Available Now · 50+ API Templates

Google Cloud Development Company

Cloud RunGKEBigQueryVertex AITerraform

Miracuves is an enterprise Google Cloud development company. Our cloud architects and backend engineers design, build and migrate applications on Google Cloud - Cloud Run or GKE for compute, Cloud SQL, AlloyDB, Spanner or Firestore for data, BigQuery and Vertex AI for analytics and AI - all written in Terraform inside an organization, projects and billing account in your company's name. Custom work takes 2-8 weeks; a ready-made platform goes live in 6 working days. 100% source code ownership from day one.

★★★★★ Clutch reviewed 5.0Ready-made platforms from $2,199View live deployments

  • 2,400+ APIs Deployed
  • Multi-Zone by Design
  • 100% Source Ownership
  • NDA Day One
6 daysReady-made platform delivery
$3,699Google Cloud work from
50+API templates
100%IP assignment
Google Cloud developers active right now
Cloud RunBigQueryCloud SQLPub/Sub9,000+ deliveredNDA day one
  • Cloud Run · GKEServerless or Kubernetes, matched to the workload
  • 50+ API TemplatesProduction-tested modules
  • TerraformEvery project and service kept as code
  • 6 DaysReady-made platform to launch
  • 100% Source CodeFull repo + docs on handoff
  • White-Label Ready

    Fully rebrandable on delivery

  • NDA Day One

    IP protected first call

  • Full Source Code

    Delivered at handoff

  • 60-Day Support

    Post-launch included

  • 100% IP Ownership

    Yours - always

  • Clutch Reviewed 5.0★

    Third-party verified

More than 6,000+ Companies Trust us Worldwide
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In short

Miracuves designs, builds and migrates applications on Google Cloud for founders and product teams: Cloud Run or GKE for compute, Cloud SQL, AlloyDB, Spanner or Firestore for data, BigQuery and Vertex AI for analytics and AI, all in Terraform inside an organization and billing account in your name. Custom work takes 2-8 weeks, a ready-made platform 6 working days, and you own 100% of the code.

Our Google Cloud Approach

How Miracuves delivers Google Cloud backends - from 2,400+ APIs of real experience

Across 2,400+ APIs, Miracuves has settled on how a Google Cloud project should start, and it is never one shared project where every developer is Owner. We begin with the resource hierarchy: an organization on your domain, folders for production and non-production, a separate project per environment, organization policies that block public buckets and service account keys, and a Terraform repository that creates all of it.

On top of that sits what your product needs: stateless services on Cloud Run, GKE when you need the Kubernetes API, Cloud SQL or AlloyDB for transactions, Pub/Sub for events, and BigQuery and Vertex AI when data and AI are part of the product. One Miracuves team owns the application code, the infrastructure and the delivery pipeline, and all of it is yours on handoff.

Who this service is built for: Founders and product teams building data-heavy SaaS, AI features on Vertex AI or backends for apps that started on Firebase, and companies moving servers or databases onto Google Cloud. Miracuves Google Cloud development fits when you want one company accountable for architecture, code and delivery, with published pricing and full IP ownership - not individual contractors. The Google Cloud organization, projects and billing account are in your company's name from day one. If your company runs on Microsoft 365 and .NET, Azure usually fits better; if your engineers and data already live on Amazon's cloud, AWS does. We will say so upfront and recommend the right cloud instead.

  • Compute matched to the workload: Cloud Run for stateless services, GKE Autopilot when you need the Kubernetes API, Cloud Run functions for event handlers
  • One service account per workload, Workload Identity Federation for CI: no downloaded JSON keys anywhere
  • Secrets in Secret Manager, private connections to Cloud SQL or AlloyDB, Cloud Armor in front of public endpoints
  • Cloud Build or GitHub Actions deploys every merge: images in Artifact Registry, each Terraform plan reviewed before apply
  • Cloud Monitoring dashboards, alerting policies and a billing budget in place before launch
9,000+Projects delivered since 2010
3,900+Apps published by Miracuves
90+Ready-made solutions to start from
6 daysReady-made clone delivery
2-8wMiracuves custom Google Cloud build timelines
100%Source code ownership
ServerlessCloud Run · functions
DataCloud SQL · AlloyDB · Spanner
Analytics & AIBigQuery · Vertex AI

Why Google Cloud at Miracuves

  • Ready-made platform6 working days
  • Default computeCloud Run · GKE Autopilot
  • Google Cloud project and billIn your company's name
  • API templates ready to ship50+ templates
  • Infrastructure as codeTerraform
  • Source code ownership100% yours
Example engagement: Singapore Food Delivery API, 3 weeks
"Real-time order dispatch API, webhooks for 12 delivery partners, Stripe payments and an admin dashboard, moved onto Google Cloud in 3 weeks. REST and WebSocket traffic runs on Cloud Run, partner webhooks fan out through Pub/Sub so one slow partner cannot hold up an order, live driver positions sit in Memorystore and orders in Cloud SQL for PostgreSQL. All of it is Terraform in the client's own Google Cloud project."

