Capability
Cloud, AWS, Microsoft Azure, IaaS, PaaS & SaaS
Choosing and operating cloud service models around workload needs, security, resilience and cost discipline.
01 · Executive overview
Cloud is not one decision. IaaS, PaaS and SaaS shift different responsibilities to the provider, and AWS and Microsoft Azure offer comparable building blocks with different strengths. The right choice depends on the workload, existing investments, skills, security requirements and commercial terms.
Well-governed cloud adoption improves agility and resilience while keeping security exposure and spending under control.
02 · Technical and business scope
- AWS and Microsoft Azure architecture concepts.
- Hybrid-cloud integration with on-premises estates.
- Workload placement and migration assessment.
- Identity and access management.
- Security, resilience, monitoring and disaster recovery.
- Cloud cost allocation, tagging, budgets and optimization.
- Shared responsibility across cloud service models.
03 · Key technologies, frameworks & concepts
- Shared responsibility model.
- Landing zones and guardrails.
- Well-architected principles (reliability, security, cost, performance, operations).
- Migration strategies: rehost, replatform, refactor, replace, retain, retire.
- Tagging and cost-allocation standards.
04 · Typical enterprise challenges
- Unclear workload requirements before migration.
- Identity and security gaps across platforms.
- Resilience and recovery not designed in.
- Fragmented monitoring across cloud and on-premises.
- Cloud and SaaS spend growing without governance.
Cloud service models: IaaS, PaaS and SaaS
Each model moves a different share of responsibility from the organisation to the provider.
IaaS — Infrastructure as a Service
- Virtual machines and compute.
- Block, file and object storage.
- Virtual networking.
- Operating systems remain the customer's responsibility.
- Security of OS, data, identity and configuration stays with the customer.
- Scaling and right-sizing.
- Infrastructure cost management.
PaaS — Platform as a Service
- Managed application platforms.
- Managed databases.
- Integration and messaging services.
- Deployment models and pipelines.
- Platform governance and policies.
- Provider runs OS and runtime; customer owns code, data and access.
SaaS — Software as a Service
- Enterprise applications delivered as a service.
- Licensing and subscriptions.
- Identity and single sign-on.
- Integrations with other systems.
- Service availability and provider SLAs.
- Renewals and utilization reviews.
- Vendor management.
Shared responsibility: the further a workload moves from IaaS to SaaS, the more the provider operates — but data, identity, access and configuration always remain the organisation's responsibility.
05 · Decision-making & solution approach
Start from workload requirements, assess placement across on-premises, IaaS, PaaS and SaaS, compare AWS and Microsoft Azure options, define the operating model, design identity, security and monitoring controls, and govern cost from day one.
06 · Financial & operational considerations
- Cloud consumption and subscriptions are OPEX; reserved commitments change the cost profile.
- Include data transfer, support plans, monitoring and staff time.
- Use official provider calculators with real terms — no assumed prices.
- Track SaaS licence utilization before renewals.
07 · Governance, risks & dependencies
- Identity, data residency and regulatory requirements.
- Provider lock-in and exit planning.
- Network connectivity for hybrid workloads.
- Skills and operating-model readiness.
08 · KPIs & success measures
- Availability against workload targets.
- Cost per workload or business unit.
- Tagging and allocation coverage.
- Security policy compliance.
- SaaS licence utilization.
09 · Illustrative practical scenario
Illustrative demonstration — not a client engagement
Comparing on-premises infrastructure, IaaS, PaaS and SaaS for a business workload.
10 · Experience, knowledge & development
A connected career journey through enterprise technology environments, including Wipro, Aurobindo Pharma and NTT DATA: from building technical foundations and troubleshooting service issues, to owning service delivery, team coordination and operational governance, to connecting infrastructure, service performance, customer relationships, cost, risk and people development into business outcomes.
Professional experience
- Bringing operating responsibilities, security, resilience and cost governance into technology decisions alongside service outcomes.
- Evaluating workload placement and service-model responsibilities from a service-delivery and governance perspective.
Working knowledge
Working knowledge (not claimed as hands-on implementation) of IaaS, PaaS and SaaS models, AWS and Microsoft Azure service concepts, hybrid patterns and the controls needed to run them responsibly.
Learning in progress
- Microsoft Azure
- AWS architecture and cloud economics
Integrated knowledge map
From technology to business value.
Each layer builds on the one beneath it. Commercial, risk and people disciplines cut across every layer.
- 1Infrastructure & Data Center
- 2Cloud Platforms & Enterprise Applications
- 3ITSM, AIOps & Automation
- 4Service Delivery, MSPs & GCCs
- 5Governance, Leadership & Technology Economics
- Customer Success & Business Value
Cross-cutting — applied at every layer