PRIYANKA VERGADIA: Welcome to Get Cooking in Cloud,
where we share the best recipes to apply in your cloud kitchen.
I am Priyanka.
JENNY BROWN: And I'm Jenny.
And in this episode, we'll be making
a loaf of gluten-free bread.
PRIYANKA VERGADIA: Yes, we will.
There's a lot going on in this recipe
that we will need to pay attention
to-- keeping ingredients separate from the allergens,
keeping ingredients separate from each other,
and making sure our space is allergen-free.
JENNY BROWN: Much like with cloud security,
we need to keep things safe from external threats,
and even from mixing internally before it's appropriate.
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PRIYANKA VERGADIA: Dinner Winner is an application
that collects recipe submissions from users
all over the world and posts regular winning
recipes for everyone to enjoy.
JENNY BROWN: The recipe submissions
need to be assessed for clarity and then
scrubbed for any identifiable information
before they are sent on to judging.
PRIYANKA VERGADIA: The anonymous judging
takes place, after which winners are contacted
and their recipes are posted to the application.
JENNY BROWN: Submitted recipes can't mix with reviewed recipes
due to the potential private information from contestants.
So it's critical to uphold that separation.
Just like with creating gluten-free recipes,
it's important to not only have gluten-free ingredients,
but a gluten-free space as well.
PRIYANKA VERGADIA: Exactly.
Our recipe is simple, but this situation is complicated.
And for Dinner Winner, due to the high number of submissions,
that's a lot to handle.
JENNY BROWN: Do we need a dedicated facility or just
a strict cleaning policy?
PRIYANKA VERGADIA: Well, it depends.
Let's see how their system works today.
During the competition times, users upload their recipe
in the text format.
These recipes get stored in blob storage
from where they're pretty manually
checked for private information like emails and phone
numbers of participants.
This private information is then removed
before sending to the judges to vote.
The winning recipe then makes it on the platform for everyone
to see.
JENNY BROWN: The problem with it?
Well, there's a lot of problems with this arrangement.
One, because this is a manual process with a ton of volume,
this system will scale badly.
But the biggest problem here is security.
It's difficult to know what's been reviewed
and what's been updated and what still
has private information in it.
PRIYANKA VERGADIA: What if just one recipe submission
gets accidentally shared with the judges with a contestant's
name and contact information?
This will potentially make the contest unfair
and can lead to brand damage for Dinner Winner, which
sounds like a losing situation.
JENNY BROWN: And since Dinner Loser
doesn't have the same ring to it,
let's make sure they can keep their recipes
clean of personal information just as we need to keep
this surface clean of gluten.
PRIYANKA VERGADIA: Just like Dinner Winner,
in every organization, data protection officers
like you face an ever increasing amount of data,
data that must be protected and treated appropriately.
Quarantining and classifying that data
can be complicated and time consuming, especially
given hundreds or thousands of files a day.
JENNY BROWN: And what if you could take each file,
upload it to a quarantine location,
and have it automatically classified
and then moved to the appropriate location
based on the classification result?
PRIYANKA VERGADIA: In the next few episodes,
we will show you how to implement such a system
by using Cloud Functions, Cloud Storage, and the Cloud Data
Loss Prevention API.
JENNY BROWN: Dinner Winner needs an automated process
for sorting submissions and categorizing reviewed
submissions.
PRIYANKA VERGADIA: The ingredients?
App Engine for front end, Google Cloud Storage to store recipe
submission files, Pub/Sub for messaging, Cloud Functions
for some quick automation in serverless fashion--
JENNY BROWN: And the most important ingredient--
DLP API to detect private information.
PRIYANKA VERGADIA: Now let's put this all together
and stir it up.
Let's say the front end is an app engine where
the user submits the recipe.
The user would upload the text file,
including the recipe and info types,
like the name, date, email, and phone numbers in the web
interface.
The uploaded file is sent to Google Cloud Storage.
This triggers a Cloud Function to create the data loss
prevention job in Pub/Sub.
JENNY BROWN: Once the event is received by Pub/Sub,
it triggers another Cloud Function,
which calls the DLP API and looks
for the confidential information in the recipe files.
Once found, it moves the file to a separate storage bucket.
If the file does not contain any confidential information,
like the info types email, address, phone number,
then the function moves it to another bucket.
This request flow keeps the confidential data separate
from the non-confidential and is fairly automated,
such that as soon as the file hits the Cloud Storage bucket,
all other processes kick off automatically
to protect the data.
PRIYANKA VERGADIA: Now that we understand
the problem and the use case, we know
exactly what needs to be done to implement the solution.
JENNY BROWN: And next week, we'll
reveal our step-by-step plan for Dinner Winner.
And maybe we'll even get to that gluten-free bread.
PRIYANKA VERGADIA: Yeah, but first,
we will need to avoid cross-contamination
by deep cleaning the kitchen.
JENNY BROWN: And since Get Cleaning with Cloud
isn't quite what we're going for,
we've got some behind the scenes work to do.
PRIYANKA VERGADIA: While we're at it,
don't forget to give us a Like, comment,
and subscribe to learn what you can cook up with the Cloud.
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