Ready-made platforms · 6 days

What Miracuves has deployed - what you can ship today

Six of our 90+ ready-made platforms, each shipping with its apps and admin panel in 6 days.

View All API Templates

Honest noteThese catalogue platforms are not Google Cloud products: each goes live in 6 working days on its own tested stack, web app, admin panel and mobile apps included, and any of them can be hosted in your own Google Cloud project. Google Cloud work designed around your product - Cloud Run or GKE services, databases, BigQuery pipelines, Terraform - is custom and priced below. If your product is a mobile app on Firebase, Firebase development may be all the backend you need.

Technology Comparison

Google Cloud vs AWS vs Azure - which is right for your project?

Agencies tied to one cloud seldom answer this straight. Miracuves builds on all three, picks Google Cloud when data and AI drive the product, and says plainly when AWS or Azure would serve you better - the choice fixes your running costs, your managed services and who you can hire for years.

MetricFive things that decide cost, speed and reach
Miracuves pick for data and AI

Google Cloud

Cloud Run · GKE · BigQuery · Vertex AI

AWS

Lambda · ECS · EKS · RDS

Microsoft Azure

Functions · AKS · Entra ID

01Serverless
Cloud RunContainers or functions that scale to zero, billed while they work
Lambda + FargateFunctions capped at 15 minutes; containers on Fargate
Functions + Container AppsEvent-driven functions plus serverless containers
02Analytics
BigQueryServerless warehouse, paid per query or by reserved capacity
Redshift + AthenaA warehouse, plus SQL straight over S3
Microsoft FabricLakehouse and warehouse tied to Power BI
03AI models
Vertex AIGemini plus third-party models in Model Garden
Bedrock + SageMakerHosted foundation models and a full ML platform
Azure OpenAIOpenAI models served inside your Azure tenant
04Discounts
Committed + sustained useCommit by resource or by spend; eligible VMs discounted automatically
Savings Plans1 or 3 year commitments on compute spend
Reservations + Hybrid BenefitReuse existing Windows Server and SQL Server licenses
05Best for
Data-heavy and AI productsAnalytics, ML, Firebase apps and teams on startup credits
Widest service catalogueSaaS and marketplaces that need many managed services
Microsoft-first companiesTeams on Entra ID, .NET and Microsoft 365
Choose Google Cloud if…

Your product's value is in its data and you want BigQuery for analytics · you plan AI features on Vertex AI with Gemini · stateless services should scale to zero on Cloud Run · the app already runs on Firebase, or your company signs in with Google Workspace · you hold Google Cloud startup credits.

Consider an alternative if…

Your team and data are already on AWS (AWS development) · your company runs on Microsoft 365, Entra ID and .NET (Azure development) · you need one design across several clouds (cloud engineering) · what you need is the application code rather than the cloud. See Python Development →

Google Cloud guide

What to know before you hire a Google Cloud development company

The decisions a Google Cloud buyer actually faces, answered for Google Cloud specifically: when it beats AWS or Azure, where the application should run, what BigQuery and Vertex AI projects involve, and who pays the Google bill.

When is Google Cloud a better choice than AWS or Azure?

Google Cloud earns its place when the product's value sits in its data. BigQuery lets a small team query terabytes without running a warehouse, Vertex AI serves Gemini models from the same project that holds the data, and Cloud Run runs containers that scale to zero between requests. It is also the natural home for apps already built on Firebase, whose projects are Google Cloud projects underneath, and for companies whose staff sign in with Google Workspace or that hold Google for Startups credits.

It is the weaker fit in a few common cases, and we say so before kickoff:

Should the application run on Cloud Run or GKE?

Cloud Run is our default. You hand Google a container image; it serves HTTP, gRPC or WebSocket traffic, adds instances as requests arrive, drops to zero when they stop, and bills for the time instances spend working. Cloud Run functions, the product formerly called Cloud Functions, handle small event handlers such as a file landing in Cloud Storage or a Pub/Sub message, and Cloud Run jobs handle batch work.

