Cloud SLA Comparison Guide for Indian Businesses

Do not compare cloud providers only by the advertised uptime percentage.

Compare SLAs across six areas:

1. Uptime percentage
   What uptime is promised: 99.5%, 99.9%, 99.95%, 99.99% or higher?
2. Scope of coverage
   Does the SLA cover compute, storage, network, database, GPU, Kubernetes or the full platform?
3. Architecture requirement
   Does the SLA apply to a single instance or only to multi-zone, multi-node or highly available deployments?
4. Downtime definition
   How does the provider define downtime, unavailability and measurement window?
5. Service credits
   What credit do you get when SLA is missed, and do you need to claim it manually?
6. Business impact
   Does the SLA match your revenue risk, customer expectation and recovery requirement?

The best cloud SLA is not just the highest uptime number. It is the SLA that clearly matches your workload design, support expectations and business risk.

This guide is useful for:

• CTOs choosing cloud infrastructure for production workloads
• Founders comparing Indian and global cloud providers
• SaaS teams selling uptime commitments to customers
• DevOps and platform teams planning high availability
• Fintech, healthcare and ecommerce teams with uptime-sensitive systems
• Procurement teams comparing cloud contracts
• AI startups running GPU workloads in production
• IT leaders reviewing cloud migration risk
• Engineering managers evaluating disaster recovery plans

This guide is not a legal review of provider contracts. It is a practical cloud buying guide to help teams ask better SLA questions before committing.

A cloud SLA, or Service Level Agreement, is a provider’s formal commitment around service availability, performance, support response or service credits.

Most cloud SLAs answer questions like:

• What uptime does the provider commit to?
• Which service does the SLA cover?
• How is downtime calculated?
• What happens if the provider misses the SLA?
• What exclusions apply?
• How can customers claim service credits?
• Which configurations qualify for the SLA?

In cloud buying, an SLA is useful because it shows how the provider defines reliability. But an SLA does not guarantee that your application will never go down.

Your application availability depends on your full architecture, including:

A provider SLA is only one layer of overall reliability.

These terms are related but not identical.

A cloud provider may meet its infrastructure SLA while your application still faces downtime because of database issues, deployment errors, application bugs or poor failover design.

That is why buyers should evaluate application availability, not only provider uptime.

Small-looking uptime differences can mean large downtime differences.

Approximate downtime allowed:

This is why the difference between 99.9% and 99.99% matters for production workloads.

But the higher number is useful only when:

• Your architecture qualifies for it
• All critical dependencies support similar reliability
• Failover is tested
• Monitoring works
• Recovery process is documented
• Support is responsive
• The business case justifies the cost

A 99.99% provider SLA does not automatically create 99.99% application uptime.

The headline SLA number can mislead buyers for several reasons.

1. SLA May Apply Only to Specific Services

A provider may advertise high uptime for compute, but your workload may also depend on:

Each service may have a different SLA.

If one critical dependency has a lower SLA, your application availability may be lower than expected.

2. SLA May Require High-Availability Architecture

Some SLAs apply only when workloads are deployed across multiple zones, multiple instances or specific configurations.

For example, a single VM may not qualify for the same availability level as a multi-zone deployment.

So before comparing SLA numbers, ask:

• Does this SLA apply to a single instance?
• Does it require multiple instances?
• Does it require multiple availability zones?
• Does it require provider-managed failover?
• Does it require load balancing?
• Does it require replicated storage?
• Does it require a specific disk or storage class?

3. Service Credits Are Not Full Compensation

A service credit usually means the provider gives back a portion of the monthly service fee.

It usually does not cover:

A 10% credit on a cloud bill may be tiny compared with the business impact of downtime.

4. Credits May Not Be Automatic

Many providers require customers to submit a claim within a defined period.

If your team does not track downtime, collect evidence and submit a claim properly, you may not receive credits even when the SLA is missed.

5. Exclusions Can Be Broad

Cloud SLAs often exclude downtime caused by:

• Scheduled maintenance
• Customer misconfiguration
• Application bugs
• Force majeure events
• Abuse or policy violations
• Unsupported configurations
• Third-party services
• Network issues outside provider control
• Customer failure to follow best practices

Read exclusions carefully before relying on SLA claims.

For Indian buyers, SLA comparison should include legal, operational, billing and support factors.

1. Uptime Commitment

Ask:

• What uptime percentage is promised?
• Is it monthly or annual?
• Does it apply per region, per service or per instance?
• Does the provider publish the SLA publicly?
• Is the SLA included in the contract?

2. Eligible Services

Ask:

• Does the SLA cover compute?
• Does it cover VPS?
• Does it cover GPU cloud?
• Does it cover object storage?
• Does it cover block storage?
• Does it cover managed databases?
• Does it cover Kubernetes?
• Does it cover load balancers?
• Does it cover network services?

