IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.
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Elastic Docs ›Beats Platform Reference [7.5] ›Release highlights

7.3 release highlights

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7.3 release highlights

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Each release of Beats brings new features and product improvements. Following are the most notable features and enhancements in 7.3.

For a complete list of highlights, see the Beats 7.3 release blog.

For a list of bug fixes and other changes, see the Beats Breaking Changes and Release Notes.

Automated Functionbeat deployment with CloudFormation templates

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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 integrations

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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 monitoring

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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 monitoring

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

Configuration-only Metricbeat modules

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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.

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