Welcome to 'This Is My Architecture'.
I'm Mathieu and today I'm joined by Florian from Keen Eye.
Hello Mathieu, thanks for having me.
Can you tell me more about Keen Eye?
Yes, Keen Eye is a health tech company.
We build deep learning technology for research and clinical study.
We guide the pathologists and doctors to analyze medical images.
Cool. So can you tell me more about the architecture?
Yeah, so the biologist, hospital, customer
are sending us the slides and the images into S3 bucket.
We are talking about 5 terabytes of data average per project.
And then we use it to host to send it into our product hosted on Kubernetes
to show them to the pathologist.
So that platform on Kubernetes is like your leveling platform
for pathologists to annotate the image?
Yes, exactly.
The pathologist is enriching the data by annotating and labeling the data.
And then we use the enriched data to train a model, their project.
So you are using SageMaker for that? Can you tell me more about the benefit?
Yes. So previously we had an infrastructure that was very static.
We migrated to SageMaker so all the pipeline we had
we containerized it into a docker.
And then, we are using the same docker into SageMaker training.
So it was very easy to migrate.
And now we train the model into SageMaker with a FSx and IAM
for security and I/O performance.
And so SageMaker are building the model, and after, what are you doing with that model?
So the model is saved into an S3 bucket
and we export the model and the results
into our project into Kubernetes
so the result is showed and displayed to the pathologist
so he can validate or refute the model.
Okay, and when the model is validated, what is the end of the story?
When the model is validated, we freeze the model and we can move to the inference part,
same on Kubernetes.
Okay, cool. And after, it is used by the hospital, is that?
Yes, correct.
Can you tell me more about the benefits of that architecture?
So compared to the previous architecture, there's three big benefits.
The biggest one is that our data scientists can work on many projects at the same time.
They can change projects, switch in term of servers,
they can run in parallel, thousands of training.
Second is they gain time.
In terms of performance, the training is up to 30 times faster.
And last but not least, we gain in terms of cost infrastructure, up to 30%,
because when we are not using the resources, we are not paying for it.
That's what I call the dynamic infrastructure.
So back on security. I think you all need to comply with certification.
Can you tell me more about that?
Yes, in the medical industry it's a serious subject.
So there's many certifications we need to comply with
and thanks to IAM we have very good control of the data.
We can document it and comply with the certification.
One certification we like to have with AWS is HDS to prove the security of the data.
Okay, and for complying with HDS you need to be in the same regions as the data?
Yes. Also with the region for a project in Germany, we keep the data in Germany.
So thanks for sharing that.
You're welcome, Mathieu.
And thank you for watching 'This Is My Architecture.'