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In a previous article, we explained the importance of monitoring the performance of your servers. Keeping tabs on metrics such as CPU, memory, disk usage, uptime, network traffic, and swap usage will help you gauge the general health of your environment as well as provide the context you need to troubleshoot and solve production issues.

In the past, command line tools, such as top, htop, or nstat, might have been enough, but in today’s modern IT environments, a more centralized approach for monitoring must be implemented.

Source de l’article sur DZONE

Elasticsearch (ES) is the most common open-source distributed search engine. It’s based on Lucene, an information-retrieval library, and provides powerful search and query capabilities. To learn its search principles, you must understand Lucene. To learn the ES architecture, you must know how to implement a distributed system. Consistency is at the core of distributed systems.

This article describes the ES cluster composition, node discovery, master election, error detection, and scaling. In terms of node discovery and master election, ES uses its own implementation instead of external components such as ZooKeeper. We will describe how this mechanism works, and the problems with it. This series covers:

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"Apps without search is like Google homepage without the search bar."

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It’s hard to design an app without a good search. These days, it’s also hard to find a database without a built-in search. MySQL to NoSQL, Sybase to Couchbase, every database has text search support — built-in like Couchbase or via integration to Elastic — as is the case in Cassandra. Unlike SQL, text search functionality isn’t standardized. Every application needs best of the breed search, but not every database provides the same text search functionality. It’s important to understand the available feature, performance of each text search implementation and choose what fits your application need. After motivating text search, you’ll learn about the text search features you’d need for an effective, compare and contrast those features in MongoDB and Couchbase with examples.

Source de l’article sur DZONE