We’re excited to announce that Zendesk is now available as a pre-built content source, along with a host of others, as part of the Workplace Search application. With more than 130,000 customers in 30 countries, Zendesk has become one of the de facto customer service platforms in the world. Each day, millions of users interact with support agents via the cloud-based tool regardless of the support channel they choose.
With Elasticsearch machine learning one can build regression and classification models for data analysis and inference. Accurate prediction models are often too complex to understand simply by looking at their definition. Using feature importance, introduced in Elastic Stack 7.6, we can now interpret and validate such models.
Wherever people encounter a search bar — whether on Google, phone apps, or while shopping online — they're conditioned to expect search experiences that deliver fast and relevant results. With this ever-evolving expectation in mind, millions of developers and organizations have chosen Elasticsearch for building powerful content discovery experiences over the years, to the great delight of their audience and user base.
As engineers, you and I have a responsibility to protect both our customers’ and our respective companies’ data. But unlike our office networks that adhere to strict security protocols and a well-defined perimeter, our home networks usually fall short. And now that most of us are at home waiting out the COVID-19 pandemic, it’s time to revisit of logging in and Elasticsearch security during while you work from home.
If you’re using the Elasticsearch query functionality, for mainly front-facing client search, there are 3 important metrics to monitor performance. Your cluster can be putting up with any number of queries at a time. The volume of queries over time will align roughly to the load of requests laying a potential burden. Unexpected peaks and valley in a time series of query load could be signs of a problem or potential optimization opportunities.
The machine that runs your instance of Elasticsearch will indicate vital signs of performance. Eyes on the CPU, memory usage, and disk I/O will ensure optimal Elasticsearch node performance in production.
Elasticsearch provides a powerful set of options for querying documents for various use cases so it’s useful to know which query to apply to a specific case. The following is a hands-on tutorial to help you take advantage of the most important queries that Elasticsearch has to offer. In this guide, you’ll learn 42 popular query examples with detailed explanations, but before we get started, here’s a summary of what the types of queries we’ll tackle.
Until now, standard search solution pricing has been based on models that are difficult to understand, expensive to scale, and/or beneficial to only the search vendor. At Elastic, we’re taking a different approach based on the principles of transparency, fairness, and scalability, and have introduced resource-based pricing for our products running on Elastic Cloud. And we believe that this pricing approach will revolutionize Enterprise Search buying and ownership.