Production Infrastructure That Grows With You

Independent services, fault isolation, and real observability — delivered as a one-time project. You own it, you deploy it, it scales when you need it to.

Foundation

Deploy independently, break nothing

$15,000Save $5,100
$9,900one-time
  • 6-8 independent services
  • Docker containerization
  • Nginx API Gateway
  • Service discovery
  • PostgreSQL / MariaDB
  • Valkey caching (Redis-compatible)
  • Kafka message queue
  • Prometheus + Grafana monitoring
  • CI/CD pipeline (GitHub Actions)
  • Complete documentation
  • 90-day post-delivery support
Get Started
Most Popular

Growth

Scale what's hot, leave the rest alone

$25,900one-time
  • 9-11 independent services
  • Docker + Kubernetes orchestration
  • Nginx API Gateway with advanced routing
  • Cilium + Hubble (eBPF networking & observability)
  • PostgreSQL / MariaDB
  • Valkey with Sentinel (Redis-compatible)
  • Kafka message queue
  • Prometheus + Grafana monitoring
  • CI/CD pipeline with K8s deployments
  • Comprehensive documentation
  • Dedicated support channel
  • 120-day post-delivery support
Get Started

Production

Full platform engineering, delivered

from$30,000

Scoped to your project · every build is custom at this level

  • 12-15 independent services
  • Full Kubernetes + Helm charts
  • Cilium Gateway API (native K8s routing)
  • Cilium (eBPF networking + network policy)
  • Hubble (network flow observability)
  • REST APIs with Swagger documentation
  • PostgreSQL / MariaDB
  • Valkey Cluster (Redis-compatible)
  • Kafka message queue
  • Prometheus + Grafana (metrics & dashboards)
  • Loki (log aggregation)
  • Tempo (distributed tracing)
  • CI/CD pipeline + GitOps
  • Comprehensive documentation
  • 150-day post-delivery support
Let's Talk
The Real Cost of "It Works for Now"

The 2 AM Wake-Up Call

Nobody dreams about microservices. But plenty of founders have nightmares about the monolith that just went down. If any of these sound familiar, you already know why you're here.

A Friday deploy takes down the entire product. Every user is affected. You roll back, but it takes 40 minutes. The Slack channel is on fire.

A report query locks the orders table. Customers can't checkout. Revenue stops for two hours while you hunt down which service is running the bad query — except everything runs in the same process.

Black Friday traffic hits your product catalog. You scale the whole app 20× to handle it — checkout, admin, notifications, everything — because there's no way to scale just the part that's hot. Your cloud bill triples.

A new developer pushes a memory leak in the notification module. It takes down auth, payments, and the admin panel. You can't deploy a fix without redeploying everything. Again.

vs.

A Sane Production Environment

What it feels like when your infrastructure is built to handle reality — not just the happy path.

Fault isolation

A failing service restarts in 30 seconds. Everything else keeps running. Your users don't notice.

Independent deploys

Ship the catalog service without touching auth. Your team moves faster because they stop waiting for each other.

Targeted scaling

Scale the hot service, leave the rest alone. Pay for what you actually use, not 20× of everything.

Real observability

Prometheus, Grafana, distributed tracing. You know exactly what's happening, where, and why — before your users tell you.

One-time delivery

You own the infrastructure. No monthly vendor lock-in, no surprise bills. Deploy it on your cloud, your terms.

Hiring a platform engineer to build this? $150K–$200K/year + months of trial and error. This is a flat fee, delivered in weeks.

Real Scenarios

Does This Sound Like You?

Five real situations where production infrastructure makes the difference. If you see yourself here, this plan was built for you.

Funded Startup

You raised a round and your MVP backend is hitting its limits

You have a working product, real users, and a monolith built by contractors that's starting to crack — slow deploys, DB contention, everything coupled. You don't have a CTO or platform team yet, but you need the infrastructure foundation before you hire engineers to build on top of it.

The outcome: $9,900–$25,900 is a fraction of your first platform hire's salary, and it gets you 3–6 months ahead. Your next engineers inherit a clean, deployable architecture instead of a growing mess.

Agency / Dev Shop

You landed a contract that needs infrastructure beyond your team's expertise

Your 3–5 person agency builds great apps and business logic, but the client needs Kubernetes, service isolation, and CI/CD pipelines — and nobody on the team has that experience. You need someone to deliver the infrastructure so your team can focus on what they do best.

