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Displaying posts with tag: charts (reset)
Explode Charts To Drill In With VividCortex

VividCortex is designed with two key scalability requirements in mind: it must perform well in large environments with many hosts, and the UI must help users understand and inspect those environments easily. The universal time selector, the host filter, and other features let you start with a top-level summary, grasp what’s happening in your entire environment no matter how many hosts, and then drill into hosts, time ranges, queries, and metrics of interest. We’ve enhanced our charting and graphing capabilities to make this same zoom-in-drill-down inspectability easier, too.

When you load a charts dashboard, you’ll see charts that contain one line per metric. For example, if I view my MongoDB dashboard and use the top-navigation filter to quickly limit the view to “checkpoints,” I’ll see the following single chart.

Notice how the subtitle says “Average of 5 hosts.” Each line on this chart is an average of 5 hosts’s …

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Custom Dashboards in VividCortex

VividCortex now offers custom dashboards, which are collections of charts you can curate as you wish. Custom dashboards are shared across your team, so they're a great way to ensure everyone has access to the metrics that you use to monitor and inspect system status and health. And you can give them meaningful names, which is one of only two hard things in computer science, so your dashboards can be full of win.

In the "Choose Dashboards" navigation menu item, there's a new option to "Add Custom Dashboard." Type in a name, and then you'll have an empty custom dashboard. You can also clone an existing dashboard (either custom or prebuilt) to get started.

When you're viewing a custom dashboard, it's easy to add a chart to it. Just start typing and you'll get autocomplete suggestions based on chart and metric names. There's turnkey charts for MySQL, PostgreSQL, MongoDB, Redis, Cassandra, operating system metrics, and much more.

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Correlated Metrics in Monitoring

If you work with monitoring or monitoring tools much, you’ve probably seen the phrase “correlating” here and there. For example, monitoring vendors often say you can use their product to correlate metrics. Issue 157 in the popular Prometheus monitoring system’s GitHub repository is to add support to correlate multiple metrics in the same graph.

I’ve noticed that when monitoring-related discussions mention correlation, the meaning is usually pretty vague. It often seems to refer to just graphing multiple things on a single chart with the same timescale. Here’s an example of metrics that seem to be correlated:

But visually aligning metrics isn’t the same thing as correlation. Correlation has a specific meaning, and I think we do ourselves injustice when we get in the habit of blurring that meaning; we lose the real benefits of correlation, we tend to think as imprecisely as we speak, and we teach ourselves and …

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common_schema 2.1 released: advanced & improved split(), persistent script tables, more schema analysis, and (ahem) charts!

common_schema 2.1 is released! common_schema is your free & open source companion schema within your MySQL server, providing with a function library, scripting capabilities, powerful routines and ready-to-apply information and recommendations.

New and noteworthy in version 2.1:

  • Better QueryScript's split() functionality
  • Persistent tables for QueryScript: no long held temporary tables
  • Index creation analysis, further range partition analysis
  • grant_access(): allow everyone to use …
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Google Charts for DBA: Tablespaces Allocation

Pythian DBA’s have daily reports for each monitored database and some of the components are using charts to visualize the data. I’m a big fan of charts myself (when applied appropriately) and want to show how you can generate simple charts directly from the database. You’d be very surprised how easy it can be done from *any* database without installing any additional software or configuring something special.

This method is not limited to Oracle by any means — use it with MySQL, SQL Server or any other database as well as without a database — yes, visualize your sar data now!

In this example, we will plot a pie diagram with Oracle tablespaces. This would be very handy when you are starting to analyze the space allocation for a database. Here is the end result of the report for my Grid Control repository test database:



The secret …

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Showing entries 1 to 5