Does your Elastic Enterprise Search Cloud deployment follow a predictable usage pattern? You can automatically scale up and down your deployment on a schedule to achieve optimal performance and reduce operating costs. In this article we show you how to use the Elastic Cloud API to change how many Enterprise Search nodes you’re running. We call these APIs from a cron job to achieve hands-free, time-triggered autoscaling.

With Elastic 7.12, Discover now uses the fields API by default. Reading from _source is still supported through a switch in the Advanced Settings. This change stems from updates made to Elasticsearch in 7.11 with the extension of the Search API to include the new fields parameter. When using the new search parameter, both a document’s raw source and the index mappings to load and return values are used.

Elastic Cloud is available for US government users and partners who want to harness the power of enterprise search, observability, and security to make mission-critical decisions. Elastic Cloud is FedRAMP authorized at Moderate Impact level so federal organizations and other customers in highly regulated environments can quickly and easily search their applications, data, and infrastructure for information, analyze data to observe insights, and protect their technology investment.

Many of you might have seen our blogs about different techniques for identifying anomalies. Perhaps you even have a handful of analytics running in Splunk to identify anomalies in your data using statistical models, using probability density functions or even using clustering.

Data lakes have challenges. And until you solve those problems, efficient, cost-effective data analytics will remain out of reach. That’s why ChaosSearch is rethinking the way businesses manage and analyze their data. As Mike Leone, Senior Analyst for Data Platforms, Analytics and AI at ESG Global, and Thomas Hazel, ChaosSearch’s founder and CTO, explained in a recent webinar, ChaosSearch offers a data analytics optimization solution that makes data faster and cheaper to store and analyze.

Since the data lake concept emerged more than a decade ago, data lakes have been pitched as the solution to many of the woes surrounding traditional data management solutions, like databases and data warehouses. Data lakes, we have been told, are more scalable, better able to accommodate widely varying types of data, cheaper to build and so on. Much of that is true, at least theoretically.

Are you looking to get started with InfluxDB on Google Cloud? We’ve pulled together our top resources to help you get the most out of your time series data whether that’s coming from your Google Cloud infrastructure or your own application. Read how customers like Wayfair and Vera C. Rubin Observatory use InfluxDB on Google Cloud to solve their time series data collection and processing challenges to power their multifaceted, complex real-world use cases.

Power BI (Business Intelligence) is a business analytics platform/service provided by Microsoft. This service aims to provide interactive visualizations and business intelligence, enabling the end-user to create individualized reports and dashboards independently. Especially for retail businesses, Power BI helps them meet the dynamic customer demands in advance with actionable insights. Microsoft Power BI service is based on cloud service, which also offers a desktop-based interface.

Consider for a moment that you are building a webpage that displays data stored in Elasticsearch. You have so much information in your index that your API Gateway cannot handle it all at once. What you’ll need to do is paginate your results so that the client can have a predictable amount of data returned each time. Before paginating your results with your client, you will need to know how to paginate data in your backend storage.