The 2026 Guide to Pulumi: Why Developers Are Moving Beyond YAML

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InfraDiaries

For years, infrastructure felt like paperwork.

Hundreds of lines of YAML.
Repetitive HCL blocks.
Copy-pasted modules.
Tiny indentation mistakes breaking entire deployments.

Infrastructure as Code gave us version control — but it didn’t give us software engineering.

Pulumi challenges that model.

Instead of writing infrastructure in a custom DSL, you write it in real programming languages: TypeScript, Python, Go, C#, even Java. The result isn’t just cleaner syntax. It’s a different way of thinking about infrastructure altogether.

In 2026, Pulumi has matured into a serious production tool used across AWS, Azure, GCP, Kubernetes, and even SaaS platforms like Cloudflare and Datadog.

This is not a beginner overview.
This is a production-focused deep dive.

Infrastructure as Software — Not Configuration

Most IaC tools are declarative DSLs. You describe what should exist, and the engine reconciles it.

That works — until your infrastructure grows.

As environments scale, teams need:

  • Reusable abstractions
  • Strong typing
  • Real testing frameworks
  • Package management
  • Internal libraries
  • Shared engineering standards

Traditional config languages weren’t designed for that level of complexity.

Pulumi takes a different route: infrastructure becomes an application.

You use loops.
You use conditionals.
You create classes.
You publish reusable packages.

Instead of copying resource blocks, you build infrastructure components.

That’s the real shift.

How Pulumi Works (The Workflow)

Pulumi still follows a declarative model — but you express it imperatively.

Here’s the lifecycle.

1. Write Infrastructure Code

Example using Python and AWS:

import pulumi
from pulumi_aws import s3

bucket = s3.Bucket("infradiaries-bucket")

pulumi.export("bucket_name", bucket.id)

That’s a real programming language.
No custom syntax. No YAML.

2. pulumi preview

Pulumi evaluates:

  • Your current cloud resources
  • Your state file
  • Your desired definition

It calculates a diff and shows exactly what will change.

Think of it as a safe execution plan.

This step is ideal for pull request validation.

3. pulumi up

Once approved, Pulumi:

  • Resolves dependencies
  • Orders operations
  • Executes API calls
  • Streams logs
  • Updates state

The engine handles the complexity so you don’t manually orchestrate resource ordering.

4. State Recording

Pulumi stores the resulting state.

That state becomes the authoritative reference for:

  • Future diffs
  • Drift detection
  • Rollbacks
  • Team collaboration

State management is where serious IaC systems are separated from hobby projects — and Pulumi treats it accordingly.

Internal Architecture: What’s Happening Under the Hood

Pulumi’s architecture is intentionally modular.

Language Host

Your chosen runtime (Node, Python, Go, .NET) executes the program. It registers resources with the Pulumi engine but does not create them directly.

Deployment Engine

The engine builds a dependency graph and compares it against the current state. It plans and executes changes safely and in parallel where possible.

Resource Providers

Providers are plugins for AWS, Azure, GCP, Kubernetes, and many other services.

Many providers are bridged from Terraform providers, which means Pulumi benefits from an enormous ecosystem and near day-zero cloud feature support.

This design is why Pulumi feels like a software framework rather than a configuration tool.

State Management in Production

State is critical.

Pulumi supports multiple backends:

Local Backend

Useful for experiments.

pulumi login file://

Not recommended for team production environments.

Pulumi Cloud

The most common production choice.

It provides:

  • State locking
  • Encryption
  • RBAC
  • Audit logs
  • Policy enforcement
  • Team collaboration

Self-Managed Backends

You can store state in:

  • AWS S3
  • GCS
  • Azure Blob Storage
  • S3-compatible object stores

This is useful for air-gapped or compliance-driven environments.

Secrets Handling

Pulumi encrypts secrets using:

  • Passphrase-based encryption
  • Cloud KMS providers
  • Built-in secret configuration

Secrets are never stored in plaintext state.

For regulated environments, this matters.

Stacks: Managing Environments Properly

Stacks are one of Pulumi’s strongest features.

Each stack represents an isolated deployment — typically dev, staging, or prod.

pulumi stack init dev
pulumi stack init staging
pulumi stack init prod

Each stack has:

  • Separate state
  • Separate configuration
  • Separate secrets

You can reuse the same code across environments without duplicating infrastructure definitions.

