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Aixo LabAixo Lab

AWS Cloud Development

We architect and run enterprise software on AWS — high availability, auto scaling, and disaster recovery designed as engineering decisions, not defaults inherited from a template.

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  • High Availability
  • Auto Scaling
  • Serverless
  • Infrastructure as Code
  • Multi-AZ
Overview

Our approach

We architect and run enterprise software on AWS — high availability, auto scaling, and disaster recovery designed as engineering decisions, not defaults inherited from a template.

  • Elastic by Design

    Capacity that grows and shrinks with real traffic, sized deliberately rather than provisioned for worst-case load year-round.

  • Redundancy Across Failure Domains

    Systems distributed across availability zones so a single hardware or network failure doesn't take down the whole platform.

  • Managed Services Where They Earn Their Keep

    RDS, managed queues, and other managed services chosen when they genuinely reduce operational burden — not by default.

  • Global Edge Delivery

    Content and API responses served from locations close to users, when latency actually matters for the product.

  • Security as Infrastructure, Not an Add-on

    Network isolation, least-privilege access, and encryption built into the architecture from the start.

  • Cost Is an Architecture Decision

    Compute, storage, and data transfer choices made with their cost implications considered up front, not discovered on a bill.

What's Included

Everything under one roof

Everything included in this engagement, from architecture to long-term support — one team, one system.

Cloud Infrastructure

Networking, compute, and storage architected around the application's actual availability and scale requirements.

Application Hosting

Web application hosting on infrastructure sized and configured for the traffic and uptime the product needs.

API Hosting

API infrastructure with load balancing, auto scaling, and health checks built in from the start.

Container Deployments

Containerized applications deployed and orchestrated with a deployment pipeline that supports safe, repeatable releases.

Serverless Applications

Event-driven, serverless architectures for workloads where they genuinely reduce operational overhead.

File Storage

Object storage architected for the access patterns, durability, and cost profile the data actually needs.

Background Processing

Asynchronous job processing decoupled from the request cycle, with retry and failure handling designed in.

Monitoring

Infrastructure and application monitoring that surfaces real problems, not a dashboard nobody looks at.

Infrastructure Automation

Infrastructure as code so environments are reproducible and changes are reviewed like any other code change.

Scalable SaaS Platforms

Multi-tenant infrastructure architected for the isolation and scaling requirements a SaaS product actually has.
Why Aixo Lab

Why companies choose Aixo Lab

  1. We Architect for Failure, Not Just Happy Paths

    Redundancy and failover are designed in from the start, because the question isn't whether something will fail, it's what happens when it does.

  2. We Choose Managed Services Deliberately

    A managed service earns its place when it genuinely reduces operational burden — not because it's the default recommendation.

  3. We Treat Infrastructure as Code From Day One

    Infrastructure changes go through the same review process as application code, so environments stay reproducible and auditable.

  4. We Design Cost Controls Into the Architecture

    Compute and storage choices are made with their cost profile considered up front, not discovered as a surprise bill after launch.

  5. We Hand Off Infrastructure Your Team Can Own

    Clear architecture and documentation mean your own engineers — or ours, later — can operate this infrastructure without archaeology.

Our Capabilities

Our AWS Capabilities

The specific technical capabilities behind every AWS engagement — not a generic feature list, the actual engineering surface we work in daily.

Cloud Architecture

Infrastructure designed around the application's real availability, scale, and compliance requirements.

High Availability

Systems distributed across multiple availability zones so a single failure doesn't take down the platform.

Auto Scaling

Capacity that adjusts to real traffic automatically, sized with actual load patterns rather than guesswork.

Load Balancing

Traffic distributed across healthy instances with automatic removal of ones that stop responding correctly.

Serverless

Event-driven compute for workloads where it genuinely reduces operational overhead compared to managing servers.

Containers

Containerized applications orchestrated for consistent deployment across development, staging, and production.

Object Storage

Durable storage for files and assets, architected around the access patterns and durability the data needs.

CDN

Content delivered from edge locations close to users, reducing latency for static and dynamic content alike.

Databases

Managed and self-hosted database options chosen based on consistency, scale, and operational requirements.

Monitoring

Visibility into infrastructure and application health — latency, error rates, and resource utilization.

Logging

Centralized, structured logging that makes production issues traceable instead of guessed at.

Security

Network isolation, least-privilege IAM policies, and encryption at rest and in transit.

