EgyKode Pilot
EgyKode/Pilot
The Intelligent Cloud DevOps Compiler

FROM CODE TO CLOUD.

Give Pilot your code. It figures out the cloud.

It understands your application, your requirements, and your budget — then builds the infrastructure to match.

See how it works
pilot://compiler/session-042· Example
LOCAL SCAN
01 · LOCAL FOLDER OR GIT REPO
📁 ~/projects/shop-microservices
READ-ONLY IN-PLACE SCAN
Django / Python
PostgreSQL
Celery Worker
Dockerfile
Rule-based analysis on your machineReads local files in place...
SCENE 02 · THE COGNITIVE REDUCTION

Cloud shouldn't start with infrastructure.

The traditional cloud journey forces developers to become full-time cloud architects just to run their application. Pilot inverts this paradigm by starting where you live: in your code.

The Pilot Paradigm: Application-First Architecture
Cognitive Overhead: ELIMINATED
WHAT YOU PROVIDE
Source Code + Intent
Repository · Target SLA · Budget Ceiling
Pilot Compiler Engine
Deterministic Analysis · Sizing Rules · Invariant Validation
WHAT COMES OUT
Production DevOps Architecture
Costed · Terraform · K8s · Verified PR
Your application already contains the cues for what it needs. Pilot compiles that intent directly into cloud infrastructure.Code → Pilot
THE CANONICAL REASONING MODEL

The Five Questions EgyKode Pilot Answers

QUESTION 01LOCAL-FIRST ANALYSIS
UNDERSTAND THE APPLICATION

What did I build?

Pilot analyzes the source code and deployment evidence to understand the application as real production workloads — identifying languages, frameworks, runtimes, services, dependencies, ports, health checks, build commands, background jobs, databases, queues, storage, and existing DevOps configuration.

Result
A verified picture of what the application actually is.
QUESTION 02PRODUCTION REQUIREMENTS
UNDERSTAND THE INTENT

What does it need to handle in production?

Pilot turns business and production requirements into explicit constraints — including expected traffic, concurrency, availability, latency, growth, budget, security, data requirements, disaster recovery, operational preferences, cloud, and region.

Result
A measurable definition of what the architecture must achieve.
QUESTION 03FEASIBILITY + OPTIMIZATION
FIND THE BEST-FIT ARCHITECTURE

What architecture should run it?

Pilot evaluates feasible architecture compositions against the application’s workloads, requirements, provider capabilities, organizational policies, and cost — eliminating impossible options first, then comparing the remaining choices across cost, performance, availability, security, scalability, and operational complexity.

Result
The best feasible architecture for the user’s actual requirements and budget — with the trade-offs and reasoning visible.
QUESTION 04CANONICAL BLUEPRINT + GENERATION
TURN THE DECISION INTO A SYSTEM

What exactly needs to exist?

Pilot converts the selected architecture into a canonical blueprint, then generates the infrastructure and operational artifacts required by that decision — including compute, networking, storage, databases, IAM, secrets, containers, Kubernetes or ECS resources, Terraform, CI/CD, security, observability, backups, documentation, and runtime configuration.

Result
One architecture decision translated into a complete, traceable Cloud DevOps project.
QUESTION 05VALIDATION + HUMAN CONTROL
PROVE IT BEFORE DELIVERY

Can I trust what Pilot created?

Pilot validates the exact reviewed project for structural correctness, infrastructure consistency, security, cross-file dependencies, cost/component alignment, and available external tool checks — then presents the changes for review and keeps delivery under explicit human approval.

Result
A validated, reviewable project that is ready to deliver — without hidden changes or unverified claims.
SCENE 03 · THE MAGIC MOMENT

Point to a local folder or Git repo. Watch Pilot understand it.

Pilot executes deterministic static analysis directly on your machine. Open any local project directory from your disk or clone a Git repo — Pilot parses your code in place, changes nothing, and sends nothing.

