Cloud application platforms
Web and mobile backends, APIs, background jobs, databases, object storage, search, events, and administration.
Built with AWS
AWS architecture selected for the workload, team, and operating reality.
Automiq designs and delivers web, mobile, SaaS, data, automation, and production AI systems on AWS without treating the breadth of the platform as a reason to use unnecessary services.
Automiq does not claim AWS Partner Network membership or AWS certifications. Services, regions, pricing, and compliance eligibility are confirmed from current AWS documentation.
Product outcome
Existing systems
Data & constraints
AWS
Fit-for-purpose design
Production controls
Owned handover
- Architecture choice
- Fit-first
- The platform must earn its place against alternatives
- Supported interfaces
- Current
- Versions, regions, APIs, and policies are verified during delivery
- Production behavior
- Operable
- Security, quality, cost, failures, and recovery remain visible
- Handover objective
- Portable
- Agreed code, access, decisions, tests, and runbooks transfer
What we build
Production systems Automiq can build with AWS.
The technology supports a business or product outcome; it is not the outcome by itself.
Production AI infrastructure
Model access, retrieval, document pipelines, evaluation, queues, observability, and application services on an AWS-aligned stack.
Migration and reliability foundations
Staged workload moves, infrastructure as code, delivery pipelines, backups, recovery, scaling, and operating dashboards.
Best-fit use cases
When AWS is a credible choice.
Fit follows workload, data, team, procurement, delivery stage, and operating responsibility—not a preferred agency stack.
The workload needs a broad managed-service catalog
Application, data, security, messaging, analytics, and AI needs can stay within one cloud operating model.
Identity and environment control matter
The business needs explicit accounts, roles, networks, secrets, encryption, logging, and separation between workloads.
The team can own cloud operations
An internal team or documented external operating model will manage cost, security, incidents, and platform change after launch.
When not to use it
- A simpler managed host or application platform meets the workload with materially less operational burden.
- The team has no owner for cloud access, cost, security, or incident response.
- AWS is being selected only because it sounds enterprise-ready, without product or procurement justification.
Architecture pattern
How AWS fits into a complete production system.
The diagram exposes the surrounding application, data, control, and operating layers that a logo wall usually hides.
- Stage 01
Edge & identity
- DNS, certificates, and request protection
- User and workload identity
- Network and account boundaries
- Stage 02
Application
- API, web, jobs, and event processing
- Containers, serverless, or managed compute
- Queues and integration interfaces
- Stage 03
Data & AI
- Relational, object, cache, and search layers
- Model or ML services where justified
- Encryption, retention, backup, and recovery
- Stage 04
Delivery & operations
- Infrastructure as code and CI/CD
- Logs, metrics, traces, and alerts
- Cost, security, incident, and recovery runbooks
Integration options
Connect through explicit interfaces and ownership boundaries.
Integration choices are evaluated for identity, source ownership, data contracts, failure behavior, supported APIs, and long-term operations.
Customer-owned AWS organization
Preferred where the customer needs direct ownership of accounts, billing, identity, audit, and long-term operations.
Hybrid or multi-cloud integration
AWS services connect through explicit identity, network, data, and failure boundaries when other systems remain elsewhere.
Managed SaaS alongside AWS
Use proven SaaS for undifferentiated capabilities while AWS hosts the application logic and data that need custom control.
Production controls
Security, cost, quality, and handover are part of the implementation.
Controls scale with failure consequence, data sensitivity, usage, and the people responsible after release.
Security and access
Account separation, least privilege, workload roles, secrets, encryption, network controls, audit logging, and reviewed break-glass access.
Performance and cost
Load profiles, right-sized compute, scaling limits, storage lifecycle, query behavior, budgets, tagging, and cost attribution.
Testing, observability, and handover
Infrastructure checks, deployment gates, service-level indicators, alert ownership, backup tests, recovery exercises, diagrams, and runbooks.
Deployment models
Ways AWS can fit the operating environment.
Current vendor support, region, procurement, identity, team capability, and recovery objectives determine the final route.
Serverless and managed services
Useful for event-driven or variable workloads when service limits and execution behavior fit.
Managed containers
Useful for portable long-running applications that need controlled runtime behavior without operating a cluster directly.
Kubernetes or specialized platforms
Reserved for workloads and organizations that justify orchestration complexity, team capacity, or platform standardization.
Regional platform context
AWS availability and terminology must match the market.
Vendor features, hosting locations, commercial terms, legal entities, supported interfaces, and model or service availability can differ by country and region.
