Welcome to Solving with AWS Solutions.
Your deep dive into architectures built by AWS
that are ready to deploy instantly
in the cloud.
I'm Tyler and with me today is a Aijun,
a solutions builder who will take us through
the AWS Dev Ops Monitoring
dashboard solution.
Our customers are telling us they now want a
simple and efficient way to capture and
monitor operational matrix in their
CICD pipeline.
That's why we built AWS Dev Ops
Monitoring dashboard, a solution that
automates this process and helps to identify
areas to improve.
So let's dive right into it.
So where do I start with this solution?
We can start from the solutions landing page.
So this landing page has an
architecture diagram, a link to source code,
CloudFormation template, an implementation
guide and a button that you can click to
launch the solution into your AWS account.
Very nice.
So can we get into the architecture for a
minute?
Of course.
Overall, the architecture splits into four
parts that data ingestion,
transformation, analysis and realization.
OK, so let's talk about the first
phase data ingestion.
Sure.
So it all starts from your AWS CodePipeline.
When you initiate any activity in
the pipeline, such as push a code change to
AWS CodeCommit or on a build using
AWS CodeBuild.
All of this activity is where create
an event.
So the event will be captured by an Amazon
EventBridge Events Rule.
That will send the data to Amazon Kinesis Data
Firehose stream for downstream processing.
So how is this data actually processed within
the solution?
Yeah.
So we have a Lambda.
We then added on Kinesis Data Firehose
for data transformation.
Then Lambda will extract relevant data from
not even state then send that data to an
Amazon S3 Bucket.
Then there is an Amazon Athena database runs
queries against accessory data, then return
the result to Amazon QuickSite where they show
what is created to realise that data.
So from what you said, it seems that AWS
Lambda is seen all through out the back end
of this solution.
So does this mean that it's truly serverless?
Yes, the solution is
built completely serverless.
Awesome.
Can you tell me a little bit about the types
of data that you visualize with this solution?
So far, the solution provides seven
different metrics, for example.
Meantime, to Recover Metric and Pipeline
Metric and more.
We plan to add more metrics in the future.
That sounds great.
So can you take me through some of the
dashboards?
I would love to.
This is Amazon QuickSight dashboard.
You can see here we have multiple types,
one tab for each metric.
So each metric provides a monthly, weekly and
the aggregate view of the metric at the top
of each tab.
There are custom filters that you can use to
filter data as needed.
So this Mean Time to Recover metrics tells you
how long and how often application went down
and the average time it takes to
restore the application.
That's awesome that this is going to show me
application downtime, because I definitely
need to know if and when that happens.
I'll need to be able to pick it back
up really quickly.
So that's great.
Yeah, absolutely.
So monitoring downtime is very important for
our customers to improve their application.
Can you show me another dashboard?
Of course.
This is the pipeline activity dashboard.
So this dashboard presents database Code
Pipeline Execution,
State, Frequency, Duration, along with other
metrics I stage and the action network.
So you can easily find out which pipelines
fail the most.
Which pipelines takes longest time to run and
which pipelines are the most active
over the time.
So what about data refresh?
How does that occur in the solution?
The solution is designed to process data
in near realtime.
So the data in the dashboard will be refreshed
when you refresh the page in your
web browser.
Awesome.
And I have one more question.
So AWS QuickSight is I know the machine
learning business intelligence tool that will
service that Amazon is using.
But if I were to use a different tool, like a
third party tool, is that available?
Yes.
So you can use your own VI tool to customize
the data from Amazon Athena database.
The solution provides an example for how
to do that.
OK, great.
So I will have that step by step if needed.
Well, this has been awesome.
I really appreciate you showing
me the solution.
My pleasure.
Thank you.
That's a great way to explore metrics in your
CICD pipeline.
You can use this solution to capture and
monitor Dev Ops metrics and identify
opportunities to improve your
software delivery process.
Check out this solution and many more on the
AWS Solutions website.
Thanks and see you soon.