Baron Schwartz

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Published by Baron Schwartz on Jan 4, 2018 3:47:50 PM

2017 Year in Review at VividCortex

It’s easy to observe (pun intended) in the rear-view mirror. Hindsight bias aside, 2017 was a big year for VividCortex and our customers! We shipped lots of features and made tons of progress on the business. Here’s a brief overview of some of our proudest moments from 2017.

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Published by Baron Schwartz on Dec 3, 2017 3:51:06 PM

Monitoring, Analytics, Diagnostics, Observability, and Root Cause Analysis

Monitoring is a hopelessly overloaded term in tech culture. The term now carries decades of inaccurate and imprecise use. The result is that several people can be engaged in an earnest conversation about monitoring and, despite efforts to get each other to see what they mean, remain on totally different wavelengths. I know, because I’ve seen it happen many times. It’s amazing how many times I’ve seen people frustrated with each other because they mean different things when talking about these words.

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Published by Baron Schwartz on Nov 7, 2017 5:09:42 PM

Hierarchical Observability with RED

I've written before about the minimal set of metrics that can serve effectively as application/service vital signs. One such set is the RED acronym, which stands for Request Rate, Request Errors, and Request Duration. (I'll write in the future about what's missing from this acronym, but it'll serve the purpose for now).

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Published by Baron Schwartz on Oct 13, 2017 10:16:40 AM

Monitor Your Citus Cluster With VividCortex

VividCortex now has support for monitoring Citus, a scale-out solution for massively sharded data storage and processing using standard open-source PostgreSQL. Citus (previously known as CitusDB) layers an additional set of capabilities on top of PostgreSQL. The result is a powerful distributed database that shards your data and lets you ingest a firehose of data, while running complex real-time analytics queries in parallel across nodes for blazing fast performance.

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Published by Baron Schwartz on Oct 6, 2017 12:20:56 PM

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.

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Published by Baron Schwartz on Oct 5, 2017 4:02:17 PM

Monitoring and Observability with USE and RED

Modern systems can emit thousands or millions of metrics, and modern monitoring tools can collect them all. Faced with such an abundance of data, it can be very difficult to know where to start looking when you’re trying to diagnose a problem. And when you’re not in diagnosis mode, but you just want to know whether there’s a problem at all, you might have the same difficulty. What are the truly key KPIs coming from your systems?


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Published by Baron Schwartz on Sep 26, 2017 11:01:16 PM

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.

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Published by Baron Schwartz on Sep 21, 2017 4:31:49 PM

Find Queries That Need Indexes With VividCortex

Queries can be slow or resource-heavy for many reasons, but one of the most common is that the table doesn't have a good index for the query. This is true for MySQL, PostgreSQL, and especially for MongoDB. Adding an index where it's missing is often a night-and-day improvement, as shown in this screenshot of a query's performance. The index was added midway through the time range, and the query got dramatically faster:

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