The outcome: Subcontract the infrastructure, mark it up to the client, and deliver a product that's architecturally sound. Your client gets production-grade infrastructure; you keep your reputation.

Fintech / Healthtech

An auditor requires physical service isolation — not because of traffic, but compliance

Your payment processing service needs to be separated from user management. Your health data pipeline can't share a runtime with the public API. The requirement isn't scale — it's that a compliance framework demands service boundaries with independent deployments and separate data stores.

The outcome: Service isolation as a compliance requirement is one of the strongest reasons to move beyond a monolith. We've seen this pattern in fintech and healthtech — the architecture pays for itself at the first audit.

International Startup

You need world-class infrastructure but a US platform engineer costs more than this entire plan

Your engineering team is growing fast, your product has real traction, and you need Docker, Kubernetes, and proper observability. Hiring a DevOps engineer in the US would cost $150K–$200K/year. Even in your market, a senior platform engineer is expensive and hard to find.

The outcome: A one-time delivery of production infrastructure at $9,900–$25,900 gives your team the foundation without the ongoing salary. Your engineers build features on top of it — they don't need to become Kubernetes experts.

Corporate Innovation

Your internal team needs modern infrastructure but IT procurement takes 6 months

You're building a proof-of-concept or internal tool on a modern stack, but provisioning a Kubernetes cluster through corporate IT means months of tickets and approvals. A flat-rate delivery with no ongoing vendor contract is easier to expense than a monthly SaaS.

The outcome: Get production infrastructure delivered as a project — fits within a single purchase order, no recurring vendor relationship to justify, and your team is unblocked in weeks instead of quarters.

Async-First Communication

Better Communication, Better Results

We use async-first communication (email, detailed documentation, video recordings) because it's better for both of us. No rushed meetings, no forgotten details.

On Your Schedule

Review proposals and updates when it suits you. No pressure to respond immediately.

Everything Documented

All decisions and changes are documented in writing. No misunderstandings or forgotten conversations.

Thoughtful Responses

Get well-researched, detailed answers instead of rushed meeting talk.

Clear Communication

Email-based workflow with optional screen recordings for complex topics.

Preferred by technical founders, busy entrepreneurs, and anyone who values clear, documented communication over rushed video calls.

When Does Your Product Need This?

When a Single Backend Starts Holding You Back

Independent services aren't for everyone. If you have fewer than 6 engineers and haven't hit clear scaling bottlenecks, a well-structured monolith is still the right answer. Here's when that changes.

Your team outgrew the codebase

The most reliable indicator — not traffic, not module count. When 6–8 engineers commit to the same repo simultaneously, merge conflicts become daily friction, CI/CD becomes a queue everyone waits in, and deploying requires cross-team coordination. Conway's Law is real: your architecture will mirror your team structure whether you plan for it or not.

6–8 engineers on one repois the real inflection point

Your team speaks different languages

A monolith locks every engineer into one runtime. With microservices, each service chooses the best tool: ML recommendation engine in Python (PyTorch/scikit-learn), auth service in Rust (10 MB memory footprint vs ~150 MB in Node.js), core API in Node.js. Uber runs Go for dispatch, Python for ML pricing, Java for trip management — in production, at scale.

10 MB vs 150 MBRust auth vs Node.js equivalent

One endpoint shouldn't cost you 20× everywhere

When your product catalog gets 20× normal traffic on a sale day, a monolith forces you to scale the entire application. Spin up 20 replicas of a 500 MB app and you're allocating 10 GB of RAM — for checkout, for admin, for everything. Scale only the catalog microservice (≈60 MB × 20 replicas = 1.2 GB) and the rest run at normal capacity. Netflix reported ~40% infrastructure cost reduction from this alone.

~8× RAM efficiencyon a single hot service during spikes

One bad deploy shouldn't take down everything

In a monolith, a memory leak or unhandled exception in any module degrades the entire application. A bad deploy means a full rollback — 15 to 45 minutes of degraded service for every user. With microservices and Kubernetes health checks, a failing service is detected in under 30 seconds, restarted in isolation, and circuit breakers prevent the failure from propagating. Everything else keeps running.

