BYTE the Cloud

Chris 0:00
All right, let's jump right in. Today we're tackling Amazon AppFlow.

Kelly 0:03
Sounds good

Chris 0:04
now, as mid level cloud engineers, I'm sure you've all dealt with data integration before. Oh yeah, definitely it can be. Well, it's often super complex, yeah, code heavy, yeah, and honestly, kind of a pain. But what if there was a way to move data between your favorite sauce, apps like Salesforce or market or anything like that, and AWS services all without writing any code.

Kelly 0:28
That's where Amazon AppFlow comes in. It's like having a data super highway, connecting all your different apps and services like a universal translator for your data, moving it back and forth without needing to build custom integrations.

Chris 0:39
I like that analogy. So imagine you need to analyze customer data. You've got some in Salesforce, and you want to compare it alongside your sales figures from an internal app, one that's hosted on AWS, right? That would usually involve tons of custom scripting APIs,

Kelly 0:55
yeah, late nights probably,

Chris 0:57
oh for sure, yeah. But with AppFlow, you just set up a flow to automatically pull that sales force data, maybe into an S3 data lake, or right into Redshift to analyze it. And that's

Kelly 1:05
just one example. We're talking about, taking, say, marketing leads from Marketo, putting them straight into a DynamoDB table, or moving financial records from SAP right into Redshift for reporting. You could even sync data between custom applications built on AWS. So it's

Chris 1:21
more than just point to point data transfer.

Kelly 1:24
Absolutely it's about having control over your data pipelines without getting bogged down in the complexities of coding or infrastructure management. You can transform data on the fly, like you could mask sensitive information standardized formats, enrich it with context all while it's being moved.

Chris 1:39
So you could strip out credit card numbers before sending data to a data warehouse, exactly. So how does AppFlow fit into the larger AWS ecosystem? Is it a standalone thing, or does it work with other services? It's

Kelly 1:52
definitely not a standalone thing. It's like a hub that connects to a whole network of services like IAM for controlling access, CloudWatch for monitoring and alerting. Oh, okay, and even Lambda for triggering custom functions based on your data flows.

Chris 2:06
So you could use AppFlow to pull data from a CRM and then trigger a Lambda function to clean it up and validate it all before it gets put into an S3 bucket

Kelly 2:14
Exactly. Or you could even imagine using it to stream real time data from an IoT device into a Kinesis data stream, you could analyze that or even trigger an email every time a new file shows up in an S3 bucket. It really opens up a lot of possibilities. Yeah, it takes care

Chris 2:29
of a lot of those tedious data tasks that we cloud engineers end up doing. Right? Yeah. Now I know you're here to ace that next cloud certification exam, and AppFlow will probably be on it. So let's dive into some practice questions so you can get a taste of what to expect. What

Kelly 2:42
to expect. Okay, great idea. Let's test your knowledge. Here's the first scenario. You need to move data from an old on premises database to an S3 data lake. This is part of a cloud migration project, but the source database has some sensitive customer information that you need to hide before it gets to the lake. How would you handle that using AppFlow. So we're

Chris 3:02
talking about data security and compliance right away, if I remember correctly, AppFlow can transform data right could we use that to mask the sensitive data? You're

Kelly 3:12
on the right track. You can define data transformations as part of your flow. In this case, you would use a masking transformation to replace sensitive fields like credit card numbers or social security numbers, things like that, with Placeholder values, or just remove them entirely. So

Chris 3:28
while the data is moving from that database to S3 AppFlow would just automatically mask those fields on the fly, that way the sensitive data is protected both during the transfer and while it stored in the like

Kelly 3:40
exactly. You build security best practices directly into your data pipeline, and you don't have to do any custom scripting or anything manual. Okay,

Chris 3:47
so it's not just moving data, it's moving it securely and efficiently. I'm liking this AppFlow thing more and more. Okay, what's next? Let's

Kelly 3:53
say you have a web form and you need to store data from that form in a DynamoDB table, but the web form submits data in JSON format. DynamoDB wants a tabular structure. How can AppFlow bridge that gap?

Chris 4:06
Ah, the classic data format mismatch. So AppFlow can transform data formats too Exactly.

