YAML in Backend Development

We take look at YAML and its challenges

4 Min Read

YAML (Yet Another Markup Language) has become a vital part of many software development projects, mostly due to its human-readable and intuitive structure. This article aims to shed light on the usage, benefits, and challenges of YAML, specifically in the realms of backend development and cloud infrastructure.

YAML: A Brief Introduction

YAML is a data serialization standard that's designed to be human-friendly and works perfectly with languages like Python, and JavaScript, among others. It allows developers to describe data structures in a format that’s easy to read and write.

Consider this example:

server: host: localhost port: 8080

This YAML snippet represents a simple configuration for a server with properties like host and port. The indentation illustrates hierarchy, making it easy to visualize the structure of the data.

Usage in Backend Development

In backend development, YAML files are often used for configuration. Frameworks like Ruby on Rails, Django, and Express.js can use YAML files to store settings. It's also used in Docker for creating Docker Compose files, which define services, networks, and volumes.

Consider a Docker Compose file:

version: '3' services: web: build: . ports: - "5000:5000"

This YAML file defines a Docker service named web that's built from the Dockerfile in the current directory and maps the host's port 5000 to the container's port 5000.

YAML in Cloud Infrastructure

In cloud infrastructure management, particularly in the Infrastructure as Code (IaC) paradigm, YAML is extensively used. Tools like Kubernetes, Helm, AWS CloudFormation, and Google Cloud Deployment Manager use YAML files for defining and managing resources on the cloud.

Here's an example of a Kubernetes deployment defined in a YAML file:

apiVersion: apps/v1 kind: Deployment metadata: name: nginx-deployment spec: replicas: 3 selector: matchLabels: app: nginx template: metadata: labels: app: nginx spec: containers: - name: nginx image: nginx:1.14.2 ports: - containerPort: 80

This YAML file tells Kubernetes to create a deployment with three replicas of the nginx server, each serving on port 80.

Challenges with YAML

Despite its ubiquity, YAML has its share of complexities and challenges that can create roadblocks and obstacles for developers.

Indentation and Syntax Issues

The most common challenge is managing indentation. YAML relies heavily on indentation to represent nested elements and the hierarchy of the data structure. A slight indentation error can change the data's meaning and even cause parsing errors. For example, consider the following YAML document:

a: 1 b: 2 c: - 3 - 4

This document defines a structure with three keys: a, b, and c. However, if we wrongly indent the c key, it could lead to a completely different structure or even a syntax error:

a: 1 b: 2 c: - 3 - 4

This situation is not desirable, especially in large configurations or data files, as it can lead to difficult-to-detect bugs and unexpected behaviors.

Managing Large YAML Files

Large YAML files, especially in the context of cloud configurations or complex backend configurations, can become cumbersome and difficult to manage. YAML files spanning hundreds or thousands of lines are not uncommon in complex cloud infrastructure configurations. Reading, managing, and maintaining such large YAML files is not a trivial task.

Take Kubernetes as an example. While Kubernetes excels in managing containerized applications at scale, managing Kubernetes YAML manifests can be a daunting task. It's common for developers to manage dozens or hundreds of YAML files in a single project, each with hundreds of lines.

Mitigating Challenges with Tooling

Some tools and practices try to alleviate these challenges. One common approach is breaking down large YAML files into smaller, manageable chunks. This strategy is often coupled with the use of template engines or tools that generate YAML files from templates, such as Helm for Kubernetes or Jinja2 for Ansible.

However, introducing such tools can increase the complexity of your projects. For instance, with Helm, you must now understand the Helm Chart structure, and how to create templates using the Go templating language. This addition introduces a new learning curve and another potential point of failure in your system.

Another mitigation strategy is the use of automated linting and validation tools that can catch syntax errors or misconfigurations. Tools like yamllint or kubeval can provide valuable feedback and catch errors before they lead to runtime issues. However, these tools can only catch syntactic issues, not semantic errors or misconfigurations that are technically correct but lead to undesired results.

If you’re interested in avoiding YAML and these challenges altogether for backend development, we encourage you to have a look at Encore. We’ve designed it from the ground up to remove this type of complexity, by letting you declare the infrastructure your application needs using an Infrastructure SDK. This keeps all the code relevant to the behavior of your application in one code base and one programming language.


YAML’s simplicity and human-friendly nature have made it an essential tool in backend development and cloud infrastructure. It's the backbone of numerous configurations, data serialization, and Infrastructure as Code (IaC) practices. However, like any tool, it's not without its challenges. Indentation and syntax issues, large and unwieldy files, and the complexity introduced by mitigation strategies can present significant hurdles.

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