Stack References

Stacks can export outputs and be consumed by other stacks.

Example:

  • A network stack exports VPC ID
  • An application stack imports it

This encourages modular infrastructure design across teams.

CI/CD and GitOps Integration

Pulumi fits naturally into modern pipelines.

Typical flow:

  1. Developer opens PR
  2. pulumi preview runs
  3. Diff is posted for review
  4. Policy checks execute
  5. Merge triggers pulumi up

OIDC Instead of Static Credentials

Modern CI setups use short-lived credentials via OIDC instead of static AWS keys.

Pulumi integrates cleanly with this pattern.

Automation API

For advanced platform engineering use cases, Pulumi can be embedded inside applications.

This enables:

  • On-demand infrastructure provisioning
  • SaaS-driven resource creation
  • Internal self-service platforms

This is where Pulumi moves beyond traditional IaC tools.

Testing Infrastructure Like Software

One of Pulumi’s strongest advantages is testability.

Because you’re using real languages, you can:

  • Write unit tests
  • Mock providers
  • Validate resource properties
  • Enforce policies

Example:

def test_bucket_encryption():
    assert bucket.server_side_encryption_configuration is not None

Infrastructure is now part of your engineering test strategy — not a black box.

For mature DevOps teams, this is a major differentiator.

Real-World Production Example

Consider a typical production setup:

  • VPC
  • Public and private subnets
  • Application Load Balancer
  • ECS or EKS cluster
  • RDS database
  • S3 asset storage
  • CloudFront distribution

In Pulumi, you can abstract this into a reusable component.

Instead of copying resource definitions across environments, you create a class that encapsulates the entire architecture.

That abstraction layer is where long-term maintainability lives.

Pricing in 2026

Pulumi is open-source.

Pulumi Cloud adds managed features.

Individual Tier
Free for single-user projects.

Team Tier
Usage-based pricing with credits (first 150k free).

Enterprise Tier
SSO, advanced RBAC, audit logs, marketplace billing.

Important: You still pay your cloud provider separately.

For most startups and mid-sized teams, Pulumi Cloud costs are modest compared to infrastructure spend.

Pulumi vs Terraform in 2026

Terraform remains the industry standard.

It has:

  • A massive ecosystem
  • Enterprise adoption
  • Deep tooling integrations

Pulumi differentiates through:

  • Real programming languages
  • Native testing support
  • Stronger abstraction patterns
  • Better developer experience

If your team consists primarily of developers, Pulumi feels natural.

If your organization is standardized on Terraform across hundreds of teams, migration requires strategic planning.

Pulumi vs AWS CDK

AWS CDK is excellent for AWS-centric environments.

But it’s AWS-only.

Pulumi supports:

  • AWS
  • GCP
  • Azure
  • Kubernetes
  • SaaS providers

If your infrastructure spans multiple clouds, Pulumi provides a unified approach.

When Pulumi May Not Be Ideal

Pulumi is powerful — but not universal.

It may not be the best fit if:

  • Your organization mandates Terraform company-wide
  • Your team prefers declarative DSLs over coding
  • You operate in highly restricted, dependency-averse environments

Cultural alignment matters more than tool capability.

Migration Strategy from Terraform

Pulumi provides:

  • tf2pulumi conversion tooling
  • Terraform provider bridge compatibility
  • Incremental migration strategies

Many teams adopt Pulumi for new services while maintaining legacy Terraform stacks.

A gradual transition is often more realistic than a full rewrite.

Performance and Scaling Considerations

Pulumi supports:

  • Parallel resource operations
  • Dependency graph optimization
  • Multi-region stacks
  • Large deployments

As with any IaC system, structure matters. Clean stack boundaries and modular design are essential for scaling effectively.

The Bigger Picture: Platform Engineering

Pulumi aligns closely with modern platform engineering principles:

  • Reusable infrastructure components
  • Golden path templates
  • Policy as code
  • Self-service provisioning
  • Internal developer platforms

It transforms infrastructure from configuration files into a programmable platform.

Final Thoughts

Developers aren’t leaving YAML because YAML is bad.

They’re leaving because context switching is expensive.

Because abstraction matters.
Because testing matters.
Because reusable components matter.

Pulumi reduces the friction between application code and infrastructure code.

In 2026, that boundary feels increasingly unnecessary.

If your team thinks in software, Pulumi is worth serious consideration.

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