Enterprise Cloud Infrastructure Services

Enterprise Cloud Infrastructure
& Architecture Services

Build a secure cloud foundation designed around your workloads, operating model, resilience requirements and growth plans.

Mobiloitte architects and engineers enterprise cloud infrastructure across AWS, Microsoft Azure and Google Cloud, including landing zones, networking, identity, compute, storage, Infrastructure as Code, governance, observability and disaster recovery.

Whether you are establishing a new cloud environment, strengthening an existing estate or operating across hybrid and multi-cloud environments, we help create infrastructure that is repeatable, governed, observable and ready to evolve.

Request a Cloud Architecture Assessment

What Are Enterprise Cloud Infrastructure Services?

Enterprise cloud infrastructure services help organizations design, provision, secure, govern and operate the computing foundation used by applications, data platforms and AI workloads.

A modern cloud environment can include compute, storage, databases, networks, identity, security controls, monitoring, backup, disaster recovery and automated provisioning across public, private or hybrid environments.

Infrastructure as Code and cloud governance make those environments more repeatable and controlled, while CloudOps, observability and FinOps help teams manage reliability, performance and cost after deployment.

Enterprise Cloud Infrastructure
Capabilities

01.

Cloud Strategy & Architecture Assessment

Start with the workloads and business requirements before provisioning resources.

  • Existing infrastructure
  • Application workloads
  • Data requirements
  • Security requirements
  • Availability targets
  • Integration dependencies
  • Cloud costs
  • Operating model
Deliverables can include: Target architecture, Risk assessment, Landing-zone design, Cost considerations, Governance model.
02.

Enterprise Cloud Landing Zones

Build a governed cloud foundation before large numbers of workloads are introduced.

  • Account/subscription structure
  • Identity
  • Network topology
  • Shared services
  • Security baselines
  • Policy guardrails
  • Resource organization
  • Environment separation
Why it matters: A landing zone establishes reusable standards before inconsistent permissions, uncontrolled costs and weak visibility scale.
03.

Cloud Networking & Connectivity

Design secure connectivity across cloud, enterprise and hybrid environments.

  • VPC/VNet architecture
  • Route design
  • Load balancing
  • DNS
  • Firewalls
  • VPN connectivity
  • Private connectivity
  • Transit architecture
Architecture should reflect application flows and security requirements rather than reusing one network template for every workload.
04.

Compute, Storage & Database Infrastructure

Provision workload infrastructure according to performance, availability and cost requirements.

  • Virtual machines & Containers
  • Serverless infrastructure
  • Object & Block storage
  • Managed relational services
  • NoSQL infrastructure
  • Backup and replication
Technology selection should follow the workload rather than a fixed cloud-services checklist.
05.

Infrastructure as Code & Automated Provisioning

Treat infrastructure configuration as version-controlled engineering.

  • Terraform
  • AWS CloudFormation
  • Azure Bicep / ARM
  • Google Cloud IaC approaches
  • Configuration automation
  • Reusable modules
Key Principle: Infrastructure should be reproducible—not dependent on undocumented console changes.
06.

Cloud Governance & Policy as Code

Define controls for how cloud resources are created and managed.

  • Resource hierarchy
  • Naming & Tagging
  • Identity standards
  • Security requirements
  • Encryption
  • Cost allocation
  • Resource lifecycle
Governance should help teams move faster within clear boundaries rather than making every cloud action a manual approval exercise.
07.

Hybrid & Multi-Cloud Infrastructure

Not every enterprise workload belongs in one public cloud.

  • AWS
  • Microsoft Azure
  • Google Cloud
  • Existing data centers
  • Private cloud
  • Edge environments
Important: Multi-cloud should solve a real business or technical requirement—not be introduced solely to say the architecture avoids vendor lock-in.
08.

Cloud Reliability & High Availability

Availability should be engineered according to actual business impact.

  • Multi-zone deployment
  • Load balancing
  • Autoscaling
  • Replication
  • Fault isolation
  • Automated recovery
  • Service-level objectives
  • Recovery time objective
Instead of claiming generic 'high uptime,' establish SLOs, RTO, RPO, and critical workload classification.
09.

Backup, Disaster Recovery & Business Continuity

High availability and disaster recovery are not the same thing.

