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Introduction Elasticsearch is a powerful search engine that's commonly used for log and data analytics. Setting a multi-node cluster enhances the availability, fault tolerance, and performance of Elasticsearch, making it a preferred choice for production environments. In this blog post, I'll walk you through the steps to create a...
Introduction In today's competitive market, delivering a seamless and responsive user experience is crucial for retaining customers and driving business growth. Elastic APM (Application Performance Monitoring) has emerged as a vital tool for achieving these objectives. By providing deep insights into application performance and...
Elasticsearch offers highly useful plugin mechanism as a standard way for extending its core functionality such as custom analyzer, native scripts and more. While some plugins may contain static content which is served through its HTTP server, some others offer a graphical front-end for selected parts of the Elasticsearch REST API such...
One of the most challenging tasks in any microservices ecosystem is the centralized log management, and there are many open source and paid solutions available in the market. In our ecosystem, we are using ELK stack as it provides scalability and the multitenant-capable full-text search engine that easily integrates with Logstash and...
In our previous blog, we have covered the basics of fluentd, the lifecycle of fluentd events and the primary directives involved. In this blog, we'll configure fluentd to dump tomcat logs to Elasticsearch. We'll also talk about filter directive/plugin and how to configure it to add hostname field in the event stream. Fluentd...
As with any software that stores data it is important o take back up of that data. Elastic search is a data store with exceptionally good capabilities of searching. In elastic search data is stored in indexes. So Either you can take back up of whole cluster or you can take back up of indexes you want. Elastic search provides a great...
Our cloud DevOps engineers have been using Elasticsearch on production environment for an e-commerce website for quite a while. The website has one admin server to manage activities such as adding new production, managing discounts on various items, fetching reports etc. We came across a requirement where downloading reports from admin...
Our DevOps team was using Found for one of our projects in the production environment. We have been facing a problem with found where it’s memory pressure frequently goes up and does not drop down so easily and until the time it remains up the Found was not able to serve the requests. Then, we decided to move to self-hosted...
In our project we have two use cases where, we need a custom analyzer that answers both the below use cases :- Let's take a string "king of pop michael jackson" thats indexed somewhere in my elasticsearch document. 1. First Use Case :- Searching Substring : Sometimes the end user doesn't want to write the complete word for...
In adaptTo() 2014, I delivered a talk on "Integrating ElasticSearch with AEM". It started with a brief introduction about ElasticSearch, its working and flexibilty when it comes to huge amount of data. Here is a brief review of topics covered after that: How data is analyzed and indexed on the server Integration approaches with AEM...