A cloud service with no explicit SLA may still be useful, but it should not support critical production workloads without risk review.

3. Architecture Conditions

Ask:

• Does the SLA require multiple nodes?
• Does it require multiple zones?
• Does it require redundant storage?
• Does it require a load balancer?
• Does it require managed failover?
• Does it require specific backup settings?
• Does it require customer-side configuration?

This is where many teams misunderstand SLAs.

4. Downtime Definition

Ask:

• What counts as downtime?
• Is partial degradation included?
• Is high latency included?
• Is packet loss included?
• Is control panel downtime included?
• Is API downtime included?
• Is region-wide outage treated differently?
• Is downtime measured by provider monitoring or customer evidence?

A service can be technically “up” but still unusable for customers because of latency, packet loss or degraded performance.

5. Service Credit Terms

Ask:

• What credit is offered if SLA is missed?
• Is the credit 5%, 10%, 25%, 50% or more?
• Is there a maximum cap?
• Is the credit automatic?
• What evidence is required?
• What is the claim deadline?
• Is the credit cash refund or account credit?
• Does credit apply to only the affected service?

For finance teams, this matters because service credits rarely match business losses.

6. Support Response

Ask:

• Is support SLA separate from uptime SLA?
• What is the response time for critical incidents?
• Is 24/7 support included?
• Is phone support available?
• Is chat support available?
• Are escalation paths defined?
• Is there an enterprise support plan?
• Does support cost extra?

High uptime claims are less valuable when support response is slow during incidents.

7. Maintenance Policy

Ask:

• How is scheduled maintenance communicated?
• How much notice is provided?
• Does maintenance count as downtime?
• Can maintenance windows be customised?
• Are updates rolling or disruptive?
• Are GPU and bare-metal systems treated differently?

This is especially important for VPS, GPU servers, managed databases and Kubernetes platforms.

8. Data Durability

Availability and durability are different.

Availability means users can access the service. Durability means stored data is not lost.

Ask:

• What durability is promised for object storage?
• How are disks replicated?
• Are snapshots included?
• What happens during storage failure?
• Are backups customer-managed or provider-managed?
• Is restore time guaranteed?

A provider may offer good uptime but weak backup or restore guarantees.

Different cloud services need different SLA questions.

VPS and Virtual Machines

For VPS and VM workloads, check whether the SLA applies to one instance or only redundant deployments.

Ask:

• Is a single VPS covered?
• Does the SLA require multiple instances?
• Does the SLA include attached storage?
• Is public network availability included?
• Is control panel access included?
• Are planned maintenance windows excluded?
• How are host failures handled?

For production applications, one VPS is rarely enough for high availability.

GPU Cloud

GPU cloud SLAs need extra care because GPU capacity can be limited.

Ask:

• Is GPU instance uptime covered?
• Is GPU availability covered?
• Is quota availability guaranteed?
• Are driver issues covered?
• Are failed GPU allocations covered?
• Is bare-metal GPU maintenance covered?
• Is support available for CUDA and driver issues?
• Are long-running training jobs protected from interruption?
• Are spot/preemptible GPU instances excluded?

For AI production workloads, capacity assurance may be as important as uptime.

Object Storage

Object storage should be evaluated for both availability and durability.

Ask:

• What is the availability SLA?
• What durability is claimed?
• Is region selection available?
• Is replication optional or default?
• Are retrieval delays covered?
• Is API availability covered?
• Are lifecycle transitions covered?
• Is data deletion or corruption covered?

Object storage often holds backups, images, datasets and logs. Weak storage planning can break recovery even if compute uptime is strong.

Block Storage

Block storage supports VMs, databases and stateful workloads.

Ask:

• Is disk availability covered separately?
• What happens if a volume becomes unavailable?
• Are snapshots covered?
• Are IOPS guarantees provided?
• Is performance degradation covered?
• Are backup and restore times guaranteed?

For databases, block storage performance can be as important as VM uptime.

Managed Databases

Managed databases need careful SLA review because they often become the most critical dependency.

Ask:

• Is the SLA for single-node or multi-node database?
• Is failover automatic?
• What is the expected failover time?
• Are read replicas covered?
• Are backups included?
• Is restore time guaranteed?
• Are maintenance windows disruptive?
• Are version upgrades covered?

Database availability usually determines whether the application is usable.

Managed Kubernetes

Kubernetes SLAs can apply to the control plane, worker nodes or both.

Ask:

• Is the control plane covered?
• Are worker nodes covered separately?
• Is etcd/control-plane availability guaranteed?
• Are node failures covered?
• Is cluster autoscaling covered?
• Are load balancers covered?
• Is persistent storage covered?
• Are upgrades disruptive?

A Kubernetes cluster can be technically running while workloads still fail because of node, storage or networking issues.

Load Balancers and Networking

Network services can affect all user traffic.

