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Compute, storage, databases, networking, serverless, data and managed AI let you compose an architecture without operating everything yourself.
Expertise · AWS architectures
AWS Cloud Architecture: Infrastructure Built for Your Application
Our AWS expertise is used to host and evolve your application with an architecture suited to its load, its data and its budget. Our teams design, deploy and operate these architectures for the products they build or take over, including AI services released to production.
Understanding the technology
AWS architectures in your project.
AWS provides services for infrastructure, storage, databases and application runtime. Designing a cloud architecture means selecting and connecting these components according to how the product works. The required availability, how data is handled and the team’s ability to operate the whole stack guide these decisions.
The benefits for your product
Why choose AWS?
High availability
Multiple regions and availability zones, load balancing and replication make it possible to design services that withstand the failure of a data center.
Capacity that follows the load
Auto scaling, serverless and elastic storage adjust resources to actual usage.
Flexible pricing models
Pay-as-you-go, commitments (Reserved Instances, Savings Plans) and Spot Instances, with cost tracking tools.
Security and compliance
IAM, encryption, network isolation and the provider’s compliance programs, within a shared responsibility model where configuration remains your responsibility.
Our scope of work
The work we take on.
Architecture
Choose compute, storage and data services based on application constraints.
Access & networking
Define roles, permissions, segmentation and secret management.
Operations
Organize metrics, backups, alerts and cost tracking.
Migration
Prepare and carry out the move from existing hosting to AWS, in stages and with a planned rollback.
Our AWS expertise
The AWS ecosystem we master.
Compute
EC2 and Auto Scaling groups, Lambda for serverless, ECS, EKS and Fargate for containers.
Storage & databases
S3 (versioning, lifecycle, encryption), RDS and Aurora for PostgreSQL and MySQL, DynamoDB.
Networking & delivery
VPC, subnets, security groups and NAT gateways, CloudFront and WAF, Route 53.
Monitoring & automation
CloudWatch, CloudFormation or Terraform for infrastructure as code, CodePipeline or GitLab CI for delivery.
For containerized applications, see also our Docker and Kubernetes expertise.
AWS and AI
Releasing AI services to production on AWS.
An AI service hosted on AWS is still a service like any other: networking, identities, secrets, logs and backups. On top of that come access to models (provider APIs or managed services such as Amazon Bedrock), storage of indexed documents, and tracking of response times and usage.
Our teams handle this production release, especially when it comes to taking over an AI POC and turning it into a service you can operate. See also our AI solutions for business.
In the field
From technology to real-world use.
To host a business application, we describe the environments, access, network flows and data persistence. The deployment must be reproducible and backups restorable. We set up the logs and alerts needed to tell an application error apart from a capacity issue or an external service problem.
The choices that matter
The choices to review before building.
A managed service removes some tasks but still comes with configuration, cost and lock-in constraints. We review volumes, data transfers and business continuity needs. Initial sizing remains an assumption to be tested against the application’s measurements, rather than a promise of unlimited capacity.
From work to deliverables
Delivery your team can take over.
The scope of work specifies the components to build or take over and the validation conditions. We prepare what is needed to understand the changes, verify them and continue the work. Migration or architecture setup as a fixed-price project, long-term operations within a dedicated team, or targeted work on costs or security.
- Versioned configurations
- Documented delivery pipeline
- Monitoring and operating procedures
Frequently asked questions
AWS: your questions.
What is AWS and why use it?
Amazon Web Services is a cloud platform offering compute, storage, database, networking and AI services. It lets you host an application with adjustable capacity, without managing hardware.
Is AWS suitable for small businesses?
Yes. Pay-as-you-go pricing, serverless and managed services avoid upfront investment. The point to watch is cost tracking, which should be planned from the initial setup.
What is the difference between AWS and other cloud providers?
AWS, Microsoft Azure and Google Cloud cover comparable needs. The choice depends on your existing environment (Azure integrates naturally with a Microsoft environment), the services required, the team’s skills and commercial terms.
How do you optimize AWS costs?
Size instances based on measurements, use commitments and Spot Instances where appropriate, use serverless for intermittent workloads, apply lifecycle policies to storage and track spending with Cost Explorer.
Is AWS safe for sensitive data?
Yes, if the architecture is properly configured, with encryption at rest and in transit, least-privilege IAM, network isolation, logs and compliance checks. AWS secures the infrastructure; configuration is the responsibility of the customer and its service provider.
How do you ensure high availability on AWS?
Multi-zone deployments, Auto Scaling groups, load balancers, Route 53 health checks, replication, tested backups and a disaster recovery plan, based on the AWS Well-Architected Framework.
When should you choose serverless over EC2?
Lambda suits intermittent workloads and event-driven processing. EC2 or containers suit sustained workloads and stateful applications, or those that need more control. Cost and operational overhead decide between them.
Can you release an AI service to production on AWS?
Yes. We handle hosting, model access, secret management, monitoring of response times and costs, and taking over a prototype to make it production-ready.
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the first scope of work with your team.