>> Learn how to accelerate Oracle migrations to
Azure SQL with a new extension available on Azure Data Studio.
This week on Data Exposed.
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Hi, I'm Anna Hoffman and
welcome to this episode of Data Exposed.
Today I'm joined by Neel,
a program manager on the Azure SQL Team.
Neel, thanks so much for joining us today.
Can you tell us a little bit about what you do?
>> Hi, Anna. Hi, I'm Neel.
I'm a Program Manager and
I focus in the Database Migration Space,
primarily focus on the heterogenous migration,
which is any non Microsoft platform like
Oracle and migrating to SQL or post space and so on.
That's pretty much the charter I manage at this point.
>> Awesome. Cool. You seem the
perfect person to have on the show to talk to us
about Oracle migrations and
some new capabilities in Azure Data Studio itself.
Can you just tell us a little bit about these new capabilities?
>> Sure. Before that,
I'll just give a quick background.
When we reached out to a lot of
enterprise customers and partners,
few of the challenges today they
have when they're migrating their Oracle to Azure
is to do a quick reassessment to
understand the feasibility and what is
the right target if they are moving to
Azure and also when they move to Azure,
what might be the effort,
a very high level effort which is
required to do the schema conversion and assessment.
Taking this feedback what we decided,
let's go ahead and unblock
this scenario for our partners and customers.
We decided to create a single place of experience in
the Azure Data Studio where we have built
our new Oracle assessment experience,
where users can connect to Oracle from Azure Data Studio,
which Azure Data Studio,
most of our DBAs and developers, they're quite familiar.
We wanted to reuse the existing platform,
and there they can connect to the existing Oracle workload,
do a quick shallow discovery of their Oracle like the schemas,
the tables, the views and based on that, we give a quick,
decent sized recommendation like
which workload is simple, which is complex,
and what are the future compatibilities
if they are trying to migrate, let's say,
for example, partitioning, then how
the feature parity is between Oracle and SQL.
We are trying to make the life easy for our customers to make
those initial assessment done in a much more wholistic way.
>> Awesome. Cool. I'd love
to take a look if you have something for us.
>> Yes, I have a quick demo for that.
Give me a couple of seconds and let
me show the new experience in Azure Data Studio.
You see that I'm connected to
the Azure Data Studio and I have an Oracle instance on the left.
You can connect to Oracle from
the Azure Data Studio and then you
can right click and click on "Manage".
When you click on "Manage",
what you see is this new experience called Oracle assessment.
The first, if you see that there's a quick snapshot of what are
my last five assessments and you can see that I have run
five assessment for success and one failure.
You get a quick summary of what are
the various assessments you might have run for this given server.
If you want to start an assessment,
just click on "Run new assessment".
When you do run your assessment you need to
provide the name, I say demoX,
and then what you do is you select a SQL as a target right now.
But in future we plan to add
many other targets and we're just constantly looking for feedback,
which are the suitable targets for Oracle workload.
But to begin with,
we start with SQL.
The scale factor is when we collect the performance data.
For example, you are running the data collection today,
but your peak load is sometime maybe
during the month of December, November.
You change the scale factor and say, hey,
my scale factor might be 2X or 1.5X.
My peak load is it's more than
current test performance data collection scenario.
You can go ahead and change the set scale factor.
When we suggest the targets SQL SKU,
we take care of those scale factor in the formulas.
Then the percentile utilization.
How many data points you want to
capture to make this recommendation.
It can be 95 percentile,
it can be 90 percentile or 50th percentile, which is average.
You can go ahead and select.
By default, the scale factor
is one and percentile utilization is 95.
With this information, you can quickly click on "Start
Assessment" and then the assessment gets kick-started.
This assessment module goes ahead and connect to
an Oracle instance and it does multiple phases of data collection.
It collects a static data collection like here.
What is the Oracle version?
What is the Oracle edition and so on.
Then it collects the features.
What are the various features which is enabled in the Oracle.
Do you have partitioning enabled,
do you have data guard enabled and so on.
Then we collect the performance data.
We collect to the Oracle,
we collect some performance metadata
which is critical for the right sizing.
Then to the schema workload collection,
which is a shallow discovery.
You discover the tables, the views,
the code objects, the storage objects, the database size,
which is primarily used to create
a high level recommendation or a migration plan for our customers.
Once we collect these data,
we go ahead and do a quick assessment
of that data and give a final recommendation.
Every 30 seconds we go ahead and refresh this.
You keep on getting the latest of what's
happening during behind the scenes.
Now, I already have an assessment report ready.
If you want to see, right now we are running so many.
I already have an assessment report ready.
When you click on the "Assessment",
what you see is, hey,
what is this suggested.
If I have to migrate this workload from Oracle to SQL.
