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Analytics

Structuring Elasticsearch data with grok on ingest for faster analytics

As well as being a search engine, Elasticsearch is also a powerful analytics engine. However, in order to take full advantage of the near real-time analytics capabilities of Elasticsearch, it is often useful to add structure to your data as it is ingested into Elasticsearch. The reasons for this are explained very well in our schema on write vs. schema on read blog post, and for the remainder of this blog series, when I talk about structuring data, I am referring to schema on write.

Community Highlight: How InfluxDB Enables IoT Monitoring of Gas Station Tanks

I recently spoke with Alex Skrivseth, the Operations Manager at The Shed App, and discovered how he’s using InfluxDB to monitor the current levels of gas and diesel at various gas stations. Simply by extracting IoT sensor data, he has been able to provide valuable previously inaccessible data to fuel truck drivers.

Building a Python web application with Elastic App Search

This post is a brief summary of a presentation I gave recently where I deploy Elastic App Search, show off the ease of setup, data indexing, and relevance tuning, and take look at a few of the many refined APIs. It’s also written up in a codelab with step-by-step instructions for building a movies search engine app using Python Flask. The app will work on desktop or mobile and is a fast, simple, and reliable way to query the information.

Powering Khoros Community Platform using Elasticsearch

At Khoros, we provide a platform for brands to build a community around their customers. Behind the scenes, this community platform is powered by Elasticsearch for operations such as free text search, fetching data for our custom query language, and building customizations. Some of the biggest communities have millions of users and greater than 100 million documents. Come and take a look into how we index these millions of documents in a reliable and efficient way to power our community platform!

Your Data Already Has the Insights. Are You Extracting Them?

The sheer scale of connected devices across physical, virtual, and distributed networks has come to scale that it has become practically impossible for most network administrators to manually keep an eye on each node. Along with the scale, the connectivity between devices within each network has also become denser.

Optimizing costs in Elastic Cloud: Replica shard management

This is part of our series on cost management and optimization in Elasticsearch Service. If you’re new to the cloud, be sure to think about these topics as you build out your deployment. If you are yet to start, you can test out the content here by signing up to a 14-day free trial of Elasticsearch Service on Elastic Cloud.

How Playtech Fixed Metrics Over-Collection with Observability

According to Forbes, 2.5 quintillion bytes of data are created every day. Data volumes have grown exponentially in recent years due to the growth of the Internet of Things (IoT) and sensors. The majority of data collected has been collected in the last two years alone. For example, the U.S. generates over 2.5 million gigabytes of Internet data every minute, and over half of the world’s online traffic comes from mobile devices.

Graph Analytics Using Splunk and the Machine Learning Toolkit

Almost all data in Splunk can be turned into graphs, and that's possibly something you may not have considered before. In your network traffic data, a source IP connects to a destination IP with attributes like bytes in/out, packets, ports, and other properties. Users log into an interconnected stack of systems, services, devices and applications which are connected with each other. Transactions run from A to B to C and may describe a process that helps you analye user journeys and business processes in general.