Database Management Blog

Our thoughts about database management plus the latest information about the ObjectRocket platform.

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Ever since Elastic{on} 17, we've been excited about all of the upcoming features in the Elastic Stack, especially the new Filebeat modules concept. Usually, when you want to start grabbing data with Filebeat, you need to configure Filebeat, create an Elasticsearch mapping template, create and test an ingest pipeline or Logstash instance, and then create the Kibana visualizations for that dataset. The Beats team has now made that setup process a whole lot easier with the modules concept.

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There's probably been a time when you said to yourself I wish Elasticsearch did _____ by itself. Luckily for you, Curator fills in a lot of those blanks. Curator has the ability to remove or close old indexes, create and modify aliases, control your snapshots, and many other handy features. We'll be highlighting a few key uses of Curator here, but feel free to read through the official documentation if you're looking for additional guidance.

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Unlocking the power of open source, enterprise-grade technology for businesses of all sizes looking to experience significant cost savings offered by a fully managed database-as-a-service solution.

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One of the coolest new features in Elasticsearch 5 is the ingest node, which adds some Logstash-style processing to the Elasticsearch cluster, so data can be transformed before being indexed without needing another service and/or infrastructure to do it. A while back, we posted a quick blog on how to parse csv files with Logstash, so I'd like to provide the ingest pipeline version of that for comparison's sake.

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Anybody who looks at the ObjectRocket for Elasticsearch page should (hopefully) notice that we mention dedicated containers and our high-performance hardware environment a number of times. Last week we posted a performance comparison between ourselves and a couple of the other Elasticsearch services to give you some insight into the results of our design. Now that you've seen the results, I thought it was about time that we walked through the architecture, where we designed for performance, and the other considerations we had to keep in mind.

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As data platforms continue to expand and transform there's one aspect that never seems to change; everyone still wants a backup copy of their data! The evolution of technology still demands a need to have access to backups in order to restore to a local development environment, a copy for safe keeping or compliance, and various other use cases. This walkthrough will show you how to leverage the S3 repository plugin with your ObjectRocket for Elasticsearch instance.

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Best practice dictates that every database user should only be assigned a minimum set of privileges that on the one hand allows the user to fulfill their mission, and on the other hand minimises the impact of a security breach. For example: a database user used for reporting; it is not nessesary and doesn’t make sense to provide write access since read-only access is adequate.

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Have you every spent time dreaming of a fully automated Elasticsearch environment? If so, stay tuned as this post will walk you through some of ObjectRocket's basic API features for our Elasticsearch product. Using the ObjectRocet API will allow you to create instances, users, acls, and more on demand.

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