GKE is worth its extra operating cost when you need the Kubernetes API itself: sidecars and operators, stateful workloads, fine network control, or the same manifests running on another cloud. Autopilot mode leaves node management to Google and bills per pod; Standard mode gives you the nodes. Multi-cluster fleets and hybrid sites use the GKE Enterprise features that absorbed Anthos. For container-first teams, see Docker and Kubernetes development.

What does a BigQuery or Vertex AI project involve?

A BigQuery project is mostly plumbing and modelling: getting data in (Pub/Sub and Dataflow streams, Datastream change capture from Cloud SQL, scheduled loads from your SaaS tools), shaping it into partitioned and clustered tables, and exposing it to Looker Studio or your own dashboards. Partitioning matters because on-demand queries are billed by the bytes they scan, so we also set a maximum-bytes-billed limit that stops one careless query from running up a large bill.

A Vertex AI project puts a model on top of that data: Gemini for chat, extraction or summaries, grounded in your own documents or BigQuery tables, with an evaluation set written before launch so answer quality is measured rather than guessed. Prompts, data and logs stay in your project and the region you choose.

Which Google Cloud database fits: Cloud SQL, AlloyDB, Spanner or Firestore?

We choose from the access pattern, not from habit:

  • Cloud SQL - managed PostgreSQL, MySQL or SQL Server. The default for most transactional apps and the easiest to migrate into.
  • AlloyDB - PostgreSQL-compatible and built for heavier reads and analytical queries on live data. Worth it when Cloud SQL read replicas stop keeping up.
  • Spanner - relational, horizontally scalable and strongly consistent across regions. Right for global ledgers and inventories; costly overkill for a typical SaaS.
  • Firestore - a document database with real-time listeners and offline sync for mobile and web clients. If the app is built on Firebase end to end, start with Firebase development.

What does Google Cloud cost to run, and who pays the bill?

You pay Google directly. The organization, projects and Cloud Billing account are opened in your company's name from day one, and Miracuves works inside them through IAM roles you grant and can remove; our fee and your Google Cloud bill never mix. The bill is driven by compute time, database size, BigQuery bytes scanned or reserved slots, network egress to the internet, and log volume in Cloud Logging, which grows quietly if nobody sets retention.

We estimate the bill with the Google Cloud Pricing Calculator before the build. At launch we set budgets with alerts and export billing data to BigQuery. Once usage is steady, committed use discounts - per resource for Compute Engine, or spend-based for services such as Cloud Run and Cloud SQL - lower the rate in exchange for a one- or three-year commitment, and sustained-use discounts already apply automatically on eligible VM types.

How does Miracuves migrate an application to Google Cloud?

We build the target first, in Terraform, and run the application there against a copy of the data while the old system still serves users. The tools depend on what is moving:

  • Virtual machines lifted as they are with Migrate to Virtual Machines, when refactoring can wait
  • Applications repackaged as containers for Cloud Run or GKE when they are ready for it
  • MySQL and PostgreSQL replicated continuously into Cloud SQL or AlloyDB with Database Migration Service, so the final sync takes minutes
  • Files moved with Storage Transfer Service, and warehouse tables from Redshift or Teradata with the BigQuery Data Transfer Service
  • DNS TTLs lowered days ahead and a rehearsed rollback plan for the cutover window

Should you hire Google Cloud engineers or a Google Cloud development company?

Hiring works when someone on your side owns the architecture: approves each Terraform plan, decides who gets which IAM role, and answers for backups and the bill. Without that owner, Google Cloud projects drift - resources created by hand in the console, a service account key on a laptop, development and production sharing one project.

With Miracuves you contract with the company: a cloud architect, backend and DevOps engineers and QA work to a written scope with weekly demos, and every resource they create lives as code in your repository. After launch, the retainer from $2,299/month keeps the same team on your projects.

Technical Architecture

How Miracuves engineers structure GCP projects for production

These are the decisions our engineers make on every Google Cloud project - choices that decide whether the setup grows cleanly with the product or has to be pulled apart and rebuilt a year later.

  • 01

    Architecture - Organization, Folders and Projects

    Every workload lives in a project per environment, grouped under production and non-production folders, so organization policies and IAM are set once and inherited. Networking is a Shared VPC owned by a host project, with private IPs for Cloud SQL and AlloyDB. This is how Miracuves adds a new service or environment in a day without touching what already runs.

  • 02

    State - Terraform with a Cloud Storage Backend

    Terraform state sits in a versioned Cloud Storage bucket, which also locks it, so two people can never apply at once and any past state can be recovered. The most common problem we inherit on Google Cloud: resources created by hand in the console that nobody can reproduce. We import those into Terraform early, so the code describes what actually runs.

