Compare Cloud Costs
Compare Cloud Costs

RAG AI Application

A generative AI application using a Foundational Model connected to a Vector Database to search proprietary documents and return grounded answers.

Prices

Estimated monthly on-demand costs for this workload architecture.

Workload Costs Comparison

Prices by provider and services that enable users to run this workload. Shape the architecture based on cloud best practices using the four Architecture Priorities below — Capacity, Performance, Reliability, and Security. Components and prices recompute as you adjust each priority (e.g. higher Security adds a WAF, KMS, and threat monitoring), and you can switch region or billing period to compare like-for-like.

How each price was matched
CloseMeets the requirement but over-provisioned — the smallest SKU this provider sells above the requested size is materially larger.ApproximateFalls short on vCPU or memory. The price is real but it buys less than the architecture asks for.No comparable SKUNothing in this provider's catalog is close enough to compare fairly. Excluded from the total — the column is not a like-for-like alternative for that line.Not offeredThe provider does not sell a product in this category at all.
Unbadged prices are exact matches. Hover any badge for the specific reason. Totals cover only the components a provider actually matched — the “N of M tracked” note under a total says how many.
Workload Configuration

Architecture Priorities

Select level (High / Medium / Low) to adjust requirements
Query & Corpus Volume
Speed — instance class, storage media, caching
Redundancy — HA, replicas, backups, load balancing
Hardening — WAF, key management, threat detection
What this builds
Document Storage×100API & OrchestrationEmbeddings ModelVector Database×2Foundational ModelBackup Storage×64

Infrastructure Architecture Blueprint

Copy or download (export) Terraform and OpenTofu architecture blueprints to deploy this workload in a cloud provider of your choice. Add parameters, credentials, or steps for CLI and DevOps CI/CD pipelines.

