![]() ![]() ![]() ![]() The timestamp field gets chosen automatically for you, so no need to change anything there. For the index pattern, I still use filebeat-* (you’ll see the index name on the right turn bold as you type, indicating that it’s matching), although I’m not sure whether the wildcard actually makes a difference now that the index is some new thing called a data stream. You can give the data view a name and an index pattern. At Discover, you’re asked to create a data view.Ĭlick on the “Create data view” button. If I understand correctly, this “data view” is what used to be called an “index pattern” before. There, you’ll be prompted to create a “data view” (if you don’t have any data, you’ll be shown a different prompt offering integrations instead). Now that we know that some data exists, click the hamburger menu at the top-left corner again and go to “Discover” (the first item). GET _cat/indices shows that we have a Filebeat index. If you see an index whose name contains “filebeat” in the results panel on the right, then that’s encouraging. We can follow the same pattern as the other services in instances.yml to create a certificate for Filebeat: It creates a file at config/certs/instances.yml specifying what certificates are needed, and passes that to the bin/elasticsearch-certutil command to create them. The setup service in docker-compose.yml has a script that generates the certificates used by all the Elastic stack services defined there. certs: this is the same as in all the other services and is part of what allows them to communicate securely using SSL certificates.test.log: we’re including this example file just to see that Filebeat actually works.filebeat.yml: this is how we’ll soon be passing Filebeat its configuration.The most interesting part of this is the volumes: ELASTICSEARCH_SSL_CERTIFICATEAUTHORITIES=config/certs/ca/ca.crt env and docker-compose.yml files, you can run the following command to spin up a three-node Elasticsearch cluster and Kibana: This is a large file so I won’t include it here, but in case the documentation changes, you can find an exact copy at the time of writing as docker-compose-original.yml in the aforementioned BitBucket repo. Next, copy the sample docker-compose.yml. # Project namespace (defaults to the current folder name if not set) ![]() # Increase or decrease based on the available host memory (in bytes) # Port to expose Elasticsearch HTTP API to the host # Set to 'basic' or 'trial' to automatically start the 30-day trial # Password for the 'kibana_system' user (at least 6 characters) # Password for the 'elastic' user (at least 6 characters) env file and fill in any values you like for the ELASTIC_PASSWORD and KIBANA_PASSWORD settings, such as the following (don’t use these values in production): The section “ Start a multi-node cluster with Docker Compose” provides what you need to run a three-node Elasticsearch cluster with Kibana in Docker using docker-compose. The “ Install Elasticsearch with Docker” page at the official Elasticsearch documentation is a great starting point to run Elasticsearch with Docker. A lot of things can go wrong along the way, so I’ve included a lot of troubleshooting steps.This is merely a starting point and by no means production-ready.You can find the relevant files for this article in the FekDockerCompose folder at the Gigi Labs BitBucket Repository.I’ll be doing this with Elastic stack 8.4 on Linux, so if you’re on Windows or Mac, drop the sudo from in front of the commands.In this article, I’ll show you how to tweak this docker-compose.yml to run Filebeat alongside Elasticsearch and Kibana. Although the Elasticsearch docs provide an example docker-compose.yml that includes Elasticsearch and Kibana with certificates, this doesn’t include Filebeat. Security is enabled by default from Elasticsearch 8.0 onwards, so you’ll need SSL certificates, and the examples you’ll find on the internet using docker-compose from the Elasticsearch 7.x era won’t work. Getting them to work together, however, is not trivial. I still remember how painful it always was to set up Elasticsearch on Linux, or to set up both Elasticsearch and Kibana on Windows, and occasionally having to repeat this process occasionally to upgrade or recreate the Elastic stack.įortunately, Docker images now exist for all Elastic stack components including Elasticsearch, Kibana and Filebeat, so it’s easy to spin up a container, or to recreate the stack entirely in a matter of seconds. Docker is one of those tools I wish I had learned to use a long time ago. ![]()
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