7.3.0 release highlightsedit

Each release of Beats brings new features and product improvements. Here are the highlights of the new features and enhancements in 7.3.0.

Refer to the Beats Breaking Changes and Release Notes for a list of bug fixes and other changes.

Automated Functionbeat deployment with CloudFormation templatesedit

Functionbeat 7.3.0 introduces the ability to export a CloudFormation template for integration with automation systems. Previously, Functionbeat was only available for manual command line deployment, but with this new functionality, you can more easily automate Functionbeat deployments through their own CloudFormation stacks.

To export CloudFormation templates, use the following command:

$ ./functionbeat export function <FUNCTION_NAME>

Google Cloud integrationsedit

Filebeat 7.3.0 introduces a Google Cloud module that monitors Virtual Private Cloud (VPC) flow logs from Google Cloud through Stackdriver. It ships data to Elasticsearch in ECS format, so it’s immediately available for analysis in the SIEM app (or with Maps or a Canvas workpad).

Along with the module, Filebeat also introduces a Google Cloud Pub/Sub input for consuming from Google Cloud Pub/Sub topics. You can use this input to ingest all your events from Google Cloud for real-time analytics with the Elastic Stack.

Expanded database monitoringedit

7.3.0 introduces support for three new databases in Metricbeat and a new database source in Filebeat.

  • Oracle Database

    The Metricbeat Oracle module provides the tablespace metricset, which includes information about data files and temp files, grouped by tablespace. This module includes information about used and free space, the status of the data files, and the status of the tablespace itself.

  • Amazon RDS

    If you’re using Amazon Relational Database Service (RDS), you can now collect a rich set of metrics about your deployment, from CPU and memory usage, to disk and network throughput and latency. See all the details in the RDS metricset, now available in the Metricbeat AWS module.

  • CockroachDB

    The Metricbeat CockroachDB module exposes the status metricset, which is compatible with any CockroachDB version exposing metrics in Prometheus format.

  • Microsoft SQL Server

    The Filebeat MS SQL module monitors the Microsoft SQL Server error logs with the Elastic Stack.

Improved Kubernetes monitoringedit

Metricbeat 7.3.0 strengthens Kubernetes observability by introducing metricsets for three additional Kubernetes components:

Configuration-only Metricbeat modulesedit

For developers, we’ve streamlined the process of adding new data sources. 7.3.0 introduces a new way of creating Metricbeat modules, called light modules, that doesn’t require a single line of Go code. Light modules provide pre-defined configurations on top of existing, more generic modules, such as Prometheus or Jolokia. In fact, the CockroachDB module, introduced in this release, is a light module.