  • 03

    Performance - Concurrency, Warm Instances and Connection Limits

    Cloud Run sends many requests to one instance at a time, so we tune per-instance concurrency to each service instead of accepting the default, keep a minimum instance warm where cold starts would hurt, and cap maximum instances so a traffic spike cannot exhaust Cloud SQL connections. Every release is load-tested on staging with the production settings.

What most backend agencies get wrong

Everything built in the default VPC network. Development and production in one project. Owner role handed to every developer. Service account JSON keys committed to a repository. No budget alert until the invoice arrives. Miracuves has inherited each of these on Google Cloud, and fixing them later always costs more than starting the project correctly.

main.tf - Cloud Run service with Secret Manager and Cloud SQL
# Cloud Run service for the orders API# Applied with Terraform to your own Google Cloud projectresource "google_service_account" "api" {  account_id   = "orders-api"  display_name = "Orders API runtime identity"}resource "google_cloud_run_v2_service" "api" {  name     = "orders-api"  location = var.region  template {    service_account                  = google_service_account.api.email    max_instance_request_concurrency = 80    scaling {      min_instance_count = 1  # one warm instance, no cold start      max_instance_count = 20 # caps connections to Cloud SQL    }    volumes {      name = "cloudsql"      cloud_sql_instance {        instances = [google_sql_database_instance.main.connection_name]      }    }    containers {      image = "${var.region}-docker.pkg.dev/${var.project_id}/app/orders-api:${var.image_tag}"      env {        name = "DB_PASSWORD"        value_source {          secret_key_ref {            secret  = google_secret_manager_secret.db_password.secret_id            version = "latest"          }        }      }      volume_mounts {        name       = "cloudsql"        mount_path = "/cloudsql"      }    }  }  # grant access before the first revision starts  depends_on = [    google_project_iam_member.api_sql,    google_secret_manager_secret_iam_member.api_db,  ]}# The runtime identity may reach Cloud SQL and read one secret - nothing elseresource "google_project_iam_member" "api_sql" {  project = var.project_id  role    = "roles/cloudsql.client"  member  = "serviceAccount:${google_service_account.api.email}"}resource "google_secret_manager_secret_iam_member" "api_db" {  secret_id = google_secret_manager_secret.db_password.id  role      = "roles/secretmanager.secretAccessor"  member    = "serviceAccount:${google_service_account.api.email}"}
A Cloud Run service with its own runtime identity, one warm instance and a ceiling of 20 instances, so a traffic spike cannot run Cloud SQL out of connections. The database password is read from Secret Manager when an instance starts and never enters the repository, and because it is Terraform, the same service can be recreated in a new project or region from the code.

Our Service Models

Three ways Miracuves delivers your Google Cloud backend

Every Google Cloud engagement is a contract with Miracuves as a company - one team covering cloud architecture, backend and DevOps, one written delivery process, and one party accountable for the result. Pick the model that matches where your product is today.

Most Popular
Customer app
Partner app
Admin
Ready-made Platform · Fixed Price

Ready-made Platform Delivery

When a catalogue product fits, Miracuves launches one of its 90+ ready-made platforms under your brand - web app, admin panel and mobile apps - in 6 working days, on its own tested stack. It can be hosted in your own Google Cloud project; that setup is quoted as custom work. Source code fully yours.

  • Ready-made platform from $2,199 - fixed price, no surprises
  • 90+ solutions matched to your vertical
  • Branding, configuration, white-labelling applied
  • Admin panel included in every delivery
  • Full source code · NDA · 60-day support
Google Cloud orgProjectsComputeDataFolders · IAMCloud RunCloud SQL
Custom Development · Scoped

Custom Google Cloud Build

Miracuves designs and builds your Google Cloud setup from your specification - project layout, network, Cloud Run or GKE services, databases, BigQuery pipelines and the Terraform that defines them. Full team: cloud architect, backend engineer, DevOps engineer, QA and PM.

  • From $3,699, depending on the work - scoped and priced before development begins
  • Clean architecture designed specifically for your product
  • Weekly sprint demos - working software every sprint
  • Deployed into your own Google Cloud project - Terraform and pipeline in your repository
  • Full source code · IP 100% yours
Wk 1
Wk 2
Wk 3
Wk 4
Ongoing Retainer · Monthly

Ongoing Google Cloud Development

Miracuves works as your ongoing development partner - new features, releases, maintenance on a monthly retainer with weekly sprint demos.

  • From $2,299/month - cancel with 2 weeks notice
  • Dedicated Miracuves team assigned to your product
  • Direct communication - no account manager relay
  • Weekly sprint demos - deliverables every cycle
  • Scales up or down as your product evolves

Quality Standards

How Miracuves ensures every Google Cloud delivery meets production standard

Every Google Cloud project and every line of application code clears the same quality gates before handoff - reviewed plans, restored backups, alerts that fire - and none of them is optional on any project we ship.

