Tag: elastic stack

Note: This post was originally written for the Scalyr blog. You can check out the original here.

The amount of event data to collect has seen a dramatic increase in the last few years. It continues to grow as more companies move to microservices, containers, and the modern infrastructure stack. For many, Elasticsearch has been the solution to help.

With more data comes some common scaling problems, so you may consider solutions that are Elasticsearch alternatives.

Choosing the wrong alternative can be risky. So in this post, you’re going to learn about five Elasticsearch alternatives you should consider. You’ll learn about some of their benefits and drawbacks, and also how they’re priced.

Note: This post was originally written for the Scalyr blog. You can check out the original here.

Some things aren’t always what they seem.

You’re tasked with engineering a solution that your organization needs. You implement it with a tool that seems relatively easy to set up. But over time, you realize that there’s no Easy button.

Elasticsearch is an example of one of those things. It’s a great product for collecting event data fairly quickly and easily. You start with one data node in one cluster and go from there. And because it’s free and open-source (for now), it’s even better. But as your Elasticsearch cluster grows and collects more data, you start to have some scaling issues. In this post, I’m going to provide some information on scaling an Elasticsearch implementation, as well as some general recommendations for proactive ways to scale Elasticsearch.