Qbox to join forces with Instaclustr. Read about it on our blog post here.

WordPress is a very popular CMS that is used all over the internet for a variety of use cases. WordPress traditionally uses MySQL for the database and for its search functionality.

A good alternative is to use Elasticsearch to extend WordPress’s search functionality.

In this article, we cover how to install ElasticPress, a plugin that can be used to exploit Elasticsearch’s powerful search capabilities with WordPress.

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So you have moved all your applications to Docker and have begun enjoying all the fruits of lightweight and fast-to-deploy containers.

That’s great, but once you have multiple containers spread across multiple nodes, you’ll need to find a way to track their health, storage, CPU, and memory usage, network load, etc.

To track these metrics, you need an efficient monitoring solution and some backend store to keep your container data for subsequent analysis and processing. Managing thousands of Docker containers in production made our team here at Qbox quickly realize that Docker container monitoring is a valuable addition to our cluster management process.

In a previous article, we discussed how to use Metricbeat to ship metrics from Kubernetes. Now, it’s time to share our experience of using Metricbeat to monitor bare Docker containers and shipping container data to Elasticsearch and Kibana. This knowledge may be useful for developers and administrators who manage Docker containers without orchestration. Let’s get started!

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Apache Kafka is a very popular message broker, comparable in popularity to Logstash.

More and more companies build streaming pipelines to react on, and publish events.
Kafka gains accelerated adoption for event storage, distribution, and Elasticsearch for projection. My friend Hannes and I call it a perfect match, so we  gathered during a quiet christmas holiday to implement a connector between the two.

All code is available on Github and runs on Docker Compose.

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