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A cloud landing zone is the governed foundation for deploying and operating workloads—not just a network segment or an account created once. Before moving production workloads to Azure, AWS, or Google Cloud, decide how resources will be organized, who can access them, how they connect, which controls apply, how activity will be monitored, and how workloads will be protected and paid for. Use this checklist to document those decisions, then build only the foundation your first workloads and requirements need.
What should a cloud landing zone checklist produce?
It should produce an agreed design and an implementation sequence, not a list of cloud services to enable indiscriminately. Microsoft Learn describes an Azure landing zone as “a proven and flexible architecture for governing, securing, and scaling a multi-subscription Azure environment.” AWS frames its landing-zone design around a secure, scalable multi-account environment, while Google Cloud describes a modular cloud foundation. These are provider-specific formulations of a shared goal: give workloads a secure, supportable place to run and establish how the organization governs that environment.
For each decision below, record the chosen approach, its owner, the workloads or environments it covers, and any exception process. The design should make clear who operates shared services, who can provision workload environments, which controls are centrally enforced, and who approves exceptions. Start with the needs of the first workloads; add complexity when a real risk, regulatory requirement, or operating need justifies it.
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1. What is in scope, and who owns it?
Begin with the workloads, obligations, and people the foundation must support. Without this scope, hierarchy, network, security, and recovery decisions are guesses.
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- Name the business outcomes, initial workloads, environments, data classifications, and regions in scope.
- Identify accountable owners for platform services, identity, networking, security, operations, finance, and each workload.
- Decide whether workloads with different risk, regulatory, or connectivity requirements need separate environments or policies.
- Assign authority for approving policy and access exceptions, and specify how teams request them.
- Set an initial boundary: include what the first workloads require, and record which capabilities can be added later.
2. How will cloud resources and workloads be organized?
Choose provider-native boundaries for ownership, policy inheritance, isolation, and cost allocation. Decide where shared platform responsibilities end and workload-team responsibility begins. A hierarchy that is easy to explain and automate is generally more useful than one that mirrors every department or technical component without a governance reason.
- Define organization-level ownership and billing ownership.
- Choose account, subscription, project, folder, organizational-unit, or management-group boundaries as appropriate to the provider.
- Decide how production, non-production, sandbox, and restricted workloads will be separated and which policies each inherits.
- Establish naming, tagging or labeling, and ownership metadata conventions that support inventory, operations, and cost allocation.
- Document how workload environments are requested, created, changed, and retired.
Keep the provider terms distinct: Azure uses management groups and subscriptions and separates platform landing zones from workload landing zones; AWS Control Tower organizes accounts and organizational units; Google Cloud uses an organization, folders, projects, and billing structures. These are not interchangeable names for the same implementation.
3. Who and what can access the environment?
Design human and workload access together. A secure account hierarchy is not enough if identities are unmanaged, permissions are excessive, or machine credentials cannot be revoked reliably.
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- Decide whether cloud access will federate with the organization’s identity provider, including single sign-on where appropriate.
- Define human roles, privileged access, emergency access, and joiner, mover, and leaver procedures.
- Define workload identities and their permissions separately from human identities.
- Restrict who can create accounts or projects, alter organization-wide policy, change shared network controls, and access centralized logs.
- Set a schedule and owner for reviewing access, including privileged roles and emergency credentials.
- Prefer short-lived or federated credentials for workloads where practical. Google Cloud security guidance recommends restricting service-account key creation for most use cases and considering service-account impersonation or workload identity federation. Document an exception path for integrations that cannot use the preferred approach.
4. How will networks and connectivity work?
Decide how each workload reaches shared services, the internet, on-premises systems, and other cloud environments. Assign clear responsibility for addressing, routing, DNS, firewall rules, segmentation, ingress, and egress so that connectivity changes are reviewable rather than informal.
- Select a topology and record its trust boundaries and allowed traffic flows.
- Choose whether connectivity and network services are centralized or managed by workload teams, and define how changes are reviewed and monitored.
- Specify how private name resolution, outbound internet access, inbound exposure, and hybrid connections will be handled.
- Define the process for exceptions to network policy, including who approves them and how they are reviewed.
Reference patterns differ by provider. Azure guidance includes hub-and-spoke and Virtual WAN. AWS guidance discusses services such as Transit Gateway, Direct Connect, and Site-to-Site VPN. Google Cloud describes Shared VPC, Cloud NAT, Cloud Interconnect, Cloud VPN, and private DNS options. Select patterns based on the required connectivity and operating model; the product names are not interchangeable.
5. Which security and governance controls apply?
Set a baseline that states what is required, how compliance is checked, and who responds when a control fails. Separate preventive controls that block an action from detective controls that identify a condition after it occurs; name an owner for each.
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- Decide which regions and services are permitted and how public exposure is controlled.
- Define relevant requirements for encryption, identity permissions, and resource configuration.
- Specify how misconfiguration and security threats are detected, triaged, and escalated.
- For every exception, record the approver, rationale, review or expiry date, and any required compensating control.
- Map provider controls and services to the governance and audit outcomes they are meant to support; do not assume a service name alone proves a requirement is met.