Provider:
Engine:
1# ==============================================================================
2# ARCHITECTURE BLUEPRINT (TERRAFORM / OPENTOFU)
3# Copyright (c) 2026 Cosell Plus, LLC. All Rights Reserved.
4#
5# DISCLAIMER & TERMS OF USE:
6# This IaC blueprint is generated by CompareCloudCosts (CCC) for educational,
7# planning, and directional architectural purposes. Provided "AS IS" without
8# warranty of any kind, express or implied. Cosell Plus, LLC assumes no
9# liability for operational costs, misconfigurations, or service interruptions.
10# Always review and validate security, IAM, and compliance parameters before
11# deploying to production environment.
12# ==============================================================================
13#
14# ------------------------------------------------------------------------------
15# IDENTITY & CREDENTIAL PLACEHOLDERS (CLI & DEVOPS CI/CD PIPELINE)
16# ------------------------------------------------------------------------------
17# Steps to execute this blueprint using Terraform:
18# 1. Save this file as main.tf
19# 2. Set provider authentication credentials:
20#
21# For AWS Local CLI Execution:
22# export AWS_ACCESS_KEY_ID="<YOUR_AWS_ACCESS_KEY_ID>"
23# export AWS_SECRET_ACCESS_KEY="<YOUR_AWS_SECRET_ACCESS_KEY>"
24# export AWS_REGION="<REGION>"
25#
26# For AWS DevOps CI/CD Pipeline (GitHub Actions / GitLab CI / Azure DevOps):
27# Recommended: Use AWS OpenID Connect (OIDC) Role Assumption:
28# - role-to-assume: "arn:aws:iam::123456789012:role/GitHubActionsDeployerRole"
29# - aws-region: "<REGION>"
30#
31# 3. Initialize and apply:
32# $ terraform init
33# $ terraform plan
34# $ terraform apply
35# ------------------------------------------------------------------------------
36
37# ------------------------------------------------------------------------------
38# PROVIDER CONFIGURATION (TERRAFORM)
39# ------------------------------------------------------------------------------
40🔑 terraform {
41 required_version = ">= 1.5.0"
42 required_providers {
43 aws = {
44 source = "hashicorp/aws"
45 version = "~> 5.0"
46 }
47 }
48}
49
50🔑 provider "aws" {
51 region = var.aws_region
52
53 default_tags {
54 tags = {
55 ManagedBy = "Terraform"
56 Environment = var.environment
57 Workload = var.workload_id
58 Vendor = "Cosell Plus LLC Blueprint"
59 }
60 }
61}
62
63🔑 variable "aws_region" {
64 type = string
65 default = "us-east-1"
66 description = "Target AWS Deployment Region"
67}
68
69🔑 variable "environment" {
70 type = string
71 default = "production"
72 description = "Deployment environment (e.g. dev, staging, production)"
73}
74
75🔑 variable "workload_id" {
76 type = string
77 default = "workload-blueprint"
78 description = "Identifier tag for the workload"
79}
80
81# ------------------------------------------------------------------------------
82# WORKLOAD COMPONENT RESOURCES (RAG AI APPLICATION)
83# ------------------------------------------------------------------------------
84# Component: Document Storage
85🔑 resource "aws_s3_bucket" "document_storage" {
86 bucket_prefix = "ccc-document_storage-"
87 force_destroy = false
88}
89
90🔑 resource "aws_s3_bucket_server_side_encryption_configuration" "document_storage_enc" {
91 bucket = aws_s3_bucket.document_storage.id
92 rule {
93 apply_server_side_encryption_by_default {
94 sse_algorithm = "AES256"
95 }
96 }
97}
98
99
100
101# Component: API & Orchestration
102🔑 resource "aws_launch_template" "api_orchestration_lt" {
103 name_prefix = "api_orchestration-lt-"
104 image_id = "ami-0c55b159cbfafe1f0" # Amazon Linux 2023 AMI
105 instance_type = "t4g.medium"
106
107 tag_specifications {
108 resource_type = "instance"
109 tags = {
110 Name = "API & Orchestration"
111 }
112 }
113}
114
115🔑 resource "aws_autoscaling_group" "api_orchestration_asg" {
116 name_prefix = "api_orchestration-asg-"
117 min_size = 1
118 max_size = 4
119 desired_capacity = 1
120 vpc_zone_identifier = ["subnet-placeholder-1", "subnet-placeholder-2"]
121
122 launch_template {
123 id = aws_launch_template.api_orchestration_lt.id
124 version = "$Latest"
125 }
126}
127
128# Component: Embeddings Model (Converts the incoming query into vector embeddings)
129🔑 resource "aws_custom_🔑 resource" "embeddings" {
130 # Add required parameters for Embeddings Model
131}
132
133# Component: Vector Database (Stores and searches document embeddings (Managed Vector / Relational DB))
134🔑 resource "aws_custom_🔑 resource" "vector_db" {
135 # Add required parameters for Vector Database
136}
137
138# Component: Foundational Model (Generates the final response from query and retrieved context)
139🔑 resource "aws_custom_🔑 resource" "llm" {
140 # Add required parameters for Foundational Model
141}
142
143# Component: Backup Storage
144🔑 resource "aws_s3_bucket" "backup_storage" {
145 bucket_prefix = "ccc-backup_storage-"
146 force_destroy = false
147}
148
149🔑 resource "aws_s3_bucket_server_side_encryption_configuration" "backup_storage_enc" {
150 bucket = aws_s3_bucket.backup_storage.id
151 rule {
152 apply_server_side_encryption_by_default {
153 sse_algorithm = "AES256"
154 }
155 }
156}
157
158
159
160
161# ------------------------------------------------------------------------------
162# OUTPUTS
163# ------------------------------------------------------------------------------
164🔑 output "blueprint_summary" {
165 value = {
166 workload_id = "rag-ai-app"
167 🔑 provider = "aws"
168 region = "us-east-1"
169 components = 6
170 priorities = {
171 capacity = "medium"
172 performance = "medium"
173 reliability = "medium"
174 security = "medium"
175 }
176 }
177}
178

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Disclaimer: These price results are conceptual, for comparison only. The algorithm auto-selects the cheapest matching infrastructure that meets the memory and compute minimums from your scale parameters, without accounting for licensing, egress fees, custom integrations, or platform limitations. Check official provider documentation for real-world sizing. Visit our Terms of Use for data coverage details.