Deploying to Google Cloud Platform in 2026 offers several paths, from manual console configuration to fully automated infrastructure-as-code. The right approach depends on your team's size, experience, and what you're building.

This guide covers the main options for deploying backend applications to GCP, with trade-offs, code examples, and recommendations.

Option 1: GCP Console (Click-Ops)

The Google Cloud Console is where most developers start. You navigate through the UI, configure services, and deploy manually.

When it works:

• Learning GCP concepts
• Quick experiments and prototypes
• One-off tasks

When it doesn't:

• Reproducible environments (staging, production)
• Team collaboration
• Compliance and audit requirements

Like any cloud console, it's fine for learning but doesn't scale. There's no version control, no review process, and no easy way to replicate what you built.

Option 2: Infrastructure from Code (Encore)

Encore takes a different approach than traditional infrastructure-as-code. Instead of writing separate infrastructure definitions, you declare what your application needs directly in your backend code. Encore Cloud then provisions GCP resources automatically.

import { api } from "encore.dev/api";
import { SQLDatabase } from "encore.dev/storage/sqldb";
import { Topic } from "encore.dev/pubsub";

// This creates a Cloud SQL PostgreSQL database
const db = new SQLDatabase("users", {
  migrations: "./migrations",
});

// This creates GCP Pub/Sub
const signups = new Topic<SignupEvent>("signups", {
  deliveryGuarantee: "at-least-once",
});

// This deploys to Cloud Run
export const createUser = api(
  { method: "POST", path: "/users", expose: true },
  async (req: CreateUserRequest) => {
    const user = await db.exec`INSERT INTO users ...`;
    await signups.publish({ userId: user.id });
    return user;
  }
);

When you push code, Encore analyzes it and provisions the corresponding GCP resources: Cloud SQL for databases, GCP Pub/Sub for messaging, Cloud Run for compute, Cloud Storage for objects, Cloud Scheduler for cron jobs.

What you get:

• No Terraform or Deployment Manager to write
• Infrastructure changes through code review
• Local development with Docker-based versions of GCP services
• Preview environments for every pull request
• Built-in observability (tracing, metrics, logs)

Trade-offs:

• Less granular control over resource configuration than raw Terraform
• Newer ecosystem than Terraform

Encore works well for teams that want GCP infrastructure ownership without becoming infrastructure experts. Companies like Groupon use this approach to power their backends at scale. The open-source framework has 11k+ GitHub stars.

Option 3: Google Cloud Deployment Manager

Deployment Manager is GCP's native infrastructure-as-code service. You define resources in YAML or Jinja2/Python templates.

resources:
- name: my-database
  type: sqladmin.v1beta4.instance
  properties:
    region: us-central1
    databaseVersion: POSTGRES_15
    settings:
      tier: db-f1-micro
      
- name: my-function
  type: cloudfunctions.v1.function
  properties:
    location: us-central1
    runtime: nodejs18
    entryPoint: handler
    sourceArchiveUrl: gs://my-bucket/function.zip

What you get:

• Native GCP integration
• No third-party dependencies
• Preview deployments before applying

Trade-offs:

• Verbose YAML syntax
• Limited community compared to Terraform
• GCP-only
• Less actively developed than other options

Deployment Manager works but hasn't seen the same investment as Terraform or even CloudFormation. Most teams choose Terraform instead.

Option 4: Terraform

Terraform is the industry standard for infrastructure-as-code and works well with GCP. It uses HashiCorp Configuration Language (HCL).