Regions and residency
Validate which AWS services are available in the required geography, where data and logs move, and which recovery region is permitted.
Localization layer
Design locale, language, dates, time zones, addresses, phone formats, currency, tax, units, accessibility, and right-to-left behavior where the product requires them.
Procurement and operations
Confirm account ownership, billing currency, provider terms, support route, service limits, deprecation policy, release windows, and international team overlap.
Alternatives
Compare AWS with the closest credible options.
The decision guide explains when another model, framework, cloud, platform, or simpler approach may be better.
| Option | Best when | Main tradeoff |
|---|---|---|
| AWS | Its current regions, services, procurement, identity, and team capability fit the application and operating model. | Broad capability with architecture, cost, and governance complexity. |
| Azure or Google Cloud | Microsoft or Google identity, data, AI, commercial agreements, or existing operations create a stronger fit. | Different managed-service ecosystem and skills requirement. |
| Focused application platform | A smaller workload benefits more from simple deployment and low operating overhead than from cloud breadth. | Faster operations with fewer infrastructure choices and less control. |
Delivery stages
From architecture evidence to an operable handover.
The method is adapted to the platform and project size. A bounded integration uses lighter ceremony than a cloud migration, but the control points remain.
- 01
Scope & discovery
Map users, workflows, constraints, success measures, and the smallest valuable production milestone.
Outcome: Prioritized scope and delivery plan
- 02
Data & architecture
Audit systems, integrations, data quality, security boundaries, and the architecture the future team can maintain.
Outcome: Architecture and risk register
- 03
Prototype & evaluate
Test the riskiest assumptions against representative data, measurable acceptance criteria, and real user feedback.
Outcome: Evidence-based go or adjust decision
- 04
Build & integrate
Ship in reviewable increments with testing, access controls, observability, documentation, and clear ownership.
Outcome: Production-ready software
- 05
Deploy & hand over
Release progressively, monitor real usage, train operators, and transfer repositories, infrastructure, and runbooks.
Outcome: Controlled launch and clean handover
- 06
Support & grow
Maintain reliability, refine workflows, manage dependencies, and keep shipping as the product and business evolve.
Outcome: A stable platform that keeps improving
Timeline and investment context
Scope follows the production responsibility—not a technology label.
Automiq does not publish a universal duration or price for technology implementation. Discovery identifies a bounded milestone and the risks that shape it.
Environment and governance depth
Accounts, networks, environments, identity, audit, policy, and infrastructure code shape the setup effort.
Reliability objectives
Availability, data durability, recovery time, recovery point, multi-region behavior, and incident response influence architecture.
Consumption and operating ownership
Traffic, compute, storage, data transfer, monitoring, support, and team time belong in total cloud cost.
Third-party platform, model, cloud, hosting, data, support, app-store, and usage charges remain separate unless an engagement agreement explicitly includes them.
Relevant experience
Product context behind the technology decisions.
ATZ CRM provides founder-led SaaS operating experience relevant to cloud delivery, customer data, integrations, support, monitoring, and international product use. No AWS-specific certification or unverified architecture claim is attached.
Product visual
founded
ATZ CRM
Recruitment · B2B SaaS experience involving AI, Web app, Workflow automation, CRM integrations.
- Recruitment
- B2B SaaS
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AWS development questions, answered
Direct answers about fit, alternatives, architecture, access, operations, ownership, and handover.
Does every production product need AWS?
No. A focused managed platform can be the better choice for smaller products or teams. AWS is justified when its control, service breadth, procurement, region, or scaling profile creates real value.
Can Automiq migrate an existing application to AWS?
Yes. Migration can use inventory, dependency mapping, infrastructure as code, data replication, compatibility testing, gradual traffic movement, reconciliation, rollback, and post-cutover monitoring.
How do you control AWS cost?
Cost control starts with workload shape and ownership, then uses right-sizing, scaling boundaries, storage lifecycle, query efficiency, budgets, tagging, attribution, alerts, and regular review.
Does Automiq claim an official vendor partnership for this technology?
No official vendor partnership or certification is claimed on this page. Automiq is an independent engineering company; any future partner status should be published only with current supporting evidence.
Who owns the application and handover materials?
Ownership is finalized in the engagement agreement. The intended custom-build model hands over the agreed source code, configuration, infrastructure access, architecture decisions, tests, documentation, and operating runbooks. Third-party platforms retain ownership of their own services.
Talk to the engineering team
Discuss a AWS requirement with the engineering team.
Bring the product, workflow, current stack, constraints, and expected operating model. We will help determine whether this technology is the right fit and define the first useful milestone.