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Avoid common mistakes when assigning Elasticsearch Mappings in your cluster

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.

How to reindex your Elasticsearch data

The Elasticsearch reindex API copies data from one index to another. You can use reindex to change the index mapping, copy data to another cluster, or copy only a subset of data to another index. For example, suppose you want to reindex all the data in index1 into index2. In that case, you run the following example in Kibana dev tools: In this article, we dive into some common issues solved by reindexing as well as troubleshooting issues with reindexing itself.

Top metrics for Elasticsearch monitoring with Prometheus

Starting the journey for Elasticsearch monitoring is crucial to get the right visibility and transparency over its behavior. Elasticsearch is the most used search and analytics engine. It provides both scalability and redundancy to provide a high-availability search. As of 2023, more than sixty thousand companies of all sizes and backgrounds are using it as their search solution to track a diverse range of data, like analytics, logging, or business information.

Viable Ways for Online Information Search That Challenge Google's Dominance

Google it! This has become the go-to expression for almost everyone who suggests looking for something online. As a result, Google has become synonymous with an online search. However, things may change in the next few years with the rise of alternatives to the search giant.

How to add support for more languages in your Elastic Enterprise Search engines

Engines in Elastic App Search enable you to index documents and provide out-of-the-box, tunable search capabilities. By default, engines support a predefined list of languages. If your language is not on that list, this blog explains how you can add support for additional languages. We’ll do this by creating an App Search engine that has analyzers set up for that language.

The Latest Version of OpenSearch Is Now Live On Logit.io

Logit.io is pleased to introduce the latest version of OpenSearch onto the platform, with an OpenTelemetry-compliant data schema that unlocks a host of future analytics and observability capabilities. Also included in this release are improvements in threat detection for security analytics workloads, visualization tools, and machine learning (ML) models.

Supercharging Elasticsearch with the Power of Telemetry Pipelines

Elasticsearch has made a name for itself as a powerful, scalable, and easy-to-use search and analytics engine, enabling organizations to derive valuable insights from their data in real-time. However, to truly unlock the potential of Elasticsearch, it is essential that the right data in the right format is provisioned to Elasticsearch. This is where integrating a telemetry pipeline can add value to Elasticsearch.

Comparing OpenSearch Managed Services

In March of 2022, Elastic decided to close source the most popular log management and analytics solution in the world: the ELK Stack. Millions chose ELK as their logging platform and made it the heart of their troubleshooting operations because it was open source. And suddenly, it wasn’t – leaving many looking for other options. Shortly after, AWS launched OpenSearch and OpenSearch Dashboards as open source alternatives to Elasticsearch and Kibana, respectively.

How to Find and Fix Elasticsearch Unassigned Shards

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.