Operations | Monitoring | ITSM | DevOps | Cloud



Search Observability Data In-Place: Store Where You Want, Query When You Want

When we created Cribl Search, we wanted to give systems administrators the ability to query data without having to spend resources on collection and processing first — but we didn’t stop there. With Search, we’re also making it possible to query all the data you’ve already collected, processed, and kept in places like object stores, file systems, analytics tools, S3 buckets, or other data stores.


Cribl Search: The Most Powerful Tool for Querying Data at Its Source

One of the most useful features of Cribl’s flagship solution Stream is its ability to separate the wheat from the chaff in your data’s journey from source to destination — Stream allows you to control what data goes to what system, Cribl Search, takes this to the next level by controlling what data should be collected before it is ever put in motion.


How to build scoped search suggestions and search query corrections

You get one shot to keep shoppers on your ecommerce website with relevant search results. According to Harris Poll, 76% of online shoppers abandon a retail website after an unsuccessful search. Therefore, it’s critical to optimize your search experience so buyers can find what they need fast. That’s the theory behind a modern search experience: Nowadays it’s not enough to simply provide a search bar that returns matching products.


Searching Observability Data Just Became Point & Shoot

The traditional approach for searching observability data is a tried-and-true: Once all the search staging is accomplished, we can perform high-speed, high-performance, deep-dive analysis of the data. But is this the best way or even the only way to search all that observability data? The answer to the first question is maybe, as it depends on what you are trying to accomplish. The answer to the second question must be a resounding no.

Elasticsearch Tutorial | Getting Started Guide for Beginners - Sematext

Elasticsearch is the search engine of choice for some of the very largest companies in the world. The reason Elasticsearch is loved by so many is due to its searching and indexing capabilities. In this Short elasticsearch tutorial for beginners, we will learn what elasticsearch is and what are the advantages of indexing data. We will also do some practical examples where we will deploy our own elasticsearch cluster, manually create an index, use a bash command to import large amounts of JSON documents and run our first search (query) within elasticsearch.

Unlock the full potential of your data with Elastic Search Platform

Data: the volume of it, the variety of it, and the complexity of it is overwhelming. Join Elastic Enterprise Search Product Lead Jonas Lavoie as he interviews VP of Elastic Platform Steve Kearns, GM of Elastic Observability Sajai Krishnan, GM of Elastic Security Santosh Krishnan, and GM of Elastic Enterprise Search Matt Riley about the data challenges facing IT leaders today and how 1 platform with 3 search-powered solutions built on 1 tech stack can unlock the power of structured and unstructured data -- anywhere.

OpenSearchCon: Together after 18 Months

OpenSearch was created by the community for the community to continue to keep an open-source alternative to ElasticSearch and Kibana. The project has been hard at work for the last 1.5 years building, launching and iterating on this important initiative. Some remarkable milestones have been achieved, including over 5,800 stars on GitHub with 19 different community-led projects.


What is OpenSearch?

OpenSearch is an open-source search and analytics suite. Developers build solutions for search, data observability, data ingestion and more using OpenSearch. Another popular use case is log analytics. You take the logs from applications, servers and network elements, feed them into OpenSearch, and use the rich search and visualisation functionality to identify issues.


Elastic Enterprise Search 8.5: Machine learning for intuitive search experiences

The latest release of Elastic Enterprise Search introduces a suite of new features and capabilities for building world-class search experiences for your mission-critical applications, websites, online stores, or anything in-between: With this release, building search experiences for your ecommerce retail site, enhancing your employees’ ability to access relevant HR documentation, or building a custom application to quickly draw analytic insights can draw on the power of using the trained model of


How to personalize search experiences using Elastic

Creating personalized search experiences can be challenging. In this post, we’ll demystify the steps to get started, so you can prioritize search results according to user profiles, offer relevant recommendations, and accelerate workflows. But before we get to that, let’s address why personalized search matters.