Kelly 4:11
AppFlow has a variety of transformations specifically for different data formats. In this case, you'd use the JSON parsing transformation. It'll pull out the fields from the JSON data and map them to the right columns in the DynamoDB table.

Chris 4:24
So AppFlow is like a translator, turning that JSON into something DynamoDB understands precisely.

Kelly 4:29
And you do all of this in the AppFlow interface. No need to write any code to do that JSON parsing and data mapping.

Chris 4:36
Okay, so AppFlow is all about making data integration simple, secure and maybe even a little bit fun, but there are limits, right? Yeah,

Kelly 4:45
of course, like any tool, let's say you have a real time application that needs to analyze customer behavior data and it's streaming in from lots of sources, you need to process that data for insights in almost real time. Can AppFlow handle that? Hmm,

Chris 4:58
that's a good question. Question, we've mainly been talking about batch data transfers with AppFlow, real time streaming seems different. Exactly.

Kelly 5:04
Appflow is great for scheduled batch processing, but it's not designed for continuous, high volume real time data streams. So

Chris 5:11
I'd need something like Kinesis data streams to build a real time data analysis system,

Kelly 5:16
right? Kinesis is perfect for handling that kind of real time streaming data, it would be a much better fit for that kind of situation. Appflow is great for a lot of data integration tasks, but it's not a one size fits all solution. Good

Chris 5:30
point understanding the right tool for the job is key. Okay, let's keep going with these practice questions. I'm getting more and more confident,

Kelly 5:37
awesome. Okay, let's keep practicing with AppFlow. Ready for another scenario? Yeah, hit me all right. Your company has a BYOD policy. Bring Your Own Device, and employees are using all sorts of devices to access sensitive data. You need to make sure that only authorized devices can trigger AppFlow flows to move data. How would you make that happen? That's

Chris 5:59
a tough one. So we need to tie AppFlow actions to specific devices, right? Well, AppFlow works with IAM, doesn't it? Can we use IAM policies to do that? You're

Kelly 6:08
thinking in the right direction, but IAM is really for user based access control. It doesn't deal with device level stuff, yeah, but you could use IAM along with something like device certificates or a mobile device management solution, MDM, okay,

Chris 6:23
so we could give certificates to approve devices and set up AppFlow to only allow flows from devices with those certificates, or we could use MDM to set up policies on the devices and restrict AppFlow access based on those policies Exactly.

Kelly 6:39
It's all about adding layers of security. Appflow gives you the flexibility. To work with your existing security setup no matter how the data is

Chris 6:46
being accessed. It's not just about knowing how to use AppFlow. It's about understanding the whole security strategy, right? I like that. What's next?

Kelly 6:52
Let's talk about cost. Say you're working with a startup, okay, they need to move data from a bunch of sauce applications into an S3 data lake, but they're worried about the cost of using AppFlow. What advice would you give them to keep their costs down?

Chris 7:06
That's a good one. Yeah, especially for startups. So we want to get the most out of AppFlow without spending too much. AppFlow's pricing is based on the number of flows you run and how much data you process, right?

Kelly 7:16
That's right. So there are a few things you can do. First, you can schedule your flows to run when demand is lower, like off peak hours. That can sometimes be cheaper,

Chris 7:26
like scheduling big compute jobs overnight Exactly. And

Kelly 7:29
second, be smart about the data you're moving. Do you really need all of it? Or can you just pick and choose what you need? That's

Chris 7:36
a great point. Filtering out unnecessary data can make a big difference, right? And you could also

Kelly 7:41
look at compressing your data before transferring it. That'll reduce the data volume. So

Chris 7:46
it's about being smart about how you use AppFlow and making it work with your budget. Yeah, all right. Give me another scenario. Okay, how

Kelly 7:52
about this? You need to build a data pipeline that moves data from an IoT device that's your streaming source into a Kinesis data stream, then you want to use AppFlow to pull data from that stream into an S3 bucket every so often for batch processing.

Chris 8:08
Okay, so this is combining real time streaming with batch processing. Interesting. I don't think you can connect AppFlow directly to a Kinesis data stream. Can you AppFlow is mainly for SaaS and AWS

Kelly 8:22
sources. That's right. Appflow doesn't do streaming sources directly, but you can use Kinesis data Firehose to connect the stream and S3 Oh, I see. So Firehose would pull the data from the stream and send it to an S3 bucket. Then you could set up AppFlow to grab data from that bucket for batch processing. So

Chris 8:40
it's like a relay race. Kinesis handles the streaming firehose, gets it to S3 and AppFlow takes it from there for batch processing Exactly.