This is an example for SQL database and it clearly states that
this Oracle data instance has
308 simple schemas which can be migrated and it's easy to migrate.
It's a green tick. You can get
amber warning or you can get a red cross,
which is not recommended.
Along with that, what we suggest is how many estimated hours,
and in this case it's 576 hours of
code development effort which is required to convert the schemas,
and with the final one is the feature compatibility.
Now when you are trying to migrate Oracle to SQL,
there are a lot of features and we do
a feature migration parity and see out of the score of 100.
How much is the feature compatibility between the Oracle and SQL?
This case is a pretty high of 83.
The final one is the recommended configuration.
With the current performance data,
the suggestion is a two-vCore and three-GB storage.
This is a high level assessment summary,
but user can go ahead and drill down further.
They can go to the database details, they can understand.
These are the various schemas.
If we look at Oracle demo has 476 table,
74 stored procedures and
so many other components and in total that
take 201 development hours to do this migration.
Similarly for Oracle tests, it's 291.
You can understand the complexity of each schema and
each workload and you can prioritize based on your requirements.
Now one thing I would like to call out
these numbers, the estimated numbers,
which we have done based on heuristic data,
we have collected a lot of previous assessment data and
we created an algorithm behind the scenes.
Now this can change when you do
a deep-dive code assessment and
the numbers can change when you start the code assessment.
But these are high level figures which
will help you at the pre-assessment and when you're
trying to build a decision which
workload to prioritize first than later.
The next is the SKU recommendation.
In the SKU recommendation will not only give you
the recommended configuration but
the recommendation reasons behind it.
Like how much is the IOPS requirement?
What's the IO latency requirement, and so on.
Based on CPU memory IO and storage,
we can go ahead and give a recommendation of the SQL SKU.
The feature compatibility is we do
a one-to-one mapping where we are possible between the feature,
in this case, active data guard,
what is a suitable the capability in SQL?
Which is always on readable secondary,
and what is in migration,
ease of migration in a scale of 0-5,
and five being the ease and the zero is very complex to migrate,
and in this case it's a four which
it's pretty fairly easy to migrate.
You can go ahead and search
whichever feature you're interested like partitioning.
If I click on "Partitioning",
you get what mode in detail information here,
what are the different partitioning capabilities
and how you can migrate,
for example, for code conversion,
you can use SMA to migrate this partitions.
With all this data available,
now user want to reuse
this data at various stages of their migration.
What we have done is you can go ahead and download this report.
When you click on "Download Report",
it actually creates an HTML report and it gives a full summary of
database migration assessment report
and we collect three targets;
Azure SQL managed instance,
Azure SQL database,
and Azure SQL VM,
and we give a full report history
of the entire assessment done for
the given workload with a lot of extra information
like what is the suitable SKU?
What is the suitable the service tier,
which is enterprise or standard edition
and little bit of more content
and information of how can you
migrate and links to our Microsoft Docs.
That is the new experience we are building for
end users and we would
like to add more and more capabilities in the near future.
>> Awesome. Cool. This is really cool.
Neel, thanks for sharing with us.
I learned a couple of things myself.
I didn't know you could connect to Oracle using
Azure Data Studio and
certainly learn a lot about the different recommendations.
How you're taking this idea of SKU recommender,
which we're seeing for other migration services to
this Oracle to Azure SQL migration. Really awesome stuff.
It's exciting to see what the the team is doing here.
I did have one question,
assuming I already have Azure Data Studio installed,
how is the best way for me to get this new capabilities?
Is it an extension?
Do I have to download something else?
How does that setup work?
>> Yeah, you go to
the new marketplace and if you search for assessment,
you will get the new Oracle assessment experience.
Yeah, that's how.
>> Awesome. Cool. It's just an extension.
It's really easy to get.
>> Yeah.
>> In my existing Azure Data Studio installations.
>> Yeah, you get the new extensions,
extensions for Oracle,
then you can go ahead and install it.
>> Okay. Awesome. Cool. Then one more question.
You mentioned that this is really new.
We're investing a lot and looking for feedback.
If users have feedback as they get started with this,
where should they put that?
>> Currently, they have multiple places to give the feedback
but one of the most easiest way
is you have this feedback link here.
When you click, there is an email alias and you can go ahead
and reach out and send your feedback directly,
or you can fill
this information in the tech community site
and provide the feedback as well.
>> Awesome. Cool. Thank so much Neel.
I personally learned a lot.
I think our viewers will as well,
especially those trying to move off of Oracle.
It's awesome to see the investment
or maybe as a team in this space.
To our viewers, go ahead and check
the links in the description on how to get
started and more information about
this new extension in Azure Data Studio.
If you like this video, go ahead and give it a like,
comment and let us know what you'd like to see next and
we hope to see you next time on Data Exposed.
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