  • Separate projects for dev, staging and production under folders - policies inherited, mistakes containedArchitecture
  • Terraform state in a versioned Cloud Storage bucket - every change goes through a reviewed planState
  • Load-tested on staging with production concurrency and min/max instance settingsPerformance
  • Backups restored and zone failover exercised in staging before go-liveQA
  • Cloud Build or GitHub Actions ships images through Artifact Registry with Workload Identity Federation - no keysDevOps
  • No secrets in source - Secret Manager, one service account per workload, key creation blocked by organization policySecurity
  • Production-ready - regional or multi-zone services, alerting policies and a billing budget in placeDelivery

Enforced QA Gates

Our 6 Continuous Delivery Gateways

Every service, Terraform module and pipeline has to clear all six gates below before the repository and your Google Cloud projects are handed back to you.

01

Code Review on Every Pull Request

A senior Miracuves engineer reviews each merge into your main branch. For infrastructure changes the review reads the Terraform plan line by line - what changes, what gets destroyed - and your production project is only touched once the plan is approved and the automated checks are green.

02

Automated Test Coverage Required

Unit tests for business logic, integration tests against a short-lived staging project, and terraform validate, tflint and policy checks on every infrastructure change. Coverage thresholds must pass before an image is promoted from staging to production.

03

Load-Tested at Production Settings - Not on Defaults

Cloud Run and GKE behave differently under load than on a quiet staging service: cold starts, per-instance concurrency and database connection limits only appear at volume. Miracuves load-tests with the production minimum and maximum instance settings and reads latency and errors in Cloud Monitoring and Cloud Trace; results from default settings are never accepted as the answer.

04

Handoff Package - Not Just a Repository

Source code, Terraform, pipeline definitions, an architecture diagram, environment setup guide, API documentation, a list of every service account and IAM role and where each secret lives (never the values), and the post-launch runbook. Access is handed over as IAM roles on your own groups - no shared passwords or key files.

05

Go-Live - Traffic Shifted in Steps, Rollback Ready

Miracuves runs the release: a new Cloud Run revision takes a small share of traffic before the rest, DNS and certificates move on an agreed date, and the previous revision stays ready for an instant rollback. Where you need HIPAA, PCI DSS or GDPR, we build to those requirements; audits and attestations belong to your organization.

06

Post-Launch Monitoring - 60-Day Active Support

Cloud Monitoring alerting policies, Error Reporting and a billing budget are live before launch and routed to your on-call channel. During the 60-day post-launch support window Miracuves watches errors, latency and spend, and acts before your users notice.

Technology Stack

The GCP stack Miracuves ships with

Chosen service by service for your workload, data and budget - not every product needs GKE, Spanner or Vertex AI.

CR
Cloud RunServerless containers · scale to zero
GK
GKE AutopilotManaged Kubernetes · per-pod billing
CF
Cloud Run functionsEvent handlers · formerly Cloud Functions
SQ
Cloud SQLManaged PostgreSQL · MySQL · SQL Server
AD
AlloyDBPostgreSQL-compatible · heavy read load
SP
SpannerHorizontal scale · strong consistency
FS
FirestoreDocuments · real-time listeners
BQ
BigQueryServerless data warehouse · SQL analytics
VX
Vertex AIGemini models · evaluation · pipelines
PS
Pub/SubMessaging · event fan-out
MS
MemorystoreManaged Redis and Valkey · caching
GS
Cloud StorageObjects · backups · static assets
TF
TerraformInfrastructure as code · reviewed plans
CB
Cloud Build / GitHub ActionsCI/CD · images in Artifact Registry
SM
Secret Manager / IAMSecrets · least-privilege access
CM
Cloud MonitoringMetrics · logs · alerts · traces

Our Process

From brief to deployed API - what happens and when

Every Google Cloud engagement runs on the same five steps, whether it is a small scoped job from $3,699 or a larger build or migration. At each step you know what our engineers are doing, which access and approvals we need from your side, and what is already live in your project. A ready-made platform follows its own 6-day schedule; Google Cloud work runs milestone by milestone with the checkpoints below.

  1. Step 01

    Brief & NDA

    Share your concept via WhatsApp. NDA signed same day. We ask 6 specific questions.

  2. Step 02

    Scope & Design

    Architecture, project and region layout, data model and a first estimate of the monthly Google Cloud bill agreed in writing before any code.