Cost Optimisation

Resource sizing and pricing model choices made deliberately against actual usage, not left to drift.

Disaster Recovery

Backup and recovery procedures designed and tested before they're needed, not assumed to work.
Process

How we work

The same disciplined process behind every engagement, from the first architecture decision to launch.

  1. 01
    Discovery

    Understand the business problem and its real constraints.

    Output:
    Scope and goals document
    Your involvement:
    Initial workshop
  2. 02
    Product definition

    Translate the problem into concrete product requirements.

    Output:
    Feature spec and priorities
    Your involvement:
    Requirements review
  3. 03
    UX/UI design

    Design user flows and interface before development starts.

    Output:
    Wireframes and design system
    Your involvement:
    Design feedback
  4. 04
    Technical architecture

    Define system structure, data flow, and technology stack.

    Output:
    Architecture document
    Your involvement:
    Technical review (optional)
  5. 05
    Iterative development

    Build in short cycles with visible, regular progress.

    Output:
    Regularly shipped working versions
    Your involvement:
    Sprint review participation
  6. 06
    Quality assurance

    Test functionality, performance, and security before release.

    Output:
    Test results and fixes
    Your involvement:
    Acceptance sign-off
  7. 07
    Launch

    Deploy to production with a rollback plan in place.

    Output:
    Product deployed to production
    Your involvement:
    Launch approval
  8. 08
    Continuous improvement

    Monitor, maintain, and evolve the product after launch.

    Output:
    Maintenance and improvement roadmap
    Your involvement:
    Regular check-in meetings
Technology Stack

Built on a modern, production-grade stack

Every technology here is a deliberate choice, not a default.

AWS

The cloud platform underlying the infrastructure for every engagement built this way.

EC2

Virtual compute instances for workloads that need more control than a fully managed platform provides.

ECS

Container orchestration for applications packaged as containers, without managing the underlying servers.

Lambda

Serverless compute for event-driven workloads where managing servers doesn't make sense.

S3

Object storage for files, backups, and static assets, sized for durability and access patterns.

CloudFront

Content delivery network for serving content from locations close to users.

RDS

Managed relational databases for workloads that benefit from AWS handling backups, patching, and failover.

PostgreSQL

The relational database of choice for applications that need strong data integrity guarantees.

Redis

Caching and session storage for workloads that need speed a database alone can't provide.

Docker

Containerized builds for consistent environments across development, staging, and production.

Next.js

A full-stack framework commonly deployed on AWS infrastructure for applications needing both frontend and API layers.

Laravel

An enterprise backend framework deployed on AWS for applications with substantial backend logic.

Node.js

A backend runtime well suited to containerized and serverless deployment on AWS.

React Native

The mobile client layer that consumes APIs hosted on AWS infrastructure.

Terraform

Infrastructure as code tooling used to define, version, and provision AWS resources reproducibly.
Cloud Engineering

Cloud Engineering

The engineering decisions that determine whether infrastructure stays reliable, secure, and affordable as it grows, not just at launch.

Infrastructure as Code

Infrastructure defined in version-controlled code, so environments are reproducible and changes are reviewed and auditable.

High Availability

Redundancy across availability zones designed during architecture planning, not added after the first outage.

Auto Scaling

Scaling policies tuned to real traffic patterns, so capacity grows ahead of demand and shrinks when it's not needed.

Load Balancing

Traffic distribution and health checks designed so a failing instance is removed before it affects users.

CI/CD

Automated build, test, and deployment pipelines that make releases routine instead of risky events.

Backups

Automated, tested backup procedures for data that actually matters, with a defined recovery point objective.

Monitoring

Infrastructure and application metrics surfaced through dashboards and alerts tied to real failure conditions.

Observability

Logs, metrics, and traces correlated together, so a production issue can be diagnosed instead of guessed at.

Security

Network isolation, identity and access management, and encryption designed as infrastructure, not configured ad hoc.

Disaster Recovery

Recovery procedures designed and tested against a defined recovery time objective, not assumed to work when needed.

Cost Management

Ongoing visibility into spend by service and environment, with resource sizing reviewed against actual usage.
Representative Solutions

Where this technology fits

Reference architectures from our Representative Solutions collection that could plausibly be built on this stack.

Smart Warehouse Management System
Representative Solution

Smart Warehouse Management System

Logistics Software
Property Management Cloud
Representative Solution

Property Management Cloud

Real Estate
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