The Elastic Cloud console gives you a single place to create and manage your deployments, view billing information, and stay informed about new releases. It provides an easy and intuitive user interface (UI) for common management and administrative tasks. While a management UI is great, many organizations also want an API to automate common tasks and workflows, especially for managing their deployments.

When ingesting data into Elasticsearch, it is often beneficial to enrich documents with additional information that can later be used for searching or viewing the data. Enrichment is the process of merging data from an authoritative source into documents as they are ingested into Elasticsearch. For example, enrichment can be done with the GeoIP Processor which processes documents that contain IP addresses and adds information about the geographical location associated with each IP address.

For many companies, Elastic included, wikis developed with Confluence are a critical source of content, procedures, policies, and plenty of other important info, spanning teams across the entire organization. But sometimes finding a particular nugget of information can be tricky, especially when you’re not exactly sure where that information was located. Was it in the wiki? In a Word doc? In Salesforce? A GitHub issue? Somewhere else?

As Elasticsearch users are pushing the limits of how much data they can store on an Elasticsearch node, they sometimes run out of heap memory before running out of disk space. This is a frustrating problem for these users, as fitting as much data per node as possible is often important to reduce costs. But why does Elasticsearch need heap memory to store data? Why doesn't it only need disk space?

Let’s be honest. No one wakes up in the morning thinking of reasons to contact customer support. It’s tedious, onerous, and can eat into your evening Netflix time. Thankfully, most brands realize that customer experiences drive brand loyalty and repeat purchases.