SPEAKER: Key Visualizer is a visualization tool
that helps you analyze the access patterns in your Cloud
Bigtable instance.
The Cloud Bigtable console lets you monitor your application
with line charts, which is effective in most cases.
However, how would you know what is causing high CPU,
if there are any hotspots or large rows,
or if a MapReduce is effecting your serving latency?
That's why we are announcing Key Visualizer for Cloud Bigtable.
It shows you read and write patterns in two dimensions--
over time and across keyspace.
It helps you find or prevent hotspots.
It helps you find rows with too much data, which
can cause performance issues.
And you can see if your key schema is balanced.
Key Visualizer has a heat map that shows time horizontally.
In this example, we see the number
of operations over one week.
The keyspace is shown vertically.
A heat scale shows values of a selected metric.
For example, ops-- from cold, representing zero,
over blue, to purple, to red, to yellow,
to glowing white for very high values.
The tool tip will show us details
about this metric for a particular time and key range.
In this example, notice that some key ranges,
like the one at the bottom, exhibit a diurnal pattern,
whereas, other ranges are very cold.
Also notice the white glowing line
in the middle that shows the busiest key range.
The diagonal lines represent linear scans
possibly from a MapReduce job.
The bar chart at the bottom shows average values
across all visible keys in 15-minute intervals.
Similarly, the bar chart on the right
shows the averages over time per key range.
This peak, again, shows our busiest key.
Bigtable developers often create keys with a prefix hierarchy.
In this example, we see keys that
are constructed with delimiters, such as slashes or dashes.
Key Visualizer has a heuristic that automatically
extracts the prefix tree from your key schema, if available.
The key prefix hierarchy is shown on the left side.
We can see that the behavior of a table
often correlates with the key prefixes, as in this example.
When we click on a prefix, it will
zoom into the corresponding key range.
We can also zoom and pan by using the scroll wheel
or dragging.
Key Visualizer offers you these 11 metrics.
Ops is the sum of read and write operations.
The three warnings metrics--
read or write pressure index and large rows--
can discover problem areas.
Then, we have read metrics, write metrics, latency,
and the amount of data stored.
Key Visualizer automatically analyzes the performance
of your Bigtable instance.
This may involve trillions of metric values.
Not only does Key Visualizer aggregate
all of these metric values to visualize them in the browser,
it also performs a detailed analysis
on your table's performance.
This produces the following metrics--
read pressure, which is an opaque function of read CPU,
read key length, which is the number of read ops waiting
to be executed, and latency.
Write pressure is a similar function
to detect bad performance for writing and large rows, which
will flag any row that contains more than 1 gigabyte of data.
The result, shown in this view, lets us discover and prevent
hotspots.
Best of all, these computations won't cause any performance
degradation on your table.
And all this is free.
Let's now see how we made this easy for you.
Key Visualizer opens by default with the ops metric.
This gives us an overview of the activity in your table.
Then, you check if there are any warnings at the top bar.
If there aren't, that's good news.
Your table's performance is, most likely, fine.
This example has three warnings.
One of them is severe, as indicated
by the three exclamation marks.
Clicking on the Read Pressure Index warning
brings us to the Read Pressure metric,
where we see immediately where and when the problem happened.
We now zoom into the white glowing stripe.
The tool tip shows us which keys are causing problems.
At the top, we see the worst problem.
It's a single key that has been stressed
for more than three hours.
We can see the precise name of the offending key.
We can see that it was using nearly 600 million nodes
worth of CPU, which is more than half of a server's CPU.
And it tells us what caused this bad performance.
This row contains 9.22 gigabytes of data,
which is way more than the recommended 256
megabytes per row.
In all of these examples, we were looking
at one metric at a time.
Very often, however, we want to compare different metrics.
Rather than switching between metrics,
we can show all the metrics and their values
together, on the right.
When we expand these, we can see all these metrics
in miniature views.
The zoom and pan operations are synchronized,
so we could compare details for each symmetric.
Key Visualizer for Cloud Bigtable
visualizes the key access patterns
in your table, helps you find hotspots, and large rows.
It extracts the key prefix hierarchy, if available.
Key Visualizer analyzes trillions of metric values
to point you to problem areas.
And it does this without any impact on your Cloud Bigtable
performance.
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