  • Backup architecture
  • Cross-zone replication
  • Cross-region recovery
  • Infrastructure recreation
  • Recovery automation
  • Failover procedures
  • Recovery testing
Key Principle: A disaster recovery plan is only useful when it has been tested.
10.

CloudOps, Observability & SRE

Cloud infrastructure needs an operating model after deployment.

  • Metrics, Logs, Traces
  • Alerting
  • Infrastructure monitoring
  • Application dependencies
  • Incident management
  • Capacity management
  • Runbooks
  • Automation
The goal is to understand what is failing, whom it affects and how quickly normal service can be restored.
11.

FinOps & Cloud Cost Optimization

Cloud cost management should be continuous rather than a one-time cleanup exercise.

  • Cost allocation
  • Tagging
  • Budget monitoring
  • Rightsizing
  • Idle-resource detection
  • Storage optimization
  • Commitment analysis
Measure More Than Spend: Cloud economics should consider Cost + performance + reliability + business requirement.
12.

Cloud Infrastructure for AI & Data Workloads

AI and modern data platforms can create different infrastructure demands.

  • Compute & GPU requirements
  • Storage throughput
  • Data locality
  • Network performance
  • Containers
  • Managed AI services
  • Model serving
The infrastructure should follow the AI or data workload rather than assuming every workload requires specialized compute.

Architecture of an
Enterprise Cloud Foundation

Organization & Governance

Accounts/Subscriptions • Resource Hierarchy • Policies • Budgets • Tags

Identity & Access

Users • Roles • Workload identities • SSO • MFA • Least privilege

Network Foundation

VPC / VNet • Subnets • Routing • DNS • Firewalls • Private/Hybrid connectivity

Shared Platform Services

Logging • Monitoring • Secrets • Key management • Container platforms • Automation services

Workload Infrastructure

Compute • Storage • Databases • Queues • Load balancers • Application services

Reliability & Recovery

Autoscaling • Replication • Backup • Disaster recovery • Failover

Operations

CloudOps • Observability • SRE • FinOps • Incident management

Across Every Layer

Security • Governance • Automation • IaC • Cost Visibility • Compliance Controls

Design Cloud Infrastructure Around
Measurable Architecture Principles

1

Operational Excellence

Can teams deploy, monitor and operate infrastructure consistently?

2

Security

Are identities, data, networks and workloads protected according to risk?

3

Reliability

Can the workload continue operating or recover according to defined business requirements?

4

Performance Efficiency

Is infrastructure appropriately sized and designed for the workload?

5

Cost Optimization

Can teams understand and continuously improve resource consumption?

6

Sustainability

Can infrastructure efficiency and resource consumption be considered alongside technical and commercial requirements?

Mobiloitte can review cloud environments against the relevant architecture guidance and workload requirements of the selected platform rather than applying one generic checklist to AWS, Azure and Google Cloud.

Enterprise Cloud Infrastructure
Delivery Process

From Workload Requirements to Governed Cloud Operations

01

Discover

Define:
  • Business objectives
  • Workloads
  • Users
  • Availability requirements
  • Security requirements
  • Integrations
  • Current infrastructure
  • Cloud constraints
02

Assess

Evaluate:
  • Current architecture
  • Dependencies
  • Networking
  • Identity
  • Security
  • Performance
  • Cloud spend
  • Operational maturity
  • Recovery capabilities
03

Architect

Design:
  • Landing zone
  • Network
  • Identity
  • Compute
  • Storage
  • Databases
  • Security
  • Governance
  • Reliability
  • Recovery
  • Operations
04

Codify

Create:
  • Infrastructure as Code
  • Reusable modules
  • Policies
  • Configuration
  • Environment patterns
  • Version-controlled definitions
05

Deploy

Provision:
  • Platform foundation
  • Networking
  • Shared services
  • Workload environments
  • Monitoring
  • Security controls
06

Validate

Test:
  • Access
  • Connectivity
  • Performance
  • Security controls
  • Failover
  • Backup
  • Recovery
  • Monitoring
  • Policy enforcement
07

Handover & Operationalize

Provide:
  • Architecture documentation
  • Runbooks
  • Access model
  • Monitoring model
  • Recovery procedures
  • Cost model
  • Operational ownership
08

Optimize

Continuously review:
  • Utilization
  • Reliability
  • Cost
  • Security
  • Performance
  • Capacity
  • Governance

Cloud Infrastructure Across
AWS, Azure & Google Cloud

We design the platform around the workload and existing enterprise environment—not around cloud-provider logo preference.

