Choosing between SaaS, PaaS, and IaaS comes down to the trade-off between control and convenience, your team’s capabilities, and how quickly outcomes need to be delivered. All three can coexist in one organization; the right fit varies by workload and maturity stage. Below is a clear, practitioner-focused guide to what each model offers, when to use it, and how to decide.
Quick definitions
- IaaS (Infrastructure as a Service): On-demand compute, storage, and networking managed by the provider; customers manage OS, middleware, runtimes, data, and apps. Highest control, most responsibility—closest to traditional IT, but elastic and pay-as-you-go.
- PaaS (Platform as a Service): Managed infrastructure plus OS, middleware, and runtimes for building and deploying apps. Developers focus on code and data; provider handles platform operations. Middle ground of control vs speed.
- SaaS (Software as a Service): Complete applications delivered over the internet. Vendor runs the app and underlying stack; customers configure and use. Fastest time-to-value, least operational overhead.
Who should pick what (by scenario)
- Need fastest business outcome with minimal IT lift (CRM, help desk, email, analytics dashboards): Choose SaaS—configure, integrate, and go live quickly.
- Building custom apps and APIs; want to ship faster without managing OS/patching (web/mobile backends, event apps, data services): Choose PaaS—focus on code, let the platform run it.
- Running specialized workloads or needing custom stacks (legacy migrations, specific OS/kernel needs, high-compliance isolation): Choose IaaS—maximum control with cloud elasticity.
Control vs convenience
- Control: IaaS > PaaS > SaaS.
- Operational burden: SaaS < PaaS < IaaS.
- Customization freedom: IaaS > PaaS > SaaS.
Typical responsibilities
- IaaS: Cloud provider manages data centers and virtualization; your team manages OS, middleware, runtime, data, and applications.
- PaaS: Provider manages infra, OS, middleware, runtimes; your team manages apps and data.
- SaaS: Provider manages everything; your team manages configs, users, and data usage policies.
Common examples
- IaaS: Virtual machines, block/object storage, VPC networking for custom stacks.
- PaaS: Managed app platforms, databases, and CI/CD environments for rapid dev/deploy.
- SaaS: Email, collaboration suites, CRM, support desks, analytics tools consumed directly by end users.
Cost and speed considerations
- Time-to-value: SaaS is fastest; PaaS accelerates dev cycles; IaaS may require more setup but can be cost-efficient for steady, well-optimized workloads.
- Cost model: All favor subscription/pay-as-you-go; IaaS spend correlates with resource use, PaaS adds platform fees for productivity, SaaS charges per user/feature tier.
- Hidden costs: IaaS needs more ops expertise; PaaS can limit low-level tuning; SaaS can introduce integration work and potential vendor lock-in.
Security and compliance
- Baseline: All models deliver managed security for their layer; your obligations increase as control increases (most in IaaS).
- Data governance: With SaaS, scrutinize data residency, export options, and audit logs; with PaaS/IaaS, ensure identity, network, and patching practices meet policies.
- Lock-in risk: Proprietary features and APIs increase switching costs—particularly in SaaS and some PaaS offerings.
Decision framework
Ask these questions and map answers to a model:
- Outcome urgency: Need value this quarter? Favor SaaS. Building a differentiating app? Favor PaaS (or IaaS if platform constraints block requirements).
- Team capabilities: Strong SRE/DevOps? IaaS is feasible. Lean team focused on features? PaaS/SaaS reduce ops toil.
- Customization needs: Unique runtime, OS-level control, or niche dependencies? IaaS. Standard web services? PaaS or SaaS.
- Compliance and data: Strict isolation or specialized controls? IaaS (or regulated PaaS). Data portability critical? Validate SaaS export and backup paths.
- Cost predictability: SaaS provides clearer per-seat costs; PaaS/IaaS need FinOps discipline to manage variable usage.
Blended strategy (most common in practice)
- Front-office: SaaS for CRM, marketing, HR, finance to minimize undifferentiated work.
- App delivery: PaaS for most net-new apps/services; use managed databases and CI/CD for speed.
- Specialized/legacy: IaaS for workloads needing OS/kernel tuning, custom networking, or stepwise modernization.
- Data platform: Mix PaaS databases/streaming with IaaS data lakes where needed; integrate with SaaS via APIs.
Pros and cons at a glance
- IaaS
- PaaS
- SaaS
How to pilot and decide (first 45–60 days)
- Week 1–2: Define the business outcome, security requirements, and data residency.
- Week 3–4: Run a small proof—SaaS for a department process; PaaS for a microservice; IaaS for a legacy workload replica. Instrument cost, latency, and ops effort.
- Week 5–6: Compare results against goals; assess lock-in and exit paths (exports, backups, infra as code). Choose the model per workload; document guardrails.
Bottom line
- Choose SaaS when speed and standardized capability matter most (and differentiation is in configuration and process).
- Choose PaaS when building custom apps fast with minimal ops is the priority.
- Choose IaaS when unique control, legacy constraints, or specialized performance/security needs require it.
Most businesses adopt all three—matching the model to the job—while maintaining strong identity, data, and cost governance across the stack