// Terraform HCL syntax
provider "google" {
  project = "my-project"
  region  = "us-central1"
}

resource "google_sql_database_instance" "main" {
  name             = "my-database"
  database_version = "POSTGRES_15"
  region           = "us-central1"

  settings {
    tier = "db-f1-micro"
  }
}

resource "google_cloud_run_service" "api" {
  name     = "my-api"
  location = "us-central1"

  template {
    spec {
      containers {
        image = "gcr.io/my-project/my-api:latest"
        env {
          name  = "DATABASE_URL"
          value = google_sql_database_instance.main.connection_name
        }
      }
    }
  }
}

What you get:

• Multi-cloud support (AWS, Azure, GCP)
• Massive ecosystem
• State management for tracking deployments
• Plan/apply workflow for reviewing changes
• Large community and documentation

Trade-offs:

• Learning HCL
• State file management complexity
• Separate from application code

Terraform is a popular choice for GCP infrastructure-as-code, particularly for teams that need multi-cloud support. The trade-off is maintaining a separate codebase for infrastructure.

Option 5: Pulumi

Pulumi lets you write infrastructure-as-code in real programming languages instead of HCL or YAML.

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const database = new gcp.sql.DatabaseInstance("database", {
  databaseVersion: "POSTGRES_15",
  region: "us-central1",
  settings: {
    tier: "db-f1-micro",
  },
});

const service = new gcp.cloudrun.Service("api", {
  location: "us-central1",
  template: {
    spec: {
      containers: [{
        image: "gcr.io/my-project/my-api:latest",
        envs: [{
          name: "DATABASE_URL",
          value: database.connectionName,
        }],
      }],
    },
  },
});

What you get:

• Real programming language (TypeScript, Python, Go)
• Type safety and IDE support
• Multi-cloud support
• Loops, conditionals, functions

Trade-offs:

• Smaller ecosystem than Terraform
• Still requires understanding GCP service configuration
• Separate from application code

Pulumi offers an alternative to Terraform's HCL if you prefer TypeScript, but you still need to understand GCP service configuration.

Option 6: Cloud Run Direct Deployment

For simple containerized applications, Cloud Run offers direct deployment without infrastructure-as-code.

# Build and deploy in one command
gcloud run deploy my-api \
  --source . \
  --region us-central1 \
  --allow-unauthenticated

What you get:

• Simple deployment for containers
• No infrastructure config needed
• Fast iteration

Trade-offs:

• Only covers compute (not databases, queues, etc.)
• No infrastructure version control
• Doesn't scale to complex applications

Cloud Run's direct deployment works for simple services but you'll need something else for databases, Pub/Sub, and other resources.

Comparison

Approach	Learning Curve	Flexibility	Maintenance	Best For
Console	Low	High	None (not repeatable)	Learning, experiments
Encore	Low	Medium	Low	Teams wanting GCP without DevOps
Deployment Manager	High	High	High	GCP-native requirements
Terraform	Medium	Very High	Medium	Multi-cloud, large infra
Pulumi	Medium	Very High	Medium	Developers who prefer real code
Cloud Run Direct	Low	Low	Low	Simple containerized apps

Which Should You Choose?

Choose the Console if:

• You're learning GCP
• It's a one-time experiment

Choose Encore if:

• You want to focus on backend code, not infrastructure
• You want GCP ownership without becoming a GCP expert
• You value fast iteration and built-in observability
• Your infrastructure needs are covered by databases, queues, cron, storage

Choose Deployment Manager if:

• Your organization mandates GCP-native tooling
• You can't use third-party tools

Choose Terraform if:

• You need multi-cloud support
• You have complex infrastructure requirements
• Your team has (or wants to build) infrastructure expertise
• You're already using Terraform for other projects

Choose Pulumi if:

• You want Terraform's flexibility with real programming languages
• Your team prefers TypeScript/Python over HCL

Choose Cloud Run Direct if:

• You're deploying a simple containerized app
• You don't need databases or other managed services

Getting Started

Start with the simplest option that meets your needs. If you're building a backend application and don't want to become an infrastructure expert, Encore is worth trying. If you need maximum flexibility or multi-cloud support, Terraform is the industry standard.

Whatever you choose, avoid the console for production workloads. Infrastructure-as-code isn't optional in 2026.

Related Resources

• How to Deploy to AWS in 2026
• Encore vs Terraform
• Migrate from Firebase to GCP