Other Services
364.other services overview
365.xray
Now, let's talk about another service that's called AWS X-Ray. So, when by default some people do
debugging in productions, so, when your application is actually deployed, the good old way, you would test
locally, then you would add log statements anywhere. Maybe look into how it logs, then you would re-deploy
in production, and the see if you can find the problem this way. And the problem is that we have logs from
different services and different applications. Doing log analysis it is very hard because we have to combine
everything. So, if you have one application that's called a big monolith, so, one giant application, it's sort of
easy to do debugging. But if you have distributed services they're connected through SQS queues, SNS
topics, they're decoupled and so on, it becomes really, really hard to trace and see what is happening within
your system. So, you have no common view of your entire architecture. But to solve that problem, you can
use AWS X-Ray. So, with X-Ray, you're going to be able to do a tracing and get visual analysis of your
application. So, X-Ray, once you enable it on your services, then you'll get a full picture of what is happening
for each service.
And see where they're failing, their performance, and in case one request goes wrong, you will be able to
visualize it directly into the X-Ray console. So, the X-Ray advantages, is to do troubleshooting of the
performance through the bottlenecks, or to understand the dependencies in a microservice architecture,
because they're all connected as you saw in the previous graph. We can pinpoint a service issue with
tracing. We can review a specific request behavior, and find the errors and exceptions for that request. We
can know if we're meeting or not our service-level agreement, or SLA, meaning are we replying on time for
all the requests. And if we're being throttled, if we're being slowed down, where is it happening, in which
service? And finally, what or which users are going to be impacted by these outages. So, X-Ray really is
great when you see, distributed tracing, troubleshooting, and you want to have a service graph. That's it, it's
a more complicated service to use, so, I will not do any hands-on. But you get a high level of review that will
be enough for the exam. So, hope you liked this lecture, and I will see you in the next lecture.
366.Amplify
So now let's talk about AWS Amplify and it's a complicated service, but at its core I want you to think of it
as a web and mobile application development tool. So this Amplify will basically allow you to integrate a lot
of the stack of AWS into one place to build your web and mobile applications. So you're a developer, and you
know you wanna do a lot of things. You wanna first create backends. So you're going to use the Amplify CLI
to create an Amplify Backend. And this backend is going to internally use a lot of resources from AWS that
we know. Amazon S3 for data storage, Amazon Cognito for identity, AppSync for APIs, API Gateway for APIs
as well, StageMaker for machine learning, Lex for text detection, Lambda for functions data service,
DynamoDB for data and so on. And so the idea is that thanks to Amplify, we have one place to configure
authentication, storage, API will be REST API or GraphQL API, CI/CD, PubSub, Analytics, AI/ML predictions,
monitoring, and so on. Then you connect your code. It could be from anywhere from GitHub, from
CodeCommit on AWS or Bitbucket, GitLab, or you can upload your code directly. And so you would go ahead
you integrate all these backend services directly from within Amplify.
consolidated backend tool for utilizing all
kinds of AWS services: AppSync/API
Gateway, Cognitio-idp, S3, Lex/SageMaker,
Lambda, SNS/SES, DynamoDB and so on