7.7 release highlightsedit

Each release of Beats brings new features and product improvements. Following are the most notable features and enhancements in 7.7.

For a complete list of related highlights, see the Observability 7.7 release blog.

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

Azure Kubernetes and container monitoringedit

We’ve enhanced the Metricbeat Azure module with three new metricsets for monitoring Microsoft Azure container services: container_instance, container_registry, and container_service. These metricsets collect metrics from the following services:

  • Azure Kubernetes Service
  • Azure Container Instances
  • Azure Container Registry

Each metricset comes with a dashboard that makes it easy to get started monitoring Azure containers.

AWS VPCs, Lambdas, and DynamoDB monitoringedit

In the Metricbeat AWS module, we’ve added support for monitoring mission-critical services in the Amazon VPC ecosystem:

  • The natgateway metricset enables you to monitor NAT gateway services to gain a better perspective on how web applications or services are performing.
  • The transitgateway metricset collects metrics sent to CloudWatch by VPC when requests are flowing through the gateway. 
  • The vpn metricset enables you to monitor VPN tunnels. VPN metric data is automatically sent to CloudWatch as it becomes available.

Also new in this release, the lambda metricset monitors Lambda functions across multiple accounts and regions. The metricset collects metrics such as total invocations, errors, duration, throttles, dead-letter queue errors, and iterator age for stream-based invocations. You can use these metrics to configure alerts to respond to events such as changes in performance and error rates.

We’ve also added the dynamodb metricset to monitor AWS DynamoDB instances. This metricset collects metrics, such as request latency, transaction conflicts, provisioned and consumed capacity, and many others.   

For Amazon Aurora users, we’ve enhanced the rds metricset to collect metrics about your Aurora instances.

Google Cloud Platform (GCP) Pub/Sub and Load Balancer monitoringedit

We’ve enhanced the Metricbeat Google Cloud Platform module with support for monitoring additional services:

  • The pubsub metricset connects to the Stackdriver API and collects metrics for topics, subscriptions, and snapshots used by a specified account. 
  • The loadbalancing metricset captures load balancing performance metrics for HTTP(S), TCP, and UDP applications.

Pivotal Cloud Foundry (PCF) monitoringedit

We continue to expand coverage of container platforms by adding support for Pivotal Cloud Foundry.

The new Metricbeat Cloudfoundry module connects to the Cloud Foundry API and pulls container, counter, and value metrics from it. These metrics are stored in cloudfoundry.container, cloudfoundry.counter and cloudfoundry.value metricsets.

In Filebeat, the new cloudfoundry input collects http access logs, container logs, and error logs from Cloud Foundry.

To learn how to run Beats on Cloud Foundry, see:

IBM MQ monitoringedit

Prior to this release, we offered support in Filebeat for collecting and parsing queue manager error logs from IBM MQ.

In this release, we’ve added the missing piece: metrics. The new Metricbeat IBM MQ module pulls status information for the Queue Manager, which is responsible for maintaining queues and ensuring that messages in the queues reach their destination.

Redis Enterprise monitoringedit

In addition to our existing Redis module, which focuses on the open source version of the database, we’ve added the new Metricbeat Redis Enterprise module to monitor features such as nodes and proxies in a Redis cluster.

Istio monitoringedit

For Istio users, we’ve introduced the Metricbeat Istio module to collect metrics about service traffic (in, out, and within a service mesh), control-plane metrics for Istio Pilot, Galley, Mixer components, and much more.

ECS field improvements in Filebeatedit

The Elastic Common Schema (ECS) defines a common set of fields to be used when storing event data in Elasticsearch.

In 7.7, we’ve improved ECS field mappings in numerous Filebeat modules, making it easier for you to analyze, visualize, and correlate data across events. For a list of affected modules, see the Release Notes for 7.7.0.