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Today, I'm going to walk you through setting up a local instance of Kibana to connect to a remote Elasticsearch cluster. ObjectRocket for Elasticsearch instances include a free, hosted Kibana install, but there are some cases where running Kibana on your local machine provides additional flexibility. Also, if you happen to be running in an environment or on a service that does not provide hosted Kibana, this walkthrough will help you easily run Kibana local to your machine.
Organizations seeking to save money might look at managing their databases in house as one place to tighten the belt, but a recent study on total cost of ownership found that a fully-managed database-as-a-service is the consistently better value.
This post outlines some discoveries related to Sitecore knowledge base 939840, an article that explains how to avoid timeouts related to saving contacts with a large number of interactions to the Sitecore Analytics database.
Today, I'm excited to announce that we're starting to roll out our RocketScale™ autoscaling technology to all ObjectRocket for Elasticsearch customers. We will be rolling out in phases, so some of our users may see the feature pop up before others. Once we're complete, data nodes will be automatically added to your Elasticsearch clusters when they're short on capacity.
By: Steve Croce Antonios Giannopoulos, Grant Killian
Posted on:
MongoDB is a technology that’s easy to overlook in a Sitecore implementation. Many people come to Sitecore already knowing SQL Server, and C# applications running on IIS are as familiar as well broken-in blue jeans. As Sitecore systems evolve, however, they move into interesting areas that are somewhat off the beaten path for the typical ASP.Net developer. One gets into areas like Solr, Redis, or – the focus of this write-up – MongoDB.
Other than "You Know, for Search", the uses of Elasticsearch continue to grow and change over time. We at ObjectRocket have been offering hosted Elasticsearch on the ObjectRocket platform for a while now and have been able to see some clear trends among our customers and how they're using the product. Below are the top 5 uses cases that we see on the platform:
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.
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.