AWS Cloud Infrastructure

Design AWS environments around appropriate:

  • AWS Organizations / account structure
  • VPC
  • Compute
  • Storage
  • Databases
  • IAM
  • Load balancing
  • Monitoring
  • Backup
  • Infrastructure as Code
Use AWS architecture patterns according to workload requirements rather than simply listing services.

Microsoft Azure Infrastructure

Design Azure environments using appropriate:

  • Management groups
  • Subscriptions
  • Azure landing zones
  • VNets
  • Microsoft Entra ID
  • Compute
  • Storage
  • Databases
  • Azure Policy
  • Monitoring
  • Backup and recovery
  • Infrastructure as Code

Google Cloud Infrastructure

Design Google Cloud environments around appropriate:

  • Organization hierarchy
  • Folders
  • Projects
  • VPC
  • IAM
  • Compute
  • Storage
  • Managed databases
  • Logging and monitoring
  • Policy controls
  • Backup
  • Infrastructure automation

Cloud Security & Governance by Design

Security should be designed across identities, networks, workloads, data and cloud operations.

Identity & Access

  • SSO
  • MFA
  • Role-based access
  • Workload identities
  • Least privilege

Network Security

  • Segmentation
  • Private networking
  • Firewalls
  • Security groups
  • Controlled ingress/egress

Data Protection

  • Encryption
  • Key management
  • Backup
  • Secrets management

Infrastructure Security

  • Secure baselines
  • Configuration reviews
  • Vulnerability management
  • Patch strategy

Logging & Monitoring

  • Activity logs
  • Security events
  • Configuration changes
  • Operational monitoring

Governance

  • Policies
  • Resource standards
  • Approved regions
  • Tagging
  • Budgets
  • Ownership

Compliance Support

Cloud controls can be mapped to applicable privacy, security and industry requirements according to the client's workloads, organizational responsibilities and regulatory environment. Compliance should be validated across the full operating environment rather than assumed from infrastructure configuration alone.

Cloud Economics & FinOps

Build Cost Visibility Into the Architecture. Cloud spending becomes difficult to manage when nobody can connect consumption with workloads, teams or business ownership.

Establish Cost Ownership

  • Accounts / subscriptions / projects
  • Tags
  • Cost centers
  • Workload ownership

Monitor

  • Compute
  • Storage
  • Network
  • Database
  • Observability
  • AI/data workloads
  • Non-production environments

Optimize

  • Rightsizing
  • Autoscaling
  • Scheduling
  • Commitment models
  • Idle resources
  • Storage lifecycle
  • Architectural efficiency

Govern

  • Budgets
  • Alerts
  • Reporting
  • Ownership
  • Review cycles
Key Principle: Cloud cost optimization should preserve required reliability and performance rather than simply minimizing the monthly bill.

CloudOps, Observability & Infrastructure Reliability

Go Beyond “Infrastructure Is Up”. A healthy cloud platform should show how infrastructure behaves and how that behavior affects workloads.

MetricsCPU, Memory, Storage, Network, Capacity, Platform services
LogsInfrastructure events, Cloud activity, Security events, Application dependencies
TracesWhere distributed workloads require deeper request visibility.
AlertingDesign actionable alerts around service impact rather than generating noise for every metric deviation.
ReliabilitySLOs, Error budgets, Incident workflows, Recovery procedures, Runbooks
AutomationAutomate repeatable operational work when the action is safe, observable and reversible.

Cloud Backup & Disaster Recovery

Design Recovery Before Failure Happens.

Define Business Requirements

  • RTO — How quickly must service be restored?
  • RPO — How much data loss can the business tolerate?
DesignBackup, Replication, Snapshots, Cross-zone architecture, Cross-region recovery, Infrastructure recreation
AutomateUse Infrastructure as Code and runbooks to make recovery repeatable.
TestPerform periodic restoration or failover exercises appropriate to workload criticality.
DocumentEnsure ownership, procedures and dependencies are clear before an incident occurs.
Supporting Principle: Recovery capability should be proven through testing—not assumed because backups exist.