Kelly 8:47
It's about using the strengths of each service that's really

Chris 8:50
helpful for understanding how to build complex data flows in AWS.

Kelly 8:53
And that kind of thinking is what you'll need for the exam. Okay, I'm ready for more. What else have you got? All right, let's see if you can handle this one. You have a marketing team. They use Salesforce a lot for their campaigns, and they want to keep track of every little change made to customer records in Salesforce, like if contact information is updated, if a lead status changes, or if a new opportunity is created, they want to see all those changes in a real time analytics dashboard. Can AppFlow help them with that.

Chris 9:21
So they basically want a live stream of changes from Salesforce. But we talked about how AppFlow is more for scheduled transfers. Can it really do that kind of real time tracking?

Kelly 9:31
You're right. Appflow isn't really made for continuous change tracking. It's more about moving data at specific times.

Chris 9:38
So we need something else to handle those Salesforce changes in real time, exactly

Kelly 9:41
something like AWS database migration service DMS. Oh, okay, it has changed data capture features that would be perfect for this. Yeah. DMS is built to track and copy database changes as they

Chris 9:54
happen. So it's important to know when not to use AppFlow too, right? Every tool has its strengths, okay? What? Else can you throw at me? Let's

Kelly 10:00
talk about data validation. You're working with a bank that needs to move sensitive transaction data. They want to move it from their own system to an S3 bucket for auditing. They have strict compliance rules and need to be absolutely sure that the data transferred by AppFlow is exactly the same as the original data, no mistakes or corruption allowed? How would you make sure that happens? Wow.

Chris 10:24
So data integrity is really important. Here. We need to be able to verify that the data in S3 is a perfect copy of what came from their system. Yeah. AppFlow does the secure transfer, but does it actually check that the data is identical? That's

Kelly 10:38
a good question. AppFlow is reliable for transferring data, but it doesn't do those deep comparisons or checksums to guarantee that every single bit is the

Chris 10:47
same. So we would need to check for differences after the transfer is done, right? You

Kelly 10:51
could use AWS Lambda functions to do that. Oh, okay. You could set them up to trigger when AppFlow finishes a transfer. Then the Lambda function could compare the source data and the S3 data and let you know if there's any mismatch. So

Chris 11:02
we're basically using Lambda to add extra data validation to AppFlow Exactly.

Kelly 11:07
You're building a custom solution that fits their specific needs. All

Chris 11:11
right, one last challenge to test my AppFlow skills. Okay, here's a tricky

Kelly 11:14
one. A company is using AppFlow to move data from a sauce application into Redshift for analysis, but they've run into a problem. Some of the data fields in the sauce application have special characters in them, and those characters are causing errors when they try to load the data into Redshift. What would you do?

Chris 11:34
So it's a data quality issue, those special characters are messing things up. Yeah. Could we use App slows, data transformation features to fix it.

Kelly 11:41
You got it. Appflow has functions for cleaning up and preparing data. You would use the Replace or Remove functions to handle those special characters so

Chris 11:50
we could either switch them out for something else or just get rid of them before the data goes to Redshift, exactly.

Kelly 11:55
And you can do all of this in AppFlows, visual interface without any complicated coding. That's

Chris 12:01
really impressive. Appflow can handle so much, from basic data transfers to complex transformations and validations, I feel a lot more confident about using AppFlow now. That's

Kelly 12:10
great. Remember, the key is to know what it can do, what it can't do, and how it works with other AWS services. Appflow is a really valuable tool for managing your data integrations. And with what you've learned today, you're well on your way to becoming an AppFlow Pro. Well, thanks

Chris 12:28
for all the insights. It's been a great deep dive into AppFlow. Thanks for having me to everyone listening. If you want to simplify your data integrations, learn more about the cloud or just show off your AppFlow skills, I definitely recommend checking out this service. It can change the way you work with data in the cloud. That's it for our deep dive today. Keep learning and keep exploring the amazing world of AWS.