Provider implementation details matter. AWS landing-zone guidance covers preventive, detective, and proactive controls and discusses Control Tower, CloudTrail, and AWS Config in its governance and audit design. Google Cloud security guidance identifies Security Command Center, centralized audit logs, and VPC Service Controls as examples, while cautioning that perimeter controls bring operational complexity and must fit the use case. Azure implementation choices should be documented across the relevant identity, policy, security, and management design areas.
6. What will be logged, monitored, and operated?
Make logs useful for investigation and operations, and protect them from unauthorized alteration or deletion. Decide which activity is collected, where it is stored, who can access it, and how long it is retained according to business and regulatory requirements.
- Choose the administrative, network, workload, and security events to collect.
- Define centralized log storage where appropriate, along with access, change, deletion, and retention controls.
- Build dashboards and alerts for actionable conditions, and assign named responders and escalation routes.
- Set owners and processes for configuration inventory, drift detection, incident response, patching, and cloud service health.
- Document how monitoring signals become an incident or remediation task, rather than leaving alerts without an operational owner.
AWS design guidance explicitly addresses centralized logging and monitoring, log archiving, alerting, and AWS Config. Google Cloud lists monitoring and logging as foundation elements and recommends dashboards and alerts for actionable exceptions.
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7. How will data be protected and workloads recovered?
Determine obligations before selecting regions or controls. For each workload class, document what must be protected, who controls the keys, and what recovery means in practice.
- Identify applicable regulatory, contractual, and internal requirements.
- Decide encryption and key ownership, secrets handling, and which data and systems are included in backups.
- Set retention and recovery objectives appropriate to each workload rather than applying one assumed value across the environment.
- Assign responsibility for restoration and schedule restoration tests that demonstrate the recovery process works.
- Make compliance evidence and control ownership discoverable to the people who need to verify them.
Google Cloud’s landing-zone overview includes backup and disaster recovery, compliance, and workload-specific requirements among the design considerations. Provider defaults should not be treated as proof that an organization’s own obligations are satisfied.
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Cloud cost and provisioning need owners just as much as security does. Decide how teams receive environments and shared capabilities, and make it possible to attribute spend to the people responsible for it.
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- Assign billing access and budget ownership; define cost allocation labels or tags and a review cadence.
- Set budgets or alerts and identify who investigates unexpected spend.
- Document how a workload team requests an environment and how shared platform capabilities are made available.
- Choose a controlled change process, including review and versioning, for the foundation.
- Consider infrastructure as code and CI/CD or GitOps when they fit team capability and operating needs; they can support repeatable deployments and consistent application of internal guidelines but are implementation choices, not universal prerequisites.
Google Cloud recommends considering infrastructure as code for repeatable, modular deployments and CI/CD or GitOps for applying internal guidelines. Microsoft says its landing-zone accelerators use infrastructure as code. Select an approach the organization can maintain rather than adopting automation without an owner.
How do the provider approaches differ?
Compare the choices that affect isolation, ownership, operations, and workload fit—not merely service names.
| Provider | Foundation and hierarchy | Architecture emphasis | Design questions to resolve |
|---|---|---|---|
| Azure | Multi-subscription environment; platform landing zones and workload landing zones, with management groups and subscriptions. | Centralized governance, security, and shared capabilities alongside workload-team environments; reference network patterns include hub-and-spoke and Virtual WAN. | Which services belong to the platform, how subscriptions inherit policy, and how workload teams consume shared capabilities. |
| AWS | Multi-account environment organized around accounts and organizational units, including through AWS Control Tower. | Account structure, preventive/detective/proactive controls, networking, authentication and authorization, centralized logging and monitoring, and configuration management. | How accounts and OUs map to ownership and isolation, which controls are centrally applied, and who operates audit and log services. |
| Google Cloud | Modular foundation using an organization, folders, projects, and billing structures. | Identity provisioning, resource hierarchy, network, and security controls, with logging, monitoring, backup, disaster recovery, compliance, and cost considered as needed. | Which modules the initial workloads need, how shared networking and policy are managed, and which enterprise-scale controls are proportionate to the team and use case. |
These distinctions follow the providers’ landing-zone guidance: Microsoft Learn’s Azure landing-zone framework and design areas, AWS’s landing-zone design guide, and Google Cloud’s landing-zone overview and security guidance. Their documentation evolves, and each architecture must still be fitted to the organization’s workload, compliance, and operating requirements.
What order should you use to implement the checklist?
Use the decisions above to sequence implementation so foundational dependencies are settled before workloads rely on them.
Quick Recap
- Agree scope and owners. Identify the first workloads, their environments and obligations, and the people accountable for shared and workload services.
- Approve hierarchy and access. Define resource boundaries, policy inheritance, identity integration, privileged roles, and workload identity patterns.
- Establish connectivity and guardrails. Approve network boundaries and flows, then define baseline controls and the exception path.
- Make operations and recovery actionable. Configure the required logging, alert ownership, configuration management, backup, and restoration process for the workloads in scope.
- Enable governed delivery and cost review. Define environment provisioning, change control, cost allocation, and budget ownership before expanding adoption.
- Revisit the design as requirements change. Add modules or stronger controls when a new workload, risk, regulation, or operational need warrants them; record why the design changed.
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