Elastic Cloud Enterprise 2.0 Comes With Deployment Control and Optimization Features

elasticsearchElasticsearch and Elastic Stack provider Elastic has released its Elastic Cloud Enterprise version 2.0. Elastic Cloud Enterprise was designed to provide a centralized and easy way to provision, manage, monitor and scale multiple Elastic Stack deployments, giving organizations the ability to control all their deployments from a single place.

Elastic Cloud Enterprise (ECE) 2.0 would elevate the control and administrative ease with many new features such as host tagging, customizable deployment templates including hot-warm architecture, automated index curation, and more.

Consider an Elastic user starting with a single cluster servicing a single use case, such as centralized logging, and growing that use case over time. As the initial logging use case grows to multiple teams or divisions, ECE would enable a user to establish a centralized ‘logging as a service’ for their entire organization.

In addition, if an organization chooses to expand into new use cases like application or site search, APM, metrics, business analytics, and security analytics, Elastic Cloud Enterprise 2.0 would provide the foundation to manage all deployments, including multiple tenants, use cases, data sources and services with a single product aligned with the user’s IT, security, backup, and compliance policies and procedures.

Some of the new features and benefits of Elastic Cloud Enterprise (ECE) 2.0 include:

  • Deployment Control and Optimization – New host tagging and tag filtering features would help users control how deployments are mapped to their underlying hardware to optimize “for both performance and cost.”
  • Templated Architectures and Provisioning – ECE has new instance configuration and deployment templates for common architecture patterns to streamline and control how new clusters are structured and provisioned.
  • Hot-Warm Deployment Templates – ECE’s hot-warm deployment template and automated index curation would make it easy to deploy and scale hot-warm clusters, a common topology for time-series use cases like logging and metrics.
  • Anomaly Detection and Forecasting – ECE now comes with new dedicated machine learning nodes to let users “easily” add anomaly detection and forecasting capabilities to their Elasticsearch clusters.
  • SAML Security Authentication – Users have the option to secure Elasticsearch clusters launched via ECE with SAML authentication using their own preferred SAML identity provider.
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