dmesg
It reads kernel events from /dev/kmsg
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fake
It provides an API to test pipelines and other plugins.
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file
It watches for files in the provided directory and reads them line by line.
Each line should contain only one event. It also correctly handles rotations (rename/truncate) and symlinks.
From time to time, it instantly releases and reopens descriptors of the completely processed files.
Such behavior allows files to be deleted by a third party software even though file.d
is still working (in this case the reopening will fail).
A watcher is trying to use the file system events to detect file creation and updates.
But update events don't work with symlinks, so watcher also periodically manually fstat
all tracking files to detect changes.
⚠ It supports the commitment mechanism. But "least once delivery" is guaranteed only if files aren't being truncated.
However, file.d
correctly handles file truncation, there is a little chance of data loss.
It isn't a file.d
issue. The data may have been written just before the file truncation. In this case, you may miss to read some events.
If you care about the delivery, you should also know that the logrotate
manual clearly states that copy/truncate may cause data loss even on a rotating stage.
So use copy/truncate or similar actions only if your data isn't critical.
In order to reduce potential harm of truncation, you can turn on notifications of file changes.
By default the plugin is notified only on file creations. Note that following for changes is more CPU intensive.
⚠ Use add_file_name plugin if you want to add filename to events.
Reading docker container log files:
pipelines:
example_docker_pipeline:
input:
type: file
watching_dir: /var/lib/docker/containers
offsets_file: /data/offsets.yaml
filename_pattern: "*-json.log"
persistence_mode: async
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http
Reads events from HTTP requests with the body delimited by a new line.
Also, it emulates some protocols to allow receiving events from a wide range of software that use HTTP to transmit data.
E.g. file.d
may pretend to be Elasticsearch allows clients to send events using Elasticsearch protocol.
So you can use Elasticsearch filebeat output plugin to send data to file.d
.
⚠ Currently event commitment mechanism isn't implemented for this plugin.
Plugin answers with HTTP code OK 200
right after it has read all the request body.
It doesn't wait until events are committed.
Example:
Emulating elastic through http:
pipelines:
example_k8s_pipeline:
settings:
capacity: 1024
input:
# define input type.
type: http
# pretend elastic search, emulate it's protocol.
emulate_mode: "elasticsearch"
# define http port.
address: ":9200"
actions:
# parse elastic search query.
- type: parse_es
# decode elastic search json.
- type: json_decode
# field is required.
field: message
output:
# Let's write to kafka example.
type: kafka
brokers: [kafka-local:9092, kafka-local:9091]
default_topic: yourtopic-k8s-data
use_topic_field: true
topic_field: pipeline_kafka_topic
# Or we can write to file:
# type: file
# target_file: "./output.txt"
Setup:
# run server.
# config.yaml should contains yaml config above.
go run ./cmd/file.d --config=config.yaml
# now do requests.
curl "localhost:9200/_bulk" -H 'Content-Type: application/json' -d \
'{"index":{"_index":"index-main","_type":"span"}}
{"message": "hello", "kind": "normal"}
'
More details...
journalctl
Reads journalctl
output.
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k8s
It reads Kubernetes logs and also adds pod meta-information. Also, it joins split logs into a single event.
Source log file should be named in the following format:
[pod-name]_[namespace]_[container-name]-[container-id].log
E.g. my_pod-1566485760-trtrq_my-namespace_my-container-4e0301b633eaa2bfdcafdeba59ba0c72a3815911a6a820bf273534b0f32d98e0.log
An information which plugin adds:
k8s_node
– node name where pod is running;
k8s_node_label_*
– node labels;
k8s_pod
– pod name;
k8s_namespace
– pod namespace name;
k8s_container
– pod container name;
k8s_label_*
– pod labels.
⚠ Use add_file_name plugin if you want to add filename to events.
Example:
pipelines:
example_k8s_pipeline:
input:
type: k8s
offsets_file: /data/offsets.yaml
file_config: // customize file plugin
persistence_mode: sync
read_buffer_size: 2048
More details...
kafka
It reads events from multiple Kafka topics using sarama
library.
It guarantees at "at-least-once delivery" due to the commitment mechanism.
Example
Standard example:
pipelines:
example_pipeline:
input:
type: kafka
brokers: [kafka:9092, kafka:9091]
topics: [topic1, topic2]
offset: newest
meta:
partition: '{{ .partition }}'
topic: '{{ .topic }}'
offset: '{{ .offset }}'
# output plugin is not important in this case, let's emulate s3 output.
output:
type: s3
file_config:
retention_interval: 10s
endpoint: "s3.fake_host.org:80"
access_key: "access_key1"
secret_key: "secret_key2"
bucket: "bucket-logs"
bucket_field_event: "bucket_name"
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