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The Best Approach To Elasticsearch Security

Introduction

Elasticsearch has rapidly—and deservedly—established itself as a popular choice for enterprise application developers. The one negative associated with the highly capable distributed open-source search and log analytics engine is that it has garnered headlines for security hiccups. This reputation for security is arguably undeserved. I think it says more about the fact that organizations too often fail to treat Elasticsearch security with the respect required for any data storage solution. With the proper attention and an accurate understanding of Elasticsearch’s specific needs, the technology can be made sufficiently secure for enterprise needs.

The basic default Elasticsearch configuration lacks enterprise-grade security features. This combination—a simple deployment that’s just as easy to then ignore when it comes to subsequent security hardening—can easily lead to lax access restrictions and data protection. And, it has, as those aforementioned headlines have shown over the past couple of years. But, by implementing enterprise-grade security and adhering to best practices, enterprises can eliminate the errors that put Elasticsearch data in peril.

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Elasticsearch Distributed Consistency Principles Analysis, Part 1

Elasticsearch (ES) is the most common open-source distributed search engine. It's based on Lucene, an information-retrieval library, and provides powerful search and query capabilities. To learn its search principles, you must understand Lucene. To learn the ES architecture, you must know how to implement a distributed system. Consistency is at the core of distributed systems.

This article describes the ES cluster composition, node discovery, master election, error detection, and scaling. In terms of node discovery and master election, ES uses its own implementation instead of external components such as ZooKeeper. We will describe how this mechanism works, and the problems with it. This series covers: