Logs are an essential part of observing any service; without them you'll have significant blind spots. 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, cause the outage!

Fear not! In this guide we'll build an observability pipeline that will send logs from AWS S3 to GCP Cloud Storage.

Background

What is AWS S3?

Amazon Simple Storage Service (Amazon S3) is a scalable, high-speed, web-based cloud storage service designed for online backup and archiving of data and applications on Amazon Web Services. It is very commonly used to store log data.

What is GCP Cloud Storage?

Google Cloud Storage is a RESTful online file storage web service for storing and accessing data on Google Cloud Platform infrastructure. The service combines the performance and scalability of Google's cloud with advanced security and sharing capabilities. This makes it a prime candidate for log data.

Strategy

How This Guide Works

We'll be using [Vector][urls.vector_website] to accomplish this task. Vector is a popular open-source observability data pipeline. It's written in Rust, making it lightweight, ultra-fast and highly reliable. And we'll be deploying Vector as a agent.

What We'll Accomplish

We'll build an observability data pipeline that:

• Collects logs from AWS S3.
  • Enriches data with useful AWS S3 context.
  • Efficiently collects data and checkpoints read positions to ensure data is not lost between restarts.
  • Securely collects data via Transport Layer Security (TLS).
  • Merges multi-line logs into one event.
• Sends logs to GCP Cloud Storage.
  • Buffers data in-memory or on-disk for performance and durability.
  • Compresses data to optimize bandwidth.
  • Automatically retries failed requests, with backoff.
  • Securely transmits data via Transport Layer Security (TLS).
  • Batches data to maximize throughput.

All in just a few minutes!

Tutorial

1. Install Vector

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

2. Configure Vector

   cat <<-'VECTORCFG' > ./vector.toml
   [sources.aws_s3]
   type = "aws_s3"
   region = "us-east-1"
   
   [sinks.out]
   type = "gcp_cloud_storage"
   inputs = [ "aws_s3" ]
   bucket = "my-bucket"
   
     [sinks.out.encoding]
     codec = "ndjson"
   VECTORCFG

3. Start Vector

   vector --config ./vector.toml

4. Observe Vector

   vector top

   explain this command

How was it? Did this tutorial work?  Yes  No

Next Steps

Vector is powerful tool 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 quickstart

Get setup in just a few minutes

Vector documentation

Everything you need to know about Vector

[urls.vector_website]: