Elasticsearch is a search and analytics engine that allows for complex searches on large datasets of different types and formats. Elasticsearch mappings are the blueprints that define how data is indexed and searched to support these data-related features. Understanding how Elasticsearch mappings work is essential to an effective Elasticsearch deployment. In this article, we’ll explore the key concepts of Elasticsearch mappings and common Elasticsearch mapping pitfalls to avoid.

Ubuntu is a Linux distribution based on Debian Linux that’s mostly composed of open-source and free software. Released in three options – servers, desktop computers and Internet of Things devices. Ubuntu is highly popular, reliable and updated every 6 months, with a long-term support version released every two years. Multiple Ubuntu versions allow users to choose whether to stick with the long-term support version or the recently updated one.

Webmasters always have their hands full with everything from user experience, search engine optimization and last but not least, SSL certificates. While some may not prioritize SSL certificates, they are still critical to the correct operation of your websites. Because Secure Layer Certificates are so important, monitoring them is a must! To help you get started, we’ve compiled a list of the top 10 best tools for monitoring SSL certificates for validity, expiry, and change.

As an Elasticsearch administrator, you will inevitably have to delete an index at some point. There could be several reasons why this might be necessary: This article provides an overview of available methods to back up and restore an Elasticsearch index in the event of deletion.

When a data index is created in Elasticsearch, the data is divided into shards for horizontal scaling across multiple nodes. These shards are small pieces of data that make up the index and play a significant role in the performance and stability of Elasticsearch deployments. A shard can be classified as either a primary shard or a replica shard. A replica is a copy of the primary shard, and whenever Elasticsearch indexes data, it is first indexed to one of the primary shards.

Whenever we start a search consulting project from scratch, the obvious question is: which search engine to use? We’ve talked about Elasticsearch vs Solr before, but here we’ll compare Elasticsearch with its fork, OpenSearch. Chances are, if you need to decide between the two, you’ll be looking at a few dimensions.

Businesses that have mission-critical applications deployed on servers often have operations teams dedicated to monitoring, maintaining, and ensuring the health and performance of these servers. Having a server monitoring system in place is critical, as well as monitoring the right parameters and following best practices. In this article, I’ll look at the key server monitoring best practices you should incorporate into your operations team’s processes to eliminate downtime.

Elasticsearch (ES) is a powerful tool offering multiple search, content, and analytics capabilities. You can extend its capacity and relatively quickly horizontally scale the cluster by adding more nodes. When data is indexed in some Elasticsearch index, the index is not typically placed in one node but is spread across different nodes such that each node contains a “shard” of the index data. The shard (called primary shard) is replicated across the cluster into several replicas.

Disk-related issues with Elasticsearch can present themselves through various symptoms. It is important to understand their root causes and know how to deal with them when they arise. As an Elasticsearch cluster administrator, you are likely to encounter some of the following cluster symptoms.

Any software application or a system can have bugs and issues in testing or production environments. Therefore, logging is essential to help troubleshoot issues easily and introduce fixes on time. However, logging is useful only if it provides the required information from the log messages without adversely impacting the system’s performance. Traditionally, implementing logging that satisfies these criteria in Java applications was a tedious process.