SPEAKER 1: Datadog is
an observability platform that
provides full visibility across your organization.
We spend end to end from
your infrastructure and your networks,
your applications, and services
all the way to your end user.
As you know it's like SQL Server Admins,
a lot of these will come into place
and your infrastructure is obvious important
when your end-users are doing so that white box
versus black box monitoring is also very important.
This enables everyone, that's
apps developers and even parts of your business to have
a shared understanding of your systems and
the ability to immediately
resolve problems as they arise.
Just in terms of database,
modern software applications are incredibly complex and
the needs for your databases are
also coming from all angles.
You'll have multi-tiered architectures with dozens of
technologies spread over hundreds
or thousands of computing units.
We're talking about development teams are
deploying updates more frequently
than ever to get updates in front of customers.
Without a single source of truth to
understand your environment from all angles,
teams can't reliably detect and troubleshoot issues.
That means it results in
constant firefighting and frustrated teams.
Traditional monitoring tools rely
only on the visibility to one aspect.
For example, metrics will indicate
that something is wrong but
the lack the details traces can point to a general area.
Traces from your application source code for
example but they're not specific enough.
Then UX tools luck
the integration with the back-end data.
If you can say your user says, hey,
when I run this search on the website it's slow.
It's often difficult to
understand what happens when it gets
the API and then when the API calls the database,
how does that response get back into the front end?
Then finally logs might have rich detail but often
the volumes are very high
and then there are varying qualities.
You might end up with like
a needle in the haystack problem.
You know that your data is in there
but finding the right query to
get at the data in aggregate becomes difficult.
Now, Datadog provides a unified Software as
a Service observability platform that
addresses the unique challenges
of modern software application.
We collect all types of observability and
make them available in a single application.
That includes metrics,
traces, logs, user activity,
database monitoring, and we've got
over 500 pre-built integrations.
It's easy to get end to end visibility
no matter what you're using in server.
I'll talk about that a little bit because SQL Server
can be deployed in a lot of applications.
But with Datadog, your teams have
a single source of truth so they don't need to
switch context when they're troubleshooting issues.
For example if you found an important log from
one service and then you go to look at the traces,
what we allow you to do is keep that context as you
pivot between different areas
with different aspects of the product.
Our machine learning-based alerts help you automatically
detect issues you didn't even know to
look for and resolve them quickly.
For example in the database monitoring area,
if you have an explained plan that's changed over time,
it's going to be able to compare that one that you've
got today versus one before,
just to see something on
the database at back-end change,
maybe you've changed like SQL Server versions for
example just to see what's
actually happening to your query now,
then you move to convergence.
Finally, with
our collaboration and workflow integrations
Datadog has you covered no matter how your team operates.
Before we dive into the DBM side.
If you're in the Windows ecosystem
which is pretty common,
I just want to go over quickly some of
the integrations that we thought
on the Datadog side all the way
up to the infrastructure level.
If you're monitoring your database
from the networking side,
the Cloud side,
Infraside, that's like CPU,
memory, disk,
that thing, we've got you covered.
What we can do is allow you to
collect real-time metrics and logs
from most Azure managers devices.
All the things that you've got deployed in
your Cloud already we can help you with.
Data dogging go beyond Azure and
AKS to monitor all of
the services in your application backend.
For example, we've got a few
pulling through here in the screen.
But basically if you're running SQL Server as well
as Postgres as well as something like
Front Door, we've got you covered.
We provide dozens out of the box integrations,
including those popular services like maybe Cosmos DB,
SQL Servers we talked about,
Azure Functions, Azure AD services,
and we automatically collect health metrics and
diagnostic logs about each service
from Azure you get at Cloud.
With our pre-built dashboards you can start visualizing
your application's health and performance in minutes.
Now, for developers and operators,
this means that you can quickly identify
those root causes that we were talking about before.
Now it's easier than ever to
get started with Datadog for Azure.
Recently we announced a partnership
between Datadog and Azure
to allow you to sign up for
a Datadog in the Azure portal.
Now, if you're already a DataClient
and you're already on Azure and
you've already got them integrate,
sometimes what I've found is that this can be
pretty handy if you're still pretty new with it.
