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.
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.
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.
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.
Isn’t all logging pretty much the same? Logs appear by default, like magic, without any further intervention by teams other than simply starting a system… right? While logging may seem like simple magic, there’s a lot to consider. Logs don’t just automatically appear for all levels of your architecture, and any logs that do automatically appear probably don’t have all of the details that you need to successfully understand what a system is doing.
When was the last time you had the chance to listen to some of the most beautiful concerts that nature can play for you? From simple chirps and tweets to complex bird songs composed into a sophisticated soundscape, you may wish you could decrypt and understand their daily conversation. “Hey, good morning, how are you today?”, you might hear in the early hours, sometimes so loudly that you are awakened from the chirping.
Today, InfluxDB Cloud is generally available on Microsoft Azure. Now you have the freedom to run the leading time series database on whichever you prefer: Microsoft Azure, Google Cloud or AWS.
In May we released the Splunk Machine Learning Toolkit (MLTK) version 5.2. We’ve loved telling you about some of the great new features, including the most recent blog on DensityFunction. However, we know that before you can start experimenting with model-building algorithms such as DensityFunction, your data needs to be prepared for machine learning. Machine learning operates best when you provide clean data as the foundation for building your models.