Source:
DIR:~/projects/shop-microservices
pilot://local://~/projects/shop-microservices· Example
LOCAL FOLDER SCAN · IN-PLACE
DISCOVERED WORKLOADS (3)CONFIDENCE: 100%
auth-service
confirmed
Python 3.12 (FastAPI)Port 8000
web-frontend
confirmed
TypeScript / React 18 + VitePort 443
roadmap-service
confirmed
Java 21 (Spring Boot 3.2)Port 8080
IN-PLACE LOCAL FILE EVIDENCE

auth-service

EVIDENCE FOUND
RUNTIME PORT:8000
RESOURCE ALLOCATION0.5 vCPU · 1024 MB
SCALING INVARIANT2 - 6 replicas (CPU > 70%)
Direct Local File Proof:
FILE: services/auth/main.py (Line 14)
↳ app = FastAPI(title="AuthService", version="2.1.0")
Discovered Resource Dependencies:
✓ PostgreSQL (User Store)✓ Redis (Session Tokens)✓ AWS KMS (JWT Signing)
The scan runs on your machine; nothing is sentRead-only local disk scan
SCENE 04 · TOPOLOGICAL INTELLIGENCE

Pilot understands what your application is.

Pilot does not treat your codebase as one giant monolithic container. Whether pointed at a local folder on disk or a cloned Git repository, it recognizes distinct workloads, runtime contracts, background workers, and databases — matching each to its optimal cloud archetype.

ARCHETYPE SPECIFICATION

High-Concurrency REST / gRPC API

CONFIRMED
RECOGNIZED RUNTIME SIGNALS
FastAPI / UvicornExpress / NestJSGo Gin / Fiber
DERIVED RUNTIME CONTRACT

Stateless HTTP listeners with health probes on /healthz or /actuator

VERIFIED REPOSITORY EVIDENCE
FastAPI(title=...) in main.py, listening on PORT 8000
Pilot anchors every cloud recommendation to concrete source code artifacts, eliminating guesswork and phantom infrastructure.
Architectural Resolution:100% Deterministic Rule Match
SCENE 05 · BUSINESS INTENT

Tell Pilot what matters.

Pilot transforms business objectives and budgetary reality into strict architectural constraints. Infrastructure is chosen because your business requires it — not because a technology is trending.

BUSINESS REQUIREMENTS INPUT
$150 / mo
$50/mo (Lean)$400/mo (Scale)
10,000 Users
2,00050,000+
COMPILED ARCHITECTURAL CONSTRAINTSDYNAMIC RULES ACTIVE
Resilience Boundary

Dual-AZ deployment behind ALB satisfies 99.95% SLA without idle standby waste.

Budget Gate: $150/mo Cap

Fargate Spot + Serverless v2 DB selected to preserve healthy 30% financial headroom.

Capacity Sizing (10,000 users)

Base allocation: 2 container replicas per service (0.5 vCPU / 1024 MB) with auto-scaling trigger.

Requirements compiled:Zero Guesswork Architecture
SCENE 06 · THE ARCHITECTURAL ANSWER

The architecture is the answer.

Pilot formulates 3 distinct cloud candidates for your workloads. Each option is scored against your business constraints, accompanied by an explicit record of why it was chosen and what lost.

Cost-Optimized Topology$82/mo

Minimalist container deployment for lean traffic and predictable budgets.

SLA:99.9%
Compute:AWS ECS Fargate (Spot-assisted savings)
Complexity:Very
Recommended Fit
Balanced Production Architecture$104/mo

Enterprise-grade Multi-AZ resiliency with strict budget boundary alignment.

SLA:99.95%
Compute:AWS ECS Fargate (Dual-AZ redundant tasks)
Complexity:Low-Medium
High-Performance & High-Availability$143/mo

Maximum throughput and sub-10ms response times for mission-critical scale.

SLA:99.99%
Compute:Dedicated ECS Fargate with Provisioned Concurrency
Complexity:Medium
WHY THIS OPTIONOPTIMAL FEASIBLE ANSWER

Balanced Production Architecture — $104/mo

Compute TierAWS ECS Fargate (Dual-AZ redundant tasks)
Database TierAmazon RDS PostgreSQL Multi-AZ
Caching / SessionAmazon ElastiCache Serverless (Redis compatible)
Ingress & EdgeAWS ALB + CloudFront Global CDN + WAF Managed Rules

Why This Candidate Was Chosen

  • Workload Fit:Directly mirrors the workloads and runtime contracts the scan found.
  • Requirements Match:Exceeds the $150 budget requirement ($104.32/mo) while delivering 99.95% Multi-AZ SLA.
  • Budget Optimization:Right-sized compute allocation with zero over-provisioning and serverless scaling bounds.

Rejected Alternatives & Trade-Offs

  • Rejected Single-AZ RDS: Fails disaster recovery requirement (< 1h RPO / RTO during AZ outage).
  • Rejected Kubernetes: Adds unwarranted cognitive overhead for a 3-service polyglot architecture.
SCENE 07 · COST AWARE BY DESIGN

Architecture without the surprise bill.