  3. Step 03

    Build & Demo

    Terraform repository and projects created. First service deployed to staging within 24h of scope sign-off. Weekly demos.

  4. Step 04

    QA & Load Test

    Load-tested on staging at production settings. Backup restore and failover checked, alerts proven to fire.

  5. Step 05

    Deploy & Handoff

    Traffic moved to production in your project. Full code, Terraform and docs delivered, our access reduced. 60 days support.

Same DayNDA turnaround
6 DaysReady-made platform delivery
24 HoursFirst deploy after scope sign-off
60 DaysPost-launch support

Six days is Miracuves build time, not calendar time

The six days are ours, and they do not run past six. What can add time sits on your side: developer account verification, merchant onboarding and compliance approvals are controlled by the app stores and your payment provider, not by us. We list exactly what you need ready on the first call so you can start those in parallel.

See what you provideFACT-005, audited quarterly

Transparent Pricing

What Google Cloud development costs at Miracuves

We publish our Google Cloud fees because the offers are defined: scoped work, a custom build or migration, or a retainer. No "contact us for pricing" pages, and no hidden fees after scope is agreed. Your Google Cloud usage is billed by Google to your own billing account, separate from our fee, and we estimate it with you before anything is deployed.

Ready-made Platform

$2,199 from

Fixed price · 6 working days · catalogue platform

  • Ready-made platform - web app, admin panel and mobile apps
  • Runs on its own stack; Google Cloud hosting quoted separately
  • Branding and white-label applied
  • Full source code on handoff
  • 60-day post-launch support
  • NDA protected from day one
Start a Clone Project
Most Requested

Custom Google Cloud Build

$3,699 from

Scoped before build · depends on the work · milestone billing

  • Full GCP team - engineer + DevOps + QA
  • Custom architecture for your spec
  • Weekly sprint demos - working software
  • Terraform, Cloud Build pipeline and go-live in your project
  • Full source code · complete IP transfer
  • Milestone billing - no pay before delivery
Get a Scope & Quote

Ongoing Development

$2,299 /mo

Monthly retainer · cancel with 2 weeks notice

  • Miracuves team assigned to your product
  • New features, releases, and maintenance
  • Weekly demos and sprint planning
  • Direct communication - no relay
  • Scales up or down as needed
  • All code remains 100% yours
Discuss Ongoing Work

Why Miracuves publishes pricesFounders who see our fee and the expected Google Cloud bill before kickoff make better architecture decisions. If your Google Cloud project needs a larger budget, Miracuves will explain exactly which part of the scope drives it - not simply charge more.

What affects GCP project cost at Miracuves

Ready-made platform pricing stays fixed when your scope matches the catalogue product. Fees for custom Google Cloud work scale with: how many services and environments you need (dev, staging, production, extra regions), whether we build new or migrate a running system and how much data has to move, the data layer (Cloud SQL, AlloyDB, Spanner or Firestore), BigQuery pipelines and Vertex AI features, compliance controls such as VPC Service Controls or customer-managed keys, and third-party integrations. Your Google Cloud bill is separate from our fee and paid by you directly to Google.

Typical Google Cloud budget ranges

  • Ready-made platform (web app, admin panel, mobile apps)from $2,1996 working days
  • Google Cloud workfrom $3,699, depending on the work
  • Custom Google Cloud build or migration$8,000-$25,0002-8 weeks depending on scope; larger scopes are quoted in writing before work starts
  • Ongoing retainerfrom $2,299/month for feature work and maintenance

Each quote is written down before you pay anything, and no invoice after kickoff carries an item the quote did not list.

Example engagement

What a typical GCP project looks like at Miracuves

An illustrative example of a typical project of this kind, with client details anonymized. Figures show what this kind of build targets, not a named client's results.

A Singapore-based food delivery startup needed its order dispatch API - multi-vendor webhooks, Stripe payment processing and an admin dashboard, across REST and WebSocket - running on Google Cloud in its own project before a seed investor demo 3 weeks away.

  1. 01

    The Challenge

    The existing MVP ran on a single rented server. It needed webhook support for 12 delivery partners, real-time driver tracking and a third-party logistics integration, on infrastructure that would hold up for the demo and the traffic after it.

  2. 02

    What Miracuves Delivered

    Built the Google Cloud setup in Terraform: Cloud Run services for the REST API and the WebSocket gateway, Pub/Sub topics fanning out partner webhooks, Memorystore for live driver positions, Cloud SQL for PostgreSQL for orders, and the logistics provider's API behind a retrying queue.

  3. 03

    Outcome

    Delivered in week 3. REST API and WebSocket service running on Cloud Run in the client's own project, with budgets and alerting set. Admin dashboard, full source code, Terraform and load test report all included. Client raised seed funding with the working product.