In order to set up something like
SQL Server or if you want to move to
an ingredient say US
3 instead of US 1 we should get to end it.
This can be a nice integration
because it's a one-click that
creates a Datadog account as well as the SSO,
so you can get both.
Datadog Database Monitoring or DBM provides
visibility into SQL queries running on your databases.
These are the queries that I
would be running for example.
Instead of running the script
and then checking something,
putting in new Excel spreadsheet
and then looking at later.
What we can do is you can troubleshoot
the database performance issues by drilling into
those frequently-used queries and analyzing
historical trends in the accrues
metrics and execution plan.
Whether you run self-hosted SQL Servers,
Azure SQL Database,
or Azure SQL Managed Instances,
DBM can provide deep visibility
into the database your applications depend on.
But in case you've yet to come
across SQL Server in the wild,
it's a relational database system
developed by Microsoft that uses an extension of
SQL called Transact-SQL for its queries.
Now, this is important because using
T-SQL you can write queries that SQL Server
will automatically compile in
cash as execution plans in order to minimize latency.
I can play this video a little
bit again here, it went fast.
But with DBM you can sort
your queries by average latency and
drill into slow queries and
expect recent trends in their performance.
If a query begins to execute more
slowly without an obvious reason,
remember I was doing
a spot checks those who weren't around.
It was hard for me to tell it what change.
It may be experiencing something called
plannery brushing which was new to me at the time.
It is something that I had splurge.
By selecting a query in DBM,
you can compare its execution plans over time to identify
potential directions and the most cost effective plan
to reduce that execution latency.
Like I mentioned, as I was moving between
database engine versions,
a lot of times I've being doing straight migrations or
straight upgrades and maybe the operating system
maybe database engine,
but not looking at the functional level
of the database engine itself.
Some of that was new to me at the time.
Now, after expecting
a queries execution plan you can navigate to
the Metrics tab to visualize trends and
performance and resource usage
and we'll demo that here in a second.
For example, DBM provides visibility need
TO each queries memory grant usage.
That's the memory used to reserve and
store temporary data for workspace queries.
Now, if you notice large disparities
between queries received memory grant
and use memory grant,
the query maybe reserving
more memory than it needs and putting
your database at risk of
memory pressure which you've
probably seen before as I said.
As a result, your database may experience
abnormally long wait queues
and maybe decrease concurrences.
That means fewer people can do many things at once.
It means that you can only handle
so many sessions at a time.
A lot of people will talk about transactions.
We'll talk about queries here
because some queries aren't transactional,
some are, there's one of
those mentals aren't things that sticks in my mind.
But by visualizing your databases
memory metrics with DBM,
you can decide if you need to enable
memory grant feedback for
example which will allow SQL server
to automatically adjust your memory grant configurations
based on past query performance.
To detect performance issues you can
use your SQL Server Integration to create monitors,
tracking the number of queries in
queue from memory grant allocation.
You can also configure an anomaly monitor that
would identify if there's a series of query that
begins to take an abnormally long time to execute.
In addition to the three level insights,
so when we're looking top-down,
you can also get,
the SQL Server integration will also get
you higher-level visibility to
your databases health and performance.
We've done an out of box
dashboard that I'll show in a moment here that
will help you visualize the metrics such as connections,
system memory, and throughput.
Those let's metrics affordable
signals which we're going to cover in a second.
Then from there you can quickly pivot
into DVM in order to get deeper insights.
For example, looking at the queries
that are running on hosts,
they exhibit high resource utilization.
Let's say for example you're looking
at the query on Maslow,
all the queries running on all your database.
What you want to find out is this query,
since we're taking out a bunch
of time, there's like a large [inaudible].
How do I figure out which servers those are running
on instead of going into the server
and just on putting the power cable,
plug it back in, and using
coppice and strategy, what is amplified.
How do we drill into all these?
Azure Database for MySQL and Postgres as well aren't
fully managed database services
that feature built-in security controls,
automated maintenance on a wide range
of additional platform features.
Not only SQL Server but also MySQL and Postgres as well.
By monitoring your Azure managed
databases with data around DVM,
you can troubleshoot inefficient queries and areas
to ensure that your databases continue to run smoothly.