30 sec vs 15–45 minfault recovery time

One slow query shouldn't block checkout

Shared databases in a monolith mean one poorly optimized query — a report aggregation doing a full table scan, a bulk export — can lock rows and add latency to completely unrelated operations. A report running for 2 hours on the orders table shouldn't slow down a customer trying to pay. Separate databases per service provide complete isolation. Failures stay contained.

Full isolationper-service database ownership

You can't upgrade a monolith one piece at a time

A monolith built in 2018 is largely stuck with 2018 choices. Upgrading the runtime or framework means touching everything at once — a months-long project with high risk. With microservices, the auth service migrates to the latest Node.js LTS first; once stable, the next service follows. You can even rewrite a single service in a new language without touching anything else. Amazon went from 2-week deployment cycles to 50+ deploys per day across services after this transition.

50+ deploys/dayvs 1–4/week with a shared monolith

Side by Side

MetricMonolithMicroservices
Deploy frequency (10+ devs)1–4 per week (coordinated)10–50+ per day per service
Build + test time at scale20–40 min (full suite)2–5 min per service
Fault blast radiusEntire applicationIsolated service only
Recovery after bad deploy15–45 min full rollback30–120 sec (K8s restart)
Scaling cost (uneven load)Scale all modules equallyScale only the hot service
Runtime flexibilityOne language, one runtimePer-service language choice
Operational complexityLow — one processHigh — requires K8s, observability
Right for early-stageYes — move fast, iterateNo — premature at pre-PMF

Last two rows intentionally favor the monolith — microservices have real costs.

The distributed monolith trap

The worst outcome in software architecture: services that share a database, depend on each other synchronously, or require coordinated deployments. You get the operational complexity of microservices with none of the benefits. It happens when teams split a monolith before its bounded contexts are clear. The prerequisite for microservices is a well-understood monolith — if you can't draw clean boundaries in your current system, splitting it will make things worse, not better. We won't let you go down that path.

Containerization

Docker

Container platform

Kubernetes

Container orchestration (Growth+)

Docker Compose

Multi-container apps

Microservices

Node.js Services

Scalable service architecture

API Gateway

Unified API entry point

Service Discovery

Dynamic service location

Service Mesh

Inter-service communication (Growth+)

Databases

PostgreSQL

Advanced relational database

MariaDB

Reliable relational database

Redis

Caching & sessions

Multi-DB Strategy

Database per service (Pro)

Messaging

Message Queues

Async task processing

Event-driven

Decoupled service communication (Pro)

Infrastructure

CI/CD Pipeline

Automated deployments

Monitoring

Complete observability

Auto-scaling

Dynamic resource management

Who You Are

  • Product has real traction and is outgrowing its first backend
  • Deploys are getting slower or riskier as the codebase grows
  • Different parts of the system need to scale independently
  • Want production-grade infrastructure without hiring a platform team
  • Ready to invest in the foundation for the next stage of growth

Business Types

  • Funded startups scaling past their MVP backend
  • Agencies delivering infrastructure above their in-house expertise
  • Companies needing service isolation for compliance (fintech, healthtech)
  • International startups needing world-class infra at a fraction of US hiring costs
  • Corporate innovation teams building on modern infrastructure

Challenges We Solve

  • One bad deploy takes down the whole product
  • Can't scale the hot service without scaling everything
  • Slow CI/CD because everything runs as one pipeline
  • Don't have Kubernetes or DevOps expertise in-house
  • Need to ship faster without stepping on each other's code

Your Goals

  • Deploy independently, break nothing
  • Fault isolation — failures stay contained
  • Scale only what needs scaling
  • Production-grade observability from day one
  • Own the infrastructure, deploy anywhere
  • Foundation that grows with the product

Sound like you? We're eager to be part of your journey and help bring your vision to life. Let's discuss your specific needs.

~/project
~tree -L 3
microservices-platform///

Microservices ecosystem

services///

Individual microservices (3-20 based on tier)

infrastructure///

Infrastructure as code

shared///

Shared libraries

docs///

Documentation

docker-compose.yml//

Local development setup

README.md//

Getting started guide

Complete Package Includes

Microservices setup
Comprehensive README.md
Environment configuration
Deployment documentation
Code comments & docs
Git repository ready

Ready to Start Your Project?

Describe your idea — we'll tell you which plan fits and what to expect.