3 WeeksFull delivery
REST + WSBoth APIs live
100%Source owned
View All Case Studies
Project Brief
  • Built onCloud Run · Pub/Sub · Cloud SQL
  • Delivery timeline3 weeks
  • Platforms deliveredREST + WebSocket + Admin
  • Key integrationsStripe · Logistics · Webhooks
  • Card dataHeld by Stripe, not our servers
  • Source code100% client-owned
50K+Daily API calls
12Partner webhooks via Pub/Sub
60dSupport included

Client Reviews

What clients say about building with Miracuves

Named clients, in their own words, on products whose infrastructure had to hold up - a VPN with server orchestration, a multi-tenant alerting platform, and a live-video service on launch nights. Each card names what it was built on; read every testimonial on our client testimonials page.

Client testimonial
"Building a consumer VPN is less about the tunnel and more about the app store, the subscriptions and the server management. Miracuves handled the client apps, the server orchestration and the billing layer, and we brought the network. Delivered inside a month and approved on both stores without a rejection cycle."
DP
Dhiru PriyadarshiFounder, Maxx
Consumer VPN with server orchestration and subscription billing
Client testimonial
"Multi-tenant structure, alert pipelines and agent collectors were the slow part and they already existed. We added our scoring engine, the playbook library and billing. First customers were onboarded within weeks and the dashboard is now a sales tool rather than an internal screen."
RK
Rohit KhannaFounder & CEO, Server ProGuard Inc
Multi-tenant security dashboard with alert pipelines and agent collectors, built on MXSecurity Dashboard
Client testimonial
"Live video, creator onboarding and tipping came ready. We added the drop calendar, artist royalty logic and our moderation layer. It has held up on launch nights without a stumble, and a from-scratch build would have been six months longer at twice the cost."
TS
Todd ScharamVP Digital, PAS Systems Corp
Live-video platform for independent artists that holds up on launch nights
5.0 / 5.0Clutch average · 14 reviews
4.8 / 5.0Google average rating
Top DeveloperClutch recognition · 2024-2025
Read All Reviews

Why Miracuves

Six places to check us before you ever call us

Each one is either run by someone else or open to anyone. Check them in any order; the whole list takes about a minute.

Why clients choose Miracuves

Three promises we would stake the company on

Every promise on this site rests on these three. Each one is something you can check, not something you have to take on trust.

  • 01People you can name

    Our leadership is public, with real LinkedIn profiles, not a stock-photo team page. A named team works your build and sends you progress on WhatsApp every working day.

    Meet the leadership
  • 02Proof over promises

    Every number we publish, pricing, timelines, project counts, is defined and sourced on a public facts ledger. If we can't back a claim, we don't make it.

    Read the facts ledger
  • 03A process with a deadline

    Ready-made platforms go from kickoff to live deployment in 6 working days, guaranteed: miss it for reasons on our side and we work free until launch. Custom builds get a fixed quote after a free feasibility study.

    Get a feasibility study

Frequently Asked

Questions about Google Cloud development at Miracuves

Something not covered here? Ask on WhatsApp and you will usually have an answer within two hours.

Ask us directly
Can Google Cloud backends handle enterprise-scale traffic?

Yes, when it is designed for it. Cloud Run and GKE add instances automatically as load grows, Cloud Load Balancing spreads traffic across zones and regions, and AlloyDB or Spanner take over when one Cloud SQL instance is no longer enough. In practice the limit is usually database connections and hot rows rather than Google's capacity, so we load-test on staging with production settings before launch and design for multi-zone failover. Google's own SLAs apply to the managed services.

How much does Google Cloud development cost at Miracuves?

It depends on the offer. Google Cloud work starts from $3,699, depending on the work. A custom Google Cloud build or migration costs $8,000-$25,000 over 2-8 weeks depending on scope - the number of services and environments, how much data has to move, the data layer, BigQuery and Vertex AI features, compliance controls and integrations decide where it lands; larger scopes are quoted in writing before work starts. An ongoing retainer for feature work and maintenance starts from $2,299/month. If a catalogue product fits, a ready-made platform with web app, admin panel and mobile apps starts from $2,199 and goes live in 6 working days. Your Google Cloud bill is separate from our fee and paid by you directly to Google. Every quote is written before payment, with no surprise invoices after kickoff.

Does Miracuves deliver the full API source code?