Pilot treats budget as a hard architectural constraint. Unknown infrastructure costs are never assumed as zero, and every component exposes its pricing provenance.

TOTAL ESTIMATED MONTHLY SPEND
$104.32USD / month
Scale Simulator:
Compute$48.00
AWS ECS Fargate (Dual-AZ)
Database$29.40
Amazon RDS PostgreSQL
Storage$8.92
Amazon S3 + CloudFront Storage
Networking$6.00
Application Load Balancer & Data Transfer
Observability$5.50
CloudWatch Logs & Metrics Retention
Events & Queue$6.50
Amazon SQS / EventBridge Bus
Baseline: 3 workloads distributed over Dual-AZ ECS Fargate + RDS PostgreSQL. Within $150 Budget Ceiling
* Illustrative product visualization derived from AWS US-East-1 pricing indices. Pilot prices from a captured AWS rate snapshot, or live AWS prices when you refresh them.
SCENE 08 · SIMULATION ENGINE

What if your requirements change?

Explore architectural counterfactuals before writing a single line of IaC. Pilot re-evaluates capacity, component topologies, costs, and feasibility in real time.

SIMULATION CONTROLS
Traffic Surge1× Baseline
1× (Normal)5× (Peak Concurrency)
Simulated Budget Cap$150/mo
$80$350
Availability Target
Runtime Orchestrator
RE-EVALUATED ARCHITECTURAL SPEC
$104/ month
RESULTING TOPOLOGY
Balanced Multi-AZ ECS Fargate
ALLOCATED REPLICAS2 Tasks / Service
DATA STRATEGYRDS PostgreSQL Multi-AZ
Architecture fits strictly within your simulated $150/mo budget envelope.
Dynamic simulation:Continuous Invariant Checking
SCENE 09 · THE CANONICAL BLUEPRINT

One architecture. Every artifact aligned.

Pilot synthesizes code evidence, business requirements, and budget constraints into a single authoritative Canonical Blueprint. All downstream infrastructure files are mathematically aligned.

SYNTHESIZED INPUTS
✓ Source Code Evidence
✓ Business SLA & RPO
✓ $150/mo Budget Limit
CANONICAL BLUEPRINT SPEC

Unified System Model

A typed, deterministic representation of the entire cloud system. Eliminates conflicting configurations between IaC, CI/CD, and security roles.

ALIGNED PROJECTIONS
Terraform IaCterraform/main.tf
Kubernetes Specsk8s/deployment.yaml
IAM Least Privilegesecurity/iam.json
CI/CD Workflow.github/workflows/deploy.yml
Terraform IaC:Dual-AZ VPC, ECS Fargate modules and an RDS PostgreSQL database declared in Terraform.
DERIVED FROM BLUEPRINT
SCENE 10 · THE COMPILER

Generated like software. Compiled like code.

Pilot is not an LLM hallucinating code snippets. It is a deterministic compiler that assembles your complete DevOps repository through six rigorous stages.

01 · ANALYZING
Workloads Discovered
02 · DESIGNING
Dual-AZ Architecture
03 · COMPOSING
Cloud Resources Mapped
04 · GENERATING
IaC & Specs Written
05 · SECURING
Zero-Wildcard IAM
06 · VALIDATING
7 Invariants Passed
Generation Plan:6 files compiled·100% Invariants Passed
pilot://output/terraform/main.tf· Example
IaC RootUTF-8 · Ready for Review
GENERATED REPOSITORY TREE
HCLterraform/main.tf
1# Generated by EgyKode Pilot — The Intelligent Cloud DevOps Compiler
2# Architecture: Balanced Production (Dual-AZ ECS Fargate + RDS PostgreSQL)
3# Budget Constraint: $150.00/mo | Estimated Monthly: $104.32/mo
4
5▾terraform {
6 required_version = ">= 1.6.0"
7▾ required_providers {
8▾ aws = {
9 source = "hashicorp/aws"
10 version = "~> 5.30"
11 }
12 }
13}
14
15▾provider "aws" {
16 region = var.aws_region
17▾ default_tags {
18▾ tags = {
19 ManagedBy = "EgyKode-Pilot"
20 Environment = "production"
21 Project = "shop-microservices"
22 }
23 }
24}
25
26▾module "vpc" {
27 source = "./modules/vpc"
28 cidr_block = "10.0.0.0/16"
29 availability_zones = ["us-east-1a", "us-east-1b"]
30 enable_nat_gateway = true
31 single_nat_gateway = true # Optimized for budget constraint
32}
33
34▾module "ecs_cluster" {
35 source = "./modules/ecs"
36 vpc_id = module.vpc.vpc_id
37 subnet_ids = module.vpc.private_subnets
38 cluster_name = "shop-prod-cluster"
39}
Clean
39 lineshcl
SCENE 11 · BROWNFIELD ADOPTION

Already have DevOps? Keep what works.

