What are Elasticsearch Beats?

The Elastic Stack expands the capabilities of Elasticsearch by adding extremely useful tooling to work alongside Elasticsearch. One of most useful of these tools is the Beats ecosystem. Beats are essentially lightweight, purpose-built agents that acquire data and then feed it to Elasticsearch.
The magic of Beats is the libbeat framework that makes it easy to create customized beats for any type of data you’d like to send to Elasticsearch. Due to that flexibility, the number of Beats available and the capabilities of Beats overall are rapidly expanding. Even those who have been using Elasticsearch for some time are finding that it is challenging to keep up with what Beats can offer them. However, it’s worth the time investment, because Beats have much to offer and Elasticsearch users are discovering that incorporating Beats into their stack offers a number of useful benefits and features.

What are Examples of Beats?
There are currently six official Beats from Elastic: Filebeat, Metricbeat, Packetbeat, Heartbeat, Winlogbeat, and Auditbeat. All of these beats are open source and Apache-licensed. Elastic maintains a list of regularly updated community beats that users can download, install, and even modify as needed. While each beat has its own distinct use, they all solve the common problem of gathering data at its source and making it easy and efficient to ship that data to Elasticsearch.

Filebeat is designed to read files from your system. It is particularly useful for system and application log files, but can be used for any text files that you would like to index to Elasticsearch in some way. In the logging case, it helps centralize logs and files in an efficient manner by reading from your various servers and VMs, then shipping to a central Logstash or Elasticsearch instance. Additionally, Filebeat eases the configuration process by including “modules” for grabbing common log file formats from MySQL, Apache, NGINX and more. These modules reduce the Filebeat configuration to a single command.

As the name implies, Metricbeat is used to collect metrics from servers and systems. It is a lightweight platform dedicated to sending system and service statistics. Like Filebeat, Metricbeat includes modules to grab metrics from operating systems like Linux, Windows and Mac OS, applications such as Apache, MongoDB, MySQL and nginx. Metricbeat is extremely lightweight and can be installed on your systems without impacting system or application performance. As with all of the Beats, Metricbeat makes it easy to create your own custom modules.

Packetbeat, a lightweight network packet analyzer, monitors network protocols to enable users to keep tabs on network latency, errors, response times, SLA performance, user access patterns and more. With Packetbeat, data is processed in real time so users can understand and monitor how traffic is flowing through their network. Furthermore, Packetbeat supports multiple application layer protocols, including MySQL and HTTP.

Winlogbeat is a tool specifically designed for providing live streams of Windows event logs. It can read events from any Windows event log channel, monitoring log-ons, log-on failures, USB storage device usage and the installation of new software programs. The raw data collected by Winlogbeat is automatically sent to Elasticsearch and then indexed for convenient future reference. Winlogbeat acts as a security enhancement tool and makes it possible for a company to keep tabs on literally everything that is happening on its Windows-powered hosts.

Auditbeat performs a similar function on Linux platforms, monitoring user and process activity across your fleet. Auditd event data is analyzed and sent, in real time, to Elasticsearch for monitoring the security of your environment.

Heartbeat is a lightweight shipper for uptime monitoring. It monitors services basically by pinging them and then ships data to Elasticsearch for analysis and visualization. Heartbeat can ping using ICMP, TCP and HTTP. IT has support for TLS, authentication and proxies. Its efficient DNS resolution enables it to monitor every single host behind a load-balanced server.

Elastic Stack + Beats

The Elastic Stack and Beats provide one of the most efficient data collection and indexing frameworks anywhere. There are so many datastores that have made themselves easy to bootstrap, but Elasticsearch and Beats make it easy to get the datastore running, and also to generate a continuous stream of real world actionable data. The fact that it is fully open source enables users from around the world to not only utilize it but also contribute to the Beats that are already out there.

Once you add in other tools from the Elasticsearch ecosystem, like Kibana, a visualization program used in conjunction with Elasticsearch, you can quickly and easily create an analytics and monitoring platform that rivals more expensive paid services like Splunk.

ObjectRocket for Elasticsearch
There’s a lot to consider when running Elasticsearch and other components of the Elastic Stack in production. Thankfully, ObjectRocket offers managed Elasticsearch and free consultations that provides users with fast, effective answers to questions regarding Elasticsearch, Kibana, Curator, Beats, and much more.