Yes - completely. Miracuves delivers the application repository with its full commit history, the Terraform for every Google Cloud resource, the Cloud Build or GitHub Actions pipelines, API documentation and the runbook. The organization, projects and billing account are already yours, and access is transferred as IAM roles, never as shared passwords or key files. Zero lock-in: your own engineers or another company can carry on the morning after handoff.

How fast can a Google Cloud project realistically be delivered?

Scoped Google Cloud work starts from $3,699, depending on the work, and custom builds and migrations take 2-8 weeks depending on scope; larger scopes are quoted in writing before work starts. If one of our 90+ catalogue products fits, the ready-made platform - web app, admin panel and mobile apps - goes live in 6 working days on its own stack. Every timeline is agreed in writing before any payment is requested.

Google Cloud vs AWS or Azure - which does Miracuves recommend?

Google Cloud when the product is built around its data: BigQuery analytics, Vertex AI and Gemini features, Cloud Run services that scale to zero, or an app already on Firebase. AWS when your team and data are already there or you need its wider service catalogue; Azure when your company runs on Microsoft 365, Entra ID and .NET. We put the recommendation and the reasons in writing before you commit.

What is included in the admin dashboard with every delivery?

The admin panel ships with our ready-made platforms: user management, content, payments and settings, as a web app that works in any browser. Custom Google Cloud work does not include a product admin panel by default. You get the Google Cloud console through IAM roles, Cloud Monitoring dashboards for health and spend, and runbooks; an admin web app for your own product can be scoped into the build.

Does Miracuves handle production deployment and monitoring?

Yes, as part of every delivery. Miracuves builds container images in Cloud Build or GitHub Actions, stores them in Artifact Registry, deploys to Cloud Run or GKE in your project, and sets up managed certificates, Cloud Monitoring alerting and Error Reporting. Production go-live happens within the same engagement as the build, and the dashboards and alerts stay with you after handoff.

What happens after the API is delivered if there are bugs?

Every Google Cloud delivery includes 60 days of post-launch technical support, and bugs in the code or Terraform we delivered are fixed at no extra cost during that window. New services or features beyond the agreed scope are quoted separately, and the monthly retainer from $2,299/month covers ongoing changes after that.

How does Miracuves handle NDA and confidentiality?

Miracuves signs a mutual NDA before you share any project details, covering your architecture, data, business logic and IP. An IP assignment agreement confirming that 100% of the code and Terraform we write transfers to you is signed at project start, not at the end, and your Google Cloud projects never leave your organization.

Who owns the Google Cloud organization, projects and billing account?

You do. The Google Cloud organization, its projects and the Cloud Billing account are created in your company's name, usually on your own Google Workspace or Cloud Identity domain, and Google invoices you directly. Miracuves works through IAM roles on groups you control and removes its access at handoff. The Terraform, pipelines, scripts and application code we write are 100% yours. Managed services such as Cloud SQL, BigQuery and Vertex AI remain Google's services, running under your account.

Can you build to HIPAA, PCI DSS or GDPR requirements on Google Cloud?

Yes. Google secures the underlying infrastructure and publishes its own compliance reports; how your projects are configured is your side of the shared responsibility model. We build to the controls these frameworks require - customer-managed encryption keys where needed, VPC Service Controls around sensitive data, least-privilege IAM, Cloud Audit Logs retained, backups with restore tests - and for HIPAA we keep protected health information in services covered by the Business Associate Agreement you accept with Google. Assured Workloads can hold data to chosen regions. Audits and attestations belong to your organization.

Can Miracuves take over a Google Cloud project someone else set up?

Yes. We start with a written review: who holds Owner roles, which service account keys exist, what runs in the default network, which charges on the bill nobody can explain, and what is not in code. Then we bring the running resources under Terraform with import blocks, rotate or remove keys, and add budgets, alerting and a staging project. The review and the fixes are quoted before work starts: custom Google Cloud work runs 2-8 weeks at $8,000-$25,000 depending on scope, and smaller scopes start from $3,699.

Get Started

Ready to build your Google Cloud backend with Miracuves?

Tell Miracuves what you want to run on Google Cloud. We will come back with the architecture we would use, the service model that fits, the timeline and an estimate of your monthly Google bill - in writing, before you commit to anything.

2,400+APIs delivered
6 DaysReady-made platform
100%Source code yours
Same DayNDA turnaround
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Page reviewed by the Miracuves Google Cloud Development Team · Last updated May 2026 · Clutch & Google Reviews

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Miracuves is an independent software development company. We are not affiliated with, connected to, sponsored by, or endorsed by any of the brands or platforms named on this page.

Why these names

Names of the form “Brand Clone” are used descriptively. It is how the software industry refers to building a platform with functionality comparable to a known service, and how clients search for it.

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