Pilot respects your existing codebase. It scans existing Dockerfiles, CI pipelines, and Terraform configurations — integrating with your current tooling rather than demanding a rewrite.

PRESERVE MODE

Maintain Multi-Stage Dockerfiles & Existing Scripts

Zero Silent Deletions

If your repository already has tuned Docker builds or custom start scripts, Pilot preserves them verbatim. It never needlessly replaces working engineering assets.

Enterprise Rule Invariant:Human Consent Mandatory for Every Modification
SCENE 12 · DETERMINISTIC SAFETY

When Pilot doesn't know, it doesn't guess.

Generative AI tools hallucinate broken startup commands and dangerous security flags. Pilot follows strict deterministic safety: it identifies what is missing, explains why it matters, and asks for one human decision.

SAFETY INQUIRY: 1 DECISION REQUIRED
RESOLVED & SAFE
KNOWN WITH 100% PROOF
Spring Boot 3.2 on JVM 21
Target Port 8080 declared in Dockerfile
Multi-stage build generates /app/roadmap-service.jar
CANNOT BE SAFELY INFERRED

Production JVM memory allocation flags and active Spring profile require human intent. Guessing memory limits risks OOM-kills in production.

Select production execution contract:
Decision recorded in Canonical BlueprintNo Model Decides the Plan
Zero Invented Prices

Costs come from a captured AWS rate snapshot or live AWS prices you refresh; unknown items are never treated as $0.

Zero Invented Secrets

Pilot never generates dummy passwords or fake API keys; it provisions AWS Secrets Manager placeholders.

Zero Hidden Changes

Every architectural modification is output as a readable diff in your PR branch.

Zero Silent Replacement

Existing Dockerfiles and CI scripts remain untouched unless explicitly flagged for replacement.

Zero Fake Validation

Checks that cannot be verified locally are never falsely marked as passed.

CANONICAL STATUS SYSTEM

Trust & Status Vocabulary

No unknown cost becomes $0 · No AI guess becomes fact
Detected

Proven by a file, dependency, manifest, or source declaration.

Inferred

Suggested from indirect cues or topological heuristics.

Verified Cost Rate

Retrieved directly from the AWS Price List API for the exact region.

Calculated

Deterministic arithmetic over a captured rate card snapshot.

Estimated

Depends on traffic forecasts, regional uplift, or declared assumptions.

Local

The operation runs on your machine and sends nothing.

SCENE 13 · PRE-FLIGHT VALIDATION

Don't trust generated infrastructure. Verify it.

Pilot validates the exact files it generated with the real tools before you can deliver them. A failure blocks delivery; a check whose tool is not installed is shown as skipped, never as passed.

VALIDATION OF THE EXACT FILES (EXAMPLE)
ALL INVARIANTS SATISFIED
Terraform Engine
PASS
Kubernetes Spec
PASS
Container Integrity
PASS
IAM & Network Perimeter
PASS
Cross-File Consistency
PASS
Credential Leak Detection
PASS
Architecture Correspondence
PASS
VERIFICATION TARGET: Terraform Engine

IaC Syntax & Provider Graph

PASS CRITERIA

Configuration is syntactically valid with 0 orphan references.

AUDIT PROOF

Provider constraints ~> 5.30 validated against HashiCorp registry.

Static Rule Engine100% Invariant Compliant
SCENE 14 · THE DELIVERY BOUNDARY

Export anywhere. Deliver safely. You stay in control.

Pilot gives you three distinct delivery methods: write directly to your local folder, download an offline ZIP package, or open a reviewable Git pull request. Nothing is deployed until a human approves.

