdata command utility.
Our new cross-platform Python-based tool to deploy,
manage, and interact with services in BDC.
You can automate entire deployment process using Azdata command,
or you can go with
a guided more interactive experience using Azdata CLI again,
or notebooks in Azure Data Studio.
For all these options, we're publishing samples,
credits, and notebooks for you to reference in our documentation.
To accommodate deployments in environments
that are not connected to the Internet,
we are publishing the list of images that must be pre-pulled from
Microsoft Container Registry and pushed into
your private Docker registry
that the target environments have access to.
A tolling required for deployment
have a disconnected install experience as well.
In terms of the actual deployment workflow,
first, of course, you must have access to a Kubernetes cluster.
Then on your client machine,
you have to install, as I was mentioning, Azdata CLI.
Optionally, if you are planning to use
notebooks for the deployment, or of course,
later once you are running workloads
against their cluster services,
you can set up Azure Data Studio.
Next step is to choose
what configuration template to use as
baseline for your deployment customizations.
If any edits are necessary to accommodate
different storage or scaling and networking requirements,
you will make a copy of the built-in template using
Azdata and then use that copy for any customizations.
Lastly, we just need to set the credentials for
accessing the external endpoints in the cluster,
and then issue the BDC create
command to start the actual deployment workflow.
Upon deployment completion, you would
probably want to connect to the BDC services and
we're providing a convenient API
for you to list all the endpoints available in
the cluster that you can use to
connect to the services and be their cluster.
Let's actually see how this works with a short demo.
So here is my client machine that I already set up with Azdata.
So just to double-check,
I can issue a simple command to see if I have it.
Definitely, I need to double-check if I can connect to
the Kubernetes cluster that I set up,
in this case, I have an AKS cluster in Azure.
For example, I can issue simple commands to see.
So I'm going to deploy in this single node Kubernetes cluster.
Let's see what happens if I just issue "Azdata BDC create".
I'm first prompted to accept the license terms,
and then this guided experience
that I was mentioning earlier starts to
prompt me for all the inputs that are
required for the deployment to start.
First, I'm prompted for
the configuration that I want my deployment to be based on.
This configuration profiles that you
see here are like templates that are
pre-populated with default values that
makes sense for the environment that you are deploying on.
Main difference between a config file
targeting Azure Kubernetes service and a config file for
a Kube ADM cluster minimum
is mostly about the storage and networking requirements.
But the rest of the defaults are pretty much the same,
and you can use those defaults as a baseline for various edits.
You can do to customize your big data cluster.
In my case, since I'm deploying on AKS,
I'm going to use the AKS dev test configuration profile.
The neat thing about this AKS Config is that
for the default minimum configuration size,
everything is pretty much ready to go and I
don't need to make other changes.
So I'm not prompted for other required inputs.
But because I didn't set up the credentials
for the external endpoints in the cluster,
I'll have to go through that.
So I need to provide credentials for SQL Server, for a gateway,
and a controller, and then the deployment is underway.
Another way that you can customize
your deployment is to pretty much create a clone or
a copy of this built-in configuration files
that we have shipped with the Azdata.
So you can use Azdata BDC config init command,
and provide one of the options that you saw earlier.
As a target, you specify a local folder
that you want the configuration files
to be stored in,
and this command it will just
create a clone of this configuration file.
So if I go here in this folder,
I can see that right, for example,
BDC JSON that describes
all the resources and
the services that are deployed in the cluster,
I can customize the ports and the number of instances and so on.
Once I have that,
the only thing that I need to do
and once I made the changes that I want,
again, I want to do BDC create.
But this time, I'm going to point to
this custom configuration profile
that I created in order for
the deployment to make use of those changes.
For more information and details on the BDC deployment,
please refer to this resources that I listed here.
You will find guidance and best practices on how to
configure and deploy a big data cluster,
pointers on tools, setup,
and simple scripts to get you started quickly.
Also, referencing here other resources
that you can leverage to learn more about BDC and
SQL Server 2019 with hands-on workshops or samples that you
can use that showcase
various use cases that you can leverage BDCs for.
Thank you for watching.
Please come back for more insights into
big data cluster capabilities and SQL Server 2019.
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