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November 2023

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chaossearch

Buyer Beware! Three Challenges with Elasticsearch and OpenSearch

Nov 30, 2023 By David Bunting In ChaosSearch

Elasticsearch and OpenSearch are powerful enterprise search and analytics engines that have become popular in the world of data management and telemetry analysis. Their ability to swiftly search, analyze, and visualize data has made them indispensable for businesses and organizations. However, in this blog, we will explore a few key challenges faced by companies using Elasticsearch and OpenSearch, shedding light on important considerations when selecting the right tool for your needs.

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A Simplified Guide to Kubernetes Monitoring

Nov 26, 2023 By George Hamilton In ChaosSearch
The open-source Kubernetes platform has become the de facto standard for deploying, managing, and scaling containerized services and workloads. In fact, 83% of DevOps teams are using Kubernetes to deploy containerized applications in production, taking advantage of its workload orchestration and automation capabilities to optimize the software development process and reduce web server provisioning costs.
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5 Elasticsearch Disadvantages You Should Know

Nov 16, 2023 By David Bunting In ChaosSearch
Since its initial release in 2010, Elasticsearch has grown into the most popular enterprise search engine with use cases that range from web crawling and website search to application performance monitoring and security log analytics. But despite its widespread adoption and success, Elasticsearch does have some notable disadvantages that you should consider - especially if you’re envisioning a high-scale deployment with a large amount of daily ingestion.
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6 Reasons Your Data Lake Isn't Working Out

Nov 9, 2023 By David Bunting In ChaosSearch
Since the data lake concept emerged more than a decade ago, data lakes have been pitched as the solution to many of the woes surrounding traditional data management solutions, like databases and data warehouses. Data lakes, we have been told, are more scalable, better able to accommodate widely varying types of data, cheaper to build and so on. Much of that is true, at least theoretically.
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