Welcome to 'This is My Architecture'.
Today, I'm joined by Tom from Veritas.
Welcome, Tom.
Thanks, Elvis. Appreciate the opportunity.
Tell us, what does Veritas do?
Veritas is an enterprise data management company
that focuses on three things:
availability of applications and the storage they're consuming,
which is what we're going to talk about today.
The other two pieces are protection.
Protecting that data and making sure
that in the event that something catastrophic happens
you can recover that data.
Then the third piece, insight into that data.
There's lots of data out there
and customers want to be able to more efficiently manage that data.
All right. Well, let's talk about the availability piece.
Tell us about that.
Probably the best way to describe InfoScale
is kind of a bridge between applications and infrastructure.
So, we're essentially abstracting the complexity of the infrastructure
from a clustering perspective, from a storage perspective,
and making it directly accessible to that application.
Okay.
So, if we have, for instance, a business critical service,
that's a large beverage company,
one of the largest beverage companies in the world,
they're business critical service was SAP in the back-end.
They use SAP for production, delivery, sales, distribution — everything.
What they wanted to do,
and this was a CIO initiative as many of us have seen,
and moving to cloud for cost-saving purposes, right?
So, we went in and worked with a system integrator initially,
and they were told that it was going to take three years
to make this transition into AWS.
We came in and said, no,
there's a number of things we can do to drastically reduce that time,
and ended up doing it in eight months.
How we did that was focusing on three key areas.
First, the migration. How do we get there?
When you're going to migrate, most of the time
you're looking at moving that dataset from on-prem into cloud.
So, InfoScale has a global file system
that enables us to actually replicate data from on-prem into cloud.
One of the things that we noticed immediately,
since we are at the file system level and have application intelligence,
is that they had 100 terabytes of capacity.
The initial system integrator was thinking, well,
I've got to copy 100 terabytes over there.
Then he says, no, if you actually look at the datasets in 100 terabytes,
there's only 30 terabytes of data.
So, that was a drastic savings.
So, you helped them,
or InfoScale helped them move that easily from on-premises
into a version of InfoScale on AWS?
- Correct. - Okay.
So, along with that storage migration piece,
the second area that they ran into a challenge with was costs.
They wanted to put the entire SAP and Oracle on the back-end
into performance storage, which is somewhat expensive.
So, since we do have this global file system,
we were able to show them that we could carve things up.
So, if you're got 10 percent of your data
that you want in high performance storage, you can do that.
You've got 60 percent that'll just sit in standard HDD.
And then you've got 30 percent that you're going to put in S3.
- Got it.
And a single file system, we can carve that up with policies
that dictate how much data stays in one persistent state at another time,
and then, eventually, tier that off.
-Yes, that makes sense.
So, you're using the various storage tiers that AWS offers
through the intelligence in InfoScale
to tier that in a cost-effective way.
And to help customers.
When they looked at it initially, it broke their TCO model.
But we said, no, like Amazon offers all kinds of storage,
and we can help you carve that up
based on the right fit for function for that dataset.
Right. So, then you got that into one region.
Can you scale across regions with InfoScale?
That comes back to the availability piece, the second concern.
They wanted the same level of availability that they had on-prem,
and they were replicating data all over the globe.
So, they were interested initially in zone to zone replication,
which we can do synchronously through this cluster file system.
And then also for disaster recovery purposes,
they wanted to be able to replicate this to another region.
So, since our intelligence within InfoScale
really sits at this business critical service or application level,
we understand the relationship between
the application and the datasets that they're being consumed.
That clustered file system that supports any type of storage on the back-end.
We're able to understand the relationship of that storage to the application.
So, in the event that there is any inconsistencies in terms of replication,
you have a failure, you immediately want
to cut things off from writing to those datasets to avoid corruption.
That's what InfoScale delivers.
Got it. And then what if you still needed on-premises for
say compliance reasons or some other reason like that?
So, many customers are concerned for regulatory purposes,
or potentially latency issues,
and they can't put everything into the cloud.
Or if you're a financial institution in the United Kingdom, for instance,
you have to be able to fail over from on-prem into cloud and back,
and be able to show that.
So, we can actually do that through an automated process.
We actually call it Fire Drill, and it's essentially a fire drill.
You don't have to do anything with your production application.
You can fail over into the cloud, fail over out of the cloud,
show the auditor the compliance report,
and we can also do this on outpost.
If you don't want to move that data out
you can have a hybrid cloud configuration
with some of your data on-prem and bursting capabilities into the cloud.
Neat. Well, thanks for sharing your architecture with us today, Tom,
and thank you for watching 'This is My Architecture'.