Cloud Infrastructure for AI & Data Workloads

AI-ready infrastructure begins with workload requirements—not GPU procurement. Depending on the system, architecture may need to consider:

Compute

  • General compute
  • Accelerated compute where genuinely required
  • Autoscaling
  • Containerized workloads

Data

  • Storage throughput
  • Data movement
  • Database connectivity
  • Analytics platforms
  • Vector or retrieval workloads

Networking

  • Private connectivity
  • Bandwidth
  • Latency
  • Security boundaries

AI Services

  • Managed model services
  • Private endpoints
  • Model-serving infrastructure
  • Agent/application dependencies

Operations

  • Usage monitoring
  • Capacity
  • Latency
  • Cost visibility
  • Security monitoring

Governance

  • Identity
  • Data access
  • Approved services
  • Regional constraints
  • Logging

Why Cloud Infrastructure Programs Fail—
and How We Engineer Around It

Cloud Without Governance

Problem
Teams create inconsistent environments and permissions.
Response
Landing zones, policy guardrails, reusable architecture and clear ownership.

Manual Infrastructure

Problem
Production environments depend on console configuration and tribal knowledge.
Response
Infrastructure as Code, reusable modules and version-controlled provisioning.

Cloud Cost Without Ownership

Problem
Spend grows faster than teams can explain it.
Response
FinOps, tagging, budgets, cost allocation and continuous optimization.

Availability Without Recovery Planning

Problem
Infrastructure is redundant but major failures have never been tested.
Response
SLOs, RTO/RPO, backup architecture and tested disaster recovery.

Monitoring Without Observability

Problem
Teams receive alerts but cannot quickly understand impact or root cause.
Response
CloudOps, observability, service-level monitoring and operational runbooks.

Multi-Cloud Without a Business Case

Problem
Architecture complexity increases without generating measurable value.
Response
Use hybrid or multi-cloud only when workload, regulatory or strategic requirements justify it.

Cloud Infrastructure in Practice

Confidential E-Commerce Enterprise

Existing EnvironmentLegacy monolithic application on provisioned VMs with manual scaling.
ChallengeCannot handle peak traffic spikes reliably, manual deployments causing errors, high fixed infrastructure costs.
ArchitectureAWS Landing Zone, Auto-scaling groups, EKS, RDS Multi-AZ, CloudFront, Terraform IaC.
Mobiloitte's WorkArchitected a scalable landing zone, containerized core workloads, implemented IaC pipelines, and optimized database tier.
ValidationLoad testing simulated 10x traffic, automated failover drills conducted, security baseline validated via AWS Config.
Measured OutcomeDeployment consistency improved to 100% automated, infrastructure provisions in minutes instead of days, zero downtime during peak sales events.
View Cloud Case Study

Financial Services Provider

Existing EnvironmentOn-premise data centers with partial shadow IT in public cloud.
ChallengeStrict regulatory requirements, inconsistent security policies, lack of disaster recovery visibility.
ArchitectureAzure Landing Zones, ExpressRoute, Azure Policy, Azure Kubernetes Service, Geo-redundant storage.
Mobiloitte's WorkDesigned compliant hybrid cloud architecture, enforced governance via Policy as Code, built automated DR environments.
ValidationFull DR failover tested within RTO objectives, compliance audited across all subscriptions.
Measured OutcomeRecovery test completed within agreed RTO, centralized governance established, legacy footprint reduced by 40%.
View Cloud Case Study

Measure Cloud Infrastructure
by Outcomes—not Resources Created

Reliability

01
  • Availability
  • Incident frequency
  • Recovery time
  • Backup success
  • DR test performance

Performance

02
  • Latency
  • Throughput
  • Capacity
  • Resource saturation

Operations

03
  • Manual infrastructure effort
  • Provisioning time
  • Incident resolution
  • Automation coverage

Cost

04
  • Cloud spend
  • Cost per workload
  • Idle resources
  • Utilization
  • Forecast accuracy

Security

05
  • Configuration findings
  • Access exceptions
  • Vulnerability remediation
  • Policy coverage

Governance & Delivery

06
  • Tagging coverage
  • Resource ownership
  • Budget coverage
  • Environment provisioning time
  • IaC adoption
  • Configuration drift
Define Your Cloud Infrastructure KPIs

Choose the Right Cloud
Infrastructure Starting Point

Cloud Architecture Assessment

For organizations evaluating current infrastructure or planning a new cloud foundation.

Outcome
Current-state assessment, target architecture, priorities and roadmap.

Landing Zone Implementation

For organizations establishing governed AWS, Azure or Google Cloud environments.

