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Published by Baron Schwartz on Jul 30, 2018 1:47:27 PM

What is Cardinality in Monitoring?

I wrote a couple of “definitions and nuances” posts about terminology in databases recently (cardinality, selectivity), and today I want to write one about cardinality in monitoring, as opposed to cardinality in databases. If you’ve seen discussions of “high-cardinality dimensions” or “observability requires support for high-cardinality fields” this is what we’re talking about today. So what does it mean?

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Published by Samantha Toet on Jun 28, 2018 1:24:31 PM

How NOT to Monitor Your Database

Do you have experience putting out backend database fires? What were some things you wished you had done differently? Proactive database monitoring is more cost efficient, manageable, and sanity-saving than reactive monitoring. We reviewed some of the most common mistakes - too many log messages, metric “melting pots,” retroactive changes, incomplete visibility, undefined KPIs - and put together an action plan on how to prevent them. From our experience, we've listed out the top 5 biggest (and preventable!) database monitoring pitfalls.

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Published by Samantha Toet on Jun 1, 2018 4:26:17 PM

Monitor Critical Databases Confidently with the Sensitive Data Vault

Building extremely deep monitoring as a SaaS product has a drawback: we capture too much data for some customers’ compliance requirements. As a result, some companies have been unable to deploy us, or have had to redact data before sending it to our cloud platform. To address this, we built the Sensitive Data Vault, a highly secure, completely on-premises storage module for the most critically private data that must never leave the customer’s firewall.

 

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Published by Samantha Toet on May 11, 2018 5:17:30 PM

How SendGrid Ships Better Code Faster with VividCortex

VividCortex CEO Baron Schwartz and SendGrid DBA Silvia Botros teamed up to discuss how performance monitoring leads to better, faster code deployment. This 30-minute webinar covers: 

  • How developers can deploy code faster and more safely.
  • A close-up view of a health- and monitoring-focused work environment.
  • How database monitoring fits into a culture of DevOps and lean, agile development. 

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Published by Andrew Morgan on Mar 30, 2018 11:15:00 AM

What's New: Product Updates  

We’ve added several major features since our last product update. These capabilities help you understand your database’s performance and health, get expert insights about topics like configuration and security, explore individual sample query executions fluidly, and store your most sensitive data on-premises instead of in our cloud platform. If you have any questions, contact us!

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Published by Preetam Jinka on Mar 20, 2018 9:05:45 AM

Holt-Winters Forecasting Simplified

Holt-Winters forecasting is a way to model and predict the behavior of a sequence of values over time—a time series. Holt-Winters is one of the most popular forecasting techniques for time series. It’s decades old, but it’s still ubiquitous in many applications, including monitoring, where it’s used for purposes such as anomaly detection and capacity planning.

Unfortunately, Holt-Winters forecasting is confusing, so it’s often poorly understood. We want to fix that, so we wrote this post: a visual introduction to Holt-Winters.  

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Published by Aisha Robinson on Mar 15, 2018 8:30:00 AM

Strata Conference 2018: What You Missed

We just got back from the west coast where our own CEO Baron Schwartz presented at Strata Data Conference 2018.

Baron held a session, Why Nobody Cares About Your Anomaly Detection at the event and in case you missed it we wanted to make sure we passed it along! In the session, Baron shares why he now sees anomaly detection as a very limited tool, to be used for specific purposes and with careful attention to design and context (including culture) and only to be considered as a part of an overall solution—not a solution itself.  View the entire presentation below.

 

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Published by Preetam Jinka on Mar 12, 2018 2:27:00 PM

Numeric Optimization in Golang with Nelder-Mead and Gonum

Numeric optimization is a set of techniques for fitting a function to a dataset by iteratively refining estimates. Numeric optimization is one way to do things like curve-fitting and parametric estimations. We use it in some time series forecasting techniques we implemented recently, where the forecasting models use parameters such as seasonality and trend that we can’t determine in advance. We use numeric optimization to select the optimal parameters based on the specific dataset we’re trying to forecast.

The gonum package https://github.com/gonum/gonum is a great set of numeric libraries for Go. It has a numerical optimization package. In this post I’ll show how to fit a line to 2D points with the optimize package. This is the simplest example of how to do numerical optimization with the package. It’s a good illustration of how to set up an optimization, and helps show how to get started so you can do more complicated things if you want.

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Published by Aisha Robinson on Mar 7, 2018 10:33:27 AM

Did You Miss Us at DevOps Days Charlotte?

DevOps Days Charlotte 2018 was a great event and we can't wait to return next year! Over 200 development, infrastructure, operations, information security, management and leadership professionals gathered to discuss the culture, processes and tools to enable better organizations and innovative products.

VividCortex engineer Preetam Jinka held a session, DevOps Comes To The Database at the event and in case you missed it we wanted to make sure we passed it along! In the session, Preetam discussed the importance of your database and how while databases are stateful they are changing and becoming more like applications. View the entire presentation below.

 

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