Send logs to Kafka

A simple guide to send logs to Kafka in just a few minutes.
type: tutorialdomain: sinkssink: kafka

Logs are an essential part of observing any service; without them you are flying blind. But collecting and analyzing them can be a real challenge -- especially at scale. Not only do you need to solve the basic task of collecting your logs, but you must do it in a reliable, performant, and robust manner. Nothing is more frustrating than having your logs pipeline fall on it's face during an outage, or even worse, disrupt more important services!

Fear not! In this guide we'll show you how to send send logs to Kafka and build a logs pipeline that will be the backbone of your observability strategy.

Background

What is Kafka?

Apache Kafka is an open source project for a distributed publish-subscribe messaging system rethought as a distributed commit log. Kafka stores messages in topics that are partitioned and replicated across multiple brokers in a cluster. Producers send messages to topics from which consumers read. This makes it an excellent candidate for durably storing logs and metrics data.

Strategy

How This Guide Works

We'll be using Vector to accomplish this task. Vector is a popular open-source utility for building observability pipelines. It's written in Rust, making it lightweight, ultra-fast and highly reliable. And we'll be deploying Vector as a daemon.

The daemon deployment strategy is designed for data collection on a single host. Vector runs in the background, in its own process, collecting all data for that host. Typically data is collected from a process manager, such as Journald via Vector's journald source, but can be collected through any of Vector's sources. The following diagram demonstrates how it works.

Vector daemon deployment strategyVector daemon deployment strategy
1. Your service logs to STDOUT
STDOUT follows the 12 factor principles.
2. STDOUT is captured
STDOUT is captured by your platform.
3. Vector collects & fans-out data
Vector will send logs to Kafka.

What We'll Accomplish

To be clear, here's everything we'll accomplish in this short guide:

  • Collect your logs from one or more sources
  • Send logs to Kafka.
    • Leverage any of AWS' IAM strategies.
    • Optionally compress data to maximize throughput.
    • Automatically retry failed requests, with backoff.
    • Buffer your data in-memory or on-disk for performance and durability.
  • All in just a few minutes!

Tutorial

  1. Install Vector

    curl --proto '=https' --tlsv1.2 -sSf https://sh.vector.dev | sh
    explain this command

    Or choose your preferred method.

  2. Configure Vector

    cat <<-VECTORCFG > vector.toml
    [sources.in]
    include = ["/var/log/nginx/*.log"] # required
    type = "file" # required
    [sinks.out]
    # General
    bootstrap_servers = "10.14.22.123:9092,10.14.23.332:9092" # required
    inputs = ["in"] # required
    key_field = "user_id" # required
    topic = "topic-1234" # required
    type = "kafka" # required
    # Encoding
    encoding.codec = "json" # required
    VECTORCFG
    explain this command
  3. Start Vector

    vector --config vector.toml

    That's it! Simple and to the point. Hit ctrl+c to exit.

Next Steps

Vector is powerful utility and we're just scratching the surface in this guide. Here are a few pages we recommend that demonstrate the power and flexibility of Vector:

Vector Github repo 4k
Vector is free and open-source!
Vector getting started series
Go from zero to production in under 10 minutes!
Vector documentation
Thoughtful, detailed docs that respect your time.