Outcome
Cloud foundation, identity, networking, policies, logging and IaC.

Cloud Infrastructure Build

For new applications and digital platforms.

Outcome
Production-ready workload infrastructure designed against defined requirements.

Hybrid & Multi-Cloud Architecture

For organizations operating workloads across clouds, data centers or distributed environments.

Cloud Reliability & DR Assessment

For critical workloads requiring stronger availability and tested recovery.

FinOps & Cloud Optimization

For organizations needing better cost visibility and workload optimization.

CloudOps & Observability Enablement

For organizations improving monitoring, incident response and infrastructure operations.

Infrastructure as Code Transformation

For environments still relying heavily on manual provisioning and configuration.

Managed Cloud Infrastructure

For organizations requiring ongoing monitoring, maintenance, optimization and operational support.

Frequently Asked Questions

Mobiloitte can design and engineer cloud architecture, landing zones, networking, identity, compute, storage, databases, Infrastructure as Code, governance, reliability, disaster recovery, observability and cost-management capabilities across supported AWS, Azure and Google Cloud environments.
A cloud landing zone is a governed foundation for deploying workloads. It typically defines areas such as account or subscription structure, identity, networking, security, logging, policies, resource organization and cost controls before application teams begin scaling cloud usage.
Infrastructure as Code represents infrastructure configuration in version-controlled files that can be reviewed and automatically deployed. It improves repeatability and reduces dependence on manual cloud-console configuration.
Terraform can be used where it fits the client's cloud architecture and technology requirements. Provider-native IaC technologies can also be used when they are more appropriate.
High availability is designed to keep a service operating despite common component failures. Disaster recovery defines how a service and its data are restored after a larger disruption. Both should be based on clearly defined business requirements.
Start with the workload's business impact and establish measurable requirements such as availability objectives, recovery time and acceptable data loss. Architecture can then be designed around those targets.
Hybrid cloud combines cloud services with existing private, on-premise or distributed infrastructure where applications or data need to operate across those environments.
No. Multi-cloud is appropriate where specific technical, organizational, regulatory or strategic requirements justify operating across multiple providers. Using multiple clouds without a clear requirement can increase operational complexity.
FinOps is an operating discipline for improving visibility, accountability and optimization of cloud consumption. It brings engineering, financial and business stakeholders together around cloud cost and value.
Optimization can include rightsizing, autoscaling, eliminating idle resources, storage lifecycle design, commitment analysis, workload scheduling and improved cost allocation. Cost decisions should also preserve required performance and reliability.
CloudOps covers the operational practices used to monitor, manage and improve cloud environments after deployment. This may include observability, incident response, capacity management, automation, reliability and operational documentation.
Yes, architecture and infrastructure can be designed around AWS, Microsoft Azure and Google Cloud according to the client's environment and workload requirements. The platform should be selected according to business and technical needs rather than provider preference alone.
Security can include identity and access controls, network segmentation, encryption, secrets management, logging, secure configuration, vulnerability management and cloud governance. The required controls depend on the workload and risk profile.
No. Cloud architecture and engineering controls can support regulatory and security requirements, but organizational compliance depends on the wider combination of technology, policies, processes, people and operational responsibilities.
Yes. Existing cloud estates can be assessed for architecture, networking, governance, reliability, security, observability, Infrastructure as Code adoption and cost efficiency before an improvement roadmap is defined.
An AI-ready cloud foundation is infrastructure designed around the compute, data, network, security, scaling and operational requirements of AI workloads. Not every AI application requires specialized hardware; architecture should follow the specific model and application requirements.
There is no universal timeline. Duration depends on cloud providers, network complexity, security requirements, accounts or subscriptions, workloads, governance, IaC, integrations and migration scope. An architecture assessment should define the realistic implementation plan.

Build a Cloud Foundation Your Workloads Can Depend On

Move beyond one-time cloud setup. Mobiloitte can help you establish a cloud environment designed around governance, security, reliability, automation, cost visibility and operational readiness from the beginning.

Start by understanding the workloads. • Design the foundation. • Automate the infrastructure. • Validate reliability. • Then operate and optimize using production evidence.
Request a Cloud Architecture AssessmentDiscuss Your Infrastructure Challenge
AWS • Azure • Google Cloud • Landing Zones • IaC • Hybrid Cloud • FinOps • CloudOps