CHOOSE EXPORT & DELIVERY METHOD

Safe Delivery Boundary

feat: add production cloud architecture for shop-microservices#104
pilot/dual-az-ecs-fargate → main · Generated by EgyKode Pilot (example)
7 Checks Passed
ArchitectureDual-AZ ECS Fargate
Monthly Spend$104.32 / mo
Generated Files14 files (+1,420 lines)
Delivery Invariant: Pilot has prepared all Terraform modules, ECS task definitions, and GitHub Actions workflows in a clean branch. Nothing in your cloud changes until your team reviews the diff, approves the PR, and runs your CI/CD pipeline.
Review approved plan:
SCENE 15 · THE AI PHILOSOPHY

AI that helps. Rules that protect.

Pilot refuses to place your production uptime in the hands of an unconstrained generative chatbot. Deterministic software remains authoritative for infrastructure, pricing, and security; AI assists through explanation and critique.

Deterministic Rule Engine
AUTHORITATIVE

Absolute System Authority

Strict, typed algorithms govern every mathematical calculation, resource sizing formula, and security policy. No model decides any of them.

  • Regional cloud catalog pricing & budget caps
  • Strict dependency graph & capacity sizing
  • Least-privilege IAM with no wildcard actions
  • Validation of the exact files before delivery
AI Reasoning & Critique
ASSISTIVE ADVISOR

Cognitive Explanation & Investigation

AI inspects edge cases, explains technical trade-offs in plain language, and critiques legacy configurations to provide developer clarity.

  • Translates complex topology trade-offs into plain English
  • Investigates unusual custom build scripts & dependencies
  • Suggests architectural alternatives for team evaluation
  • AI is off by default; a local model keeps code on your machine
SCENE 16 · DAY 2 VISIBILITY

Your cloud project doesn't end at generation.

Pilot maintains post-deployment visibility through a restrained, read-only operational telemetry lens — keeping your architecture healthy, cost-compliant, and observable.

READ-ONLY OPERATIONAL TELEMETRY
Cluster: shop-prod-dual-az
HEALTH 3/3 Healthy
DEPLOY STATUSSynced #a82ef4
RESTARTS0 in 30d
REQUEST RATE185 req/sec
P95 LATENCY24 ms
LIVE SPEND$104.32
Read-only: a connected cluster, Prometheus and AWS Cost ExplorerRollout, Golden Signals & Month-to-Date Spend
SCENE 17 · THE PLATFORM CAPABILITY SYSTEM

Everything connected.

Pilot unifies the entire cloud adoption lifecycle into five mathematically coherent phases. No disconnected scripts, no drift, no gaps.

01 / UNDERSTAND

Application Intelligence

PHASE VERIFIED

Local, rule-based analysis of your manifests, Dockerfiles and source rather than guessing from README files.

Polyglot Languages (Python, TypeScript, Go, Java, Rust)
Modern Frameworks (FastAPI, Spring Boot, React, Next.js)
Monorepos & Multi-Service Dependency Graphs
Runtime Contracts & Port / Environment Invariants
Brownfield Docker, Compose & CI/CD Tooling
SCENE 18 · THE PATH TO GREEN

From ambiguous blocker to green build.

Pilot refuses to throw cryptic cloud stack traces. When uncertainty arises, it isolates the exact blocking questions, provides clear paths to resolve them, and guides you to green.

2 BLOCKING DECISIONS REMAIN
Confirm production startup command for roadmap-service

Pilot identified Java 21 Spring Boot but located two candidate startup scripts. Which entrypoint should be compiled into the container spec?

Confirm primary AWS deployment region

Business requirements specified low latency for North American users. Please confirm target region for resource provisioning.

Compiler Invariant Check:Compilation suspended · Waiting for architectural decisions above
SCENE 19 · THE COMPLETE TRANSFORMATION

Your application already knows what it wants to become.

Pilot decodes that intent and compiles it directly into cloud reality.

01
SOURCE CODE
Polyglot Repo
02
3 WORKLOADS
Found in the Source
03
REQUIREMENTS
Business SLA & Budget
04
3 ARCHITECTURES
Evaluated Options
05
BEST FIT
Dual-AZ Fargate
06
$104.32 / MO
Deterministic Cost
07
BLUEPRINT
Canonical Model
08
INFRASTRUCTURE
Terraform & Specs
09
VALIDATION ✓
7 Invariants Passed
010
READY
Pull Request
From local source code to verified cloud delivery Deterministic Cloud DevOps Compiler

Your next deployment
starts with your code.

Experience the Intelligent Cloud DevOps Compiler. Point it at any local folder on disk or Git repository, inspect the generated plan, and deliver with total certainty.

Explore the architecture
Local by default · Deterministic where possible · Every recommendation explained · Reviewable before real