Our new Elastic for Students and Educator program provides online resources and support to help you teach and learn no matter where you are. Hear from Luis Francisco Sánchez Merchante, an educator based in Spain, as he reflects on the challenges he’s faced while teaching during a global pandemic.

Aside from ensuring each service is working properly, one of the most challenging parts of managing a cloud-based infrastructure is cost monitoring. There are countless services to keep track of—including storage, databases, and computation—each with their own complex pricing structure. Monitoring cloud costs is quite different from other organizational costs in that it can be difficult to detect anomalies in real-time and accurately forecast monthly costs.

Searches are integral parts of any application. Performing searches on terabytes and petabytes of data can be challenging when speed, performance, and high availability are core requirements. This blog post will pit Solr vs Elasticsearch, two of the most popular open source search engines whose fortunes over the years have gone in different directions. Both of them are built on top of Apache Lucene, so the features they support are very similar.

In our previous post, we introduced the concept of the Elastic Workplace Search Custom Source API as a means of adding data for which a prebuilt content source integration isn’t available. We used a simple example — a CSV file of contact information — to demonstrate the process along with the use of the associated REST API. In this post, we explore ingesting data from a more complex organizational source: Trello.

We’re excited about today’s release of Grafana 7.1, which extends Grafana’s built-in InfluxDB datasource to run queries in both the Flux language and InfluxQL. This means it’s super easy to connect Grafana to InfluxDB — whether you use InfluxDB 1.8 or 2.0, Flux or InfluxQL. Because this InfluxDB datasource is built into Grafana 7.1, there is no separate plugin to download and install.

With the increasing popularity of Python web frameworks supporting asynchronous I/O like FastAPI, Starlette, and soon in Django 3.1, there has been a growing demand for native async I/O support in the Python Elasticsearch client. Async I/O is exciting because your application can use system resources efficiently compared to a traditional multi-threaded application, which leads to better performance on I/O-heavy workloads, like when serving a web application.