Recent Posts by John Vanderzyden

John led content initiatives here at Qbox and wrote a blog series about getting started with Elasticsearch.

Qbox is proud to sponsor booth #426 at AWS re:Invent 2015 in Las Vegas, Nevada. We are here with the largest annual gathering of the Amazon Web Services community.

We'll be sharing the news about Qbox and helping folks learn about the many benefits of Elasticsearch in the cloud. We're getting the word out to Elasticsearch and big data professionals, helping them understand how they can realize gains in productivity, increases in application performance, enhance their security, and minimize their infrastructure costs.

Come visit us and get a free Elasticsearch cluster analysis.

<p>Elasticsearch recently published two new releases, and both are now available for Qbox users to upgrade their clusters. </p><p>Version 1.6.2 contains a number of bug fixes, and 1.7.1 is the latest stable release. <em>We advise all users to upgrade</em>. </p><p>Qbox customers should <a href="" data-mce-href="" data-mce-style="font-size: inherit;" rel="font-size: inherit;">contact support</a> to request an upgrade to either release as soon as you can accommodate it in your environment. Read this article for a short summary of the release notes and links to more information. </p> Keep reading

Ask most folks to describe Elasticsearch, and you'll get a variety of answers. Many senior full-stack developers will struggle with the answer. They might know how to use it, but it's hard to get a clear, concise, and accurate answer. This can create no small amount of frustration in those who need to know: What is it? What does it do? How might I benefit?

We've got answers for you. Right here in this article. Comprehensive, yet easy for almost anyone to read. Enjoy. And ..... you're welcome!

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Elasticsearch continues to evolve. The big news recently is that release 2.0 is around the corner. Pipeline aggregations is perhaps the most interesting feature set that will be available in this upcoming release. This will be an extension of the existing ES aggregations framework, and it will provide for a number of computation types that users can perform on top of the standard aggregations results.

In this article, we give a brief overview of this ES feature extension, direct you to tutorials on aggregations, and provide links to more information.

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Here's a twist on the old adage: A ounce of prevention is worth a kiloton of user satisfaction.

It's no secret that we're big fans of Elasticsearch. But we've seen more than a few customers crash their clusters—in a variety of ways. Most of those failures are quite preventable. It's often a matter of a simple misunderstanding, and the remedy is usually fairly easy to apply.

As we did in our recent article on field data, we invite you to think through a number of other potential problems. With little effort, you can apply several key practices that will improve stability and improve performance for your ES cluster.

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In Elasticsearch, field data is generated at query time by reading the index, inverting that data structure, and then storing the results in memory. This operation can be quite slow, and it often consumes far too much valuable heap space. Before you know it, your cluster is grinding slowly toward a state of complete lethargy -- but it need not be so! In this article, we present a summary of a recent Elastic article on the challenges and corresponding remedies for overgrown field data.

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This is a continuation of our extensive blog series on Elasticsearch scripting, which includes tutorials and example scripts for sorting, filtering, and scoring. In our previous article, we went through a basic tutorial on performing aggregations in Elasticsearch using scripts.

In this tutorial we move on to more advanced operations: computing term frequencies, reshaping the results of extended_stats aggregations, and implementing scripted_metric aggregations.

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If you've spent time trying to ramp up on Elasticsearch and configure a local cluster, you may be wondering if there's a better way. Perhaps you're in need of solid advice, and maybe you'd like to find an easier path. In this article, we summarize a number of best practices in managing an ES cluster. Also, we provide many links to specific information that you can find in our extensive blog and knowledge base.

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We're always glad to see unsolicited kudos from independent sources. Alex Zhitnitsky over at Takipi has given Qbox a priority placement in his review of ELK-stack cloud services. He shares his own experiences in resolutely managing his home-grown ELK stack and then outlines the advantages of hosted Elasticsearch.

Some Qbox customers have much in common with his story, although many have special business and technical requirements. Now that Alex is enjoying the benefits of hosted Elasticsearch, he offers helpful advice from the perspective of a developer who has run the entire gamut. We respond to his review in this short article.

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Elasticsearch recently published two new releases, and both are now available for Qbox users to upgrade their clusters. Version 1.6.1 contains bug fixes and small enhancements. Along with some security fixes, release 1.7.0 adds two new features to Elasticsearch: delayed shard allocation and prioritization of index recovery. We recommend that you upgrade as soon as you can accommodate it in your environment.

Qbox customers can contact support to request an upgrade to either release. Read this article for a distillation of the release notes and the benefits of these upgrades.

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