Cloud
A cloud footprint that is secure, scalable and extensible
Establish and evolve your cloud footprint on AWS, Microsoft Azure and Google Cloud with DevOps practices that keep your data estate secure, scalable and extensible.
What it is
Our cloud work covers the foundations that data and AI workloads depend on: landing zones, network design, identity and access management (IAM), infrastructure as code (IaC), continuous integration and continuous delivery (CI/CD), containers, serverless services, observability, resilience and cost control. We deliver on AWS, Microsoft Azure and Google Cloud, and we are vendor-honest about which services fit and which do not.
The goal is an environment that your own team can run, change and audit, rather than one that depends on ARCHR to operate. That includes workloads on Kubernetes or serverless platforms, hybrid connections to existing data centers, and the controls that let security and finance teams see what is running.
Problems it addresses
- Environments were built by hand and cannot be reproduced, reviewed or rebuilt after an incident.
- Development, test and production are not clearly separated, particularly for sensitive data.
- Cloud spend grows without an owner or a view of what drives it.
- Manual deployments make releases slow and risky.
- Identity, network and security settings differ between teams, accounts and subscriptions.
- Backup, recovery and data residency requirements have not been designed or tested.
What we deliver
- A landing zone or equivalent foundation with accounts or subscriptions, guardrails, network design and identity.
- Infrastructure as code using Terraform or the native tools of each provider, with peer review.
- CI/CD pipelines for data, analytics, machine learning and application workloads.
- Container platforms, including Kubernetes, and serverless patterns where they fit.
- Observability covering logs, metrics, traces, alerting and service-level objectives.
- A financial operations (FinOps) practice with tagging, budgets, reporting and ownership by workload.
- Backup, disaster recovery and resilience design, tested against agreed objectives.
- Operational runbooks and a handover plan for your team.
Our method
How we work
We follow our four-step method, and each step ends with a review where you can pause, adjust or stop. See the full method.
Discovery & Strategy
We review accounts or subscriptions, network layout, identity, tooling, spend and the commitments you already hold with each provider.
Pilot & Validation
A reference landing zone and one workload are built with infrastructure as code and a first deployment pipeline.
Build & Scale
More workloads and environments move onto the foundation, with policy as code, automated testing and cost allocation.
Optimize & Evolve
We tune performance and spend, run resilience tests, update runbooks and plan the next set of platform capabilities.
Technologies
Technologies we commonly work with
These are examples of tools we commonly work with across the three providers. We recommend what fits your estate and design around existing commitments rather than a template.
Cloud
The three major clouds we design and build on, shaped around the estate you already run.
- AWSAmazon Web Services: broad infrastructure, data and AI services.
- Microsoft AzureMicrosoft's cloud, closely tied to Microsoft 365, Fabric and Entra ID.
- Google CloudGoogle's cloud, known for BigQuery, Dataplex and Vertex AI.
- Cloud object storageAmazon S3, Azure Data Lake Storage and Google Cloud Storage as lake foundations.
DevOps and IaC
Infrastructure as code, CI/CD and observability so platforms are repeatable, reviewed and resilient.
- TerraformInfrastructure as code that works across all three clouds.
- BicepAzure-native language for declarative infrastructure.
- AWS CloudFormationAWS-native templates for repeatable infrastructure.
- GitHub ActionsCI/CD workflows that live next to the code.
- Azure DevOpsBoards, repositories and pipelines for delivery teams.
- KubernetesContainer orchestration for portable, scalable workloads.
- DockerContainer packaging for consistent builds and deployments.
- OpenTelemetryOpen standard for traces, metrics and logs.
Governance and security
Catalogs, lineage, access control and key management that make data and AI auditable.
- Microsoft PurviewData catalog, classification and governance across Microsoft estates.
- Unity CatalogUnified governance for data and AI assets on Databricks.
- CollibraData governance and catalog platform for policies and stewardship.
- AWS Lake FormationFine-grained access control for data lakes on AWS.
- Google DataplexData management and governance across Google Cloud data.
- Azure Key VaultManaged storage for secrets, keys and certificates on Azure.
- AWS KMSManaged encryption keys for services and applications on AWS.
- Microsoft Entra IDIdentity and access management for people and workloads.
- OpenLineageOpen standard for collecting data lineage across tools.
- Great ExpectationsOpen source framework for data quality checks.
These tools are examples of what we commonly work with, listed as text only. We are vendor-neutral and recommend what fits your estate. Product names belong to their owners, and their appearance here does not imply a partnership, endorsement or certification.
Governance and compliance
For regulated and data-intensive organizations, cloud is also an outsourcing and third-party risk question. We document where data resides, how access is controlled and logged, how keys are managed, and how resilience and recovery are handled, so that technology, risk and compliance teams have what they need for internal reviews. Outsourcing and technology risk expectations that prudential supervisors set out for financial institutions, such as Office of the Superintendent of Financial Institutions (OSFI) in Canada, the Office of the Comptroller of the Currency (OCC) in the United States and EU supervisors, are treated as design inputs, as are regional data residency rules in Canada, the United States and the European Union. This applies equally to distributed sites in energy, mining and resources and manufacturing. Alignment is confirmed by your own compliance function.
Ways to start
Engagement options
Most clients begin with an assessment or a pilot. Scope, owners and success measures are agreed in writing for each option, and the options can be combined.
Assessment
A review of your current cloud footprint, security posture, spend and delivery practices, with a prioritized improvement plan.
Pilot
A reference landing zone and one workload, built with infrastructure as code and a deployment pipeline.
Build
Delivery of the full foundation, platform services and migration of workloads, alongside your engineers.
Advisory retainer
Ongoing architecture review, cost review and design support while your team operates the estate.
This page is general information about ARCHR services. It is not legal, financial or investment advice, and it does not assure compliance with any regulation.
FAQ
Frequently asked questions
Do you work on all three major clouds?
Yes. We deliver on AWS, Microsoft Azure and Google Cloud, and we shape each design around your existing stack, skills, commitments and budget. Multi-cloud is a choice, not a default.
Will our team be able to operate what you build?
That is the intent. We use infrastructure as code, documented pipelines and runbooks, and plan a handover so your team can take over operation.
Can you help control cloud costs?
We can help put tagging, budgets, alerts and reporting in place as part of a FinOps practice, so spend can be attributed and reviewed. Actual savings depend on your workloads and decisions.
Can you help with data residency requirements?
Yes. We design regions, replication and backup around the residency rules your policy requires, and we document where data is stored and processed.
Let's talk about your data and AI priorities
Tell us what you are trying to solve. We aim to reply within one business day.