Fast, scalable and reliable logging using Fluent Bit and ClickHouse
klogs
klogs can be used to write the logs collected by Fluent Bit to ClickHouse. You can use klogs with or without Kafka:
Fluent Bit Plugin: The klogs Fluent Bit plugin allows you to directly write the collected logs from Fluent Bit into ClickHouse.
ClickHouse Ingester: The klogs ClickHouse ingester allows you to write your logs from Fluent Bit into Kafka, so that the ingester can write them from Kafka into ClickHouse.
You can use kobs as interface to get the logs from ClickHouse. More information regarding the klogs plugin for kobs can be found in the klogs documentation of kobs.
Configuration
The configuration for the Fluent Bit Plugin and ClickHouse Ingester can be found in the corresponding directories in the cmd
folder.
The SQL schema for ClickHouse must be created on each ClickHouse node and looks as follows:
CREATE DATABASE IF NOT EXISTS logs ON CLUSTER `{cluster}` ENGINE=Atomic;
CREATE TABLE IF NOT EXISTS logs.logs_local ON CLUSTER `{cluster}`
(
`timestamp` DateTime64(3) CODEC(Delta, LZ4),
`cluster` LowCardinality(String),
`namespace` LowCardinality(String),
`app` LowCardinality(String),
`pod_name` LowCardinality(String),
`container_name` LowCardinality(String),
`host` LowCardinality(String),
`fields_string` Map(LowCardinality(String), String),
`fields_number` Map(LowCardinality(String), Float64),
`log` String CODEC(ZSTD(1))
)
ENGINE = ReplicatedMergeTree
PARTITION BY toDate(timestamp)
ORDER BY (cluster, namespace, app, pod_name, container_name, host, timestamp)
TTL toDateTime(timestamp) + INTERVAL 30 DAY;
CREATE TABLE IF NOT EXISTS logs.logs ON CLUSTER '{cluster}' AS logs.logs_local ENGINE = Distributed('{cluster}', logs, logs_local, rand());
To speedup queries for the most frequently queried fields we can create dedicated columns for specific fiels:
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' ADD COLUMN content_level String DEFAULT fields_string['content.level']
ALTER TABLE logs.logs ON CLUSTER '{cluster}' ADD COLUMN content_level String DEFAULT fields_string['content.level']
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' ADD COLUMN content_response_code Float64 DEFAULT fields_number['content.response_code']
ALTER TABLE logs.logs ON CLUSTER '{cluster}' ADD COLUMN content_response_code Float64 DEFAULT fields_number['content.response_code']
But those columns will be materialized only for new data and after merges. In order to materialize those columns for old data:
- You can use
ALTER TABLE MATERIALIZE COLUMN
for ClickHouse version > 21.10.
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' MATERIALIZE COLUMN content_level;
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' MATERIALIZE COLUMN content_response_code;
- Or for older ClickHouse versions,
ALTER TABLE UPDATE
.
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' UPDATE content_level = content_level WHERE 1;
ALTER TABLE logs.logs_local ON CLUSTER '{cluster}' UPDATE content_response_code = content_response_code WHERE 1;