Ask:

• Is load balancer availability covered?
• Is public IP availability covered?
• Is packet loss covered?
• Is high latency covered?
• Is private networking covered?
• Is DDoS protection included?
• Are firewall rules covered?
• Are NAT gateway failures covered?

For ecommerce, SaaS and API platforms, networking issues can become customer-facing outages quickly.

CDN and DNS

CDN and DNS failures can make a healthy application unreachable.

Ask:

• Is DNS availability covered?
• Is CDN availability covered?
• Are edge locations covered?
• Is cache purge reliability covered?
• Are SSL certificate issues covered?
• Is origin connectivity covered?

DNS and CDN should be included in reliability planning, not treated as secondary tools.

Cloud uptime SLA and support SLA are different.

An uptime SLA says the service should be available. A support SLA says how quickly the provider responds to tickets.

For production workloads, both matter.

A provider may offer 99.99% uptime but only email support. Another provider may offer 99.9% uptime but faster human support and better incident handling.

Check support levels:

For small teams, fast support can sometimes matter more than a slightly higher SLA percentage.

Service credits are often misunderstood.

A service credit is usually a credit against future cloud bills. It is not usually a cash payout.

Example:

If your monthly bill for an affected service is ₹20,000 and the provider offers a 10% credit, you may receive ₹2,000 as credit.

But your business may have lost:

So service credits should be treated as accountability, not full protection.

Before signing, ask:

• What is the maximum credit?
• Is the credit based on affected service only?
• Are taxes included?
• Is the credit automatic?
• What evidence is needed?
• How quickly must the claim be submitted?
• Can credits be denied?
• Does the contract limit liability?

For critical workloads, your internal disaster recovery plan matters more than relying on service credits.

Your application availability depends on every critical component.

If your application depends on compute, database and storage, each layer affects the final availability.

A simplified way to think about it:

Application availability depends on the combined availability of all critical dependencies.

For example, if three critical services each have high availability, the combined availability may still be lower because all three must work together.

This is why teams should not assume:

Cloud provider SLA = Application SLA

Instead, review:

Your customer cares whether the application works, not whether one cloud service met its SLA.

Many SLA discussions focus only on uptime. But recovery targets are equally important.

RTO: Recovery Time Objective

RTO means how quickly you need to restore service after failure.

Examples:

• Internal test tool: RTO of 24 hours may be acceptable
• SaaS application: RTO of 1 hour may be required
• Payment system: RTO of minutes may be needed
• Healthcare system: very low RTO may be required

RPO: Recovery Point Objective

RPO means how much data loss is acceptable.

Examples:

• Analytics dashboard: a few hours of data loss may be acceptable
• CRM system: minutes may matter
• Payment system: data loss may be unacceptable
• Healthcare records: data loss can be serious

Cloud SLA tells you about availability. RTO and RPO tell you about recovery.

Before choosing a provider, define:

• How much downtime can we tolerate?
• How much data loss can we tolerate?
• How fast can we restore?
• How often do we test recovery?
• Who owns incident response?
• Which provider services support these targets?

Indian businesses should evaluate SLA in the context of local buying needs.

INR Billing and Credits

Ask:

• Are SLA credits issued in INR?
• Are credits adjusted against GST invoices?
• Are credits applied automatically?
• Are credits visible in the billing dashboard?
• Are USD-billed providers affected by exchange-rate movement?

For more billing detail, read the INR vs USD cloud billing guide.

Indian Data Centres

Ask:

• Does the provider offer India regions?
• Does the SLA apply to India regions?
• Are all services available in India?
• Are GPUs available in India?
• Are backups also available in India?
• Are disaster recovery regions available within India?

A provider may offer strong global SLAs but limited India-specific service availability.

Support Time Zone

Ask:

• Is support available during Indian business hours?
• Is 24/7 support included?
• Is escalation available in India?
• Are account managers available locally?
• Does support cover weekends and holidays?
• What happens during Indian festival seasons or bank holidays?

For Indian SaaS and ecommerce businesses, local support availability can reduce operational stress.

Customer Contracts

If your customers demand uptime commitments from you, your provider SLA should support your customer SLA.

Ask:

• What uptime do we promise customers?
• Does our provider architecture support that promise?
• Are we taking on more risk than the provider?
• Do we have a disaster recovery plan?
• Do we have monitoring evidence?
• Can we prove uptime to customers?

Never promise customers a higher SLA than your architecture can realistically support.

Use this checklist before choosing a cloud provider.

Provider SLA

• Is there a public SLA document?
• Is the SLA included in the contract?
• What uptime is promised?
• Which services are covered?
• Which regions are covered?
• What is excluded?
• What is the service credit?
• Is the credit automatic?
• What is the claim deadline?

Architecture Fit

• Does the SLA apply to single instance?
• Does it require multi-zone deployment?
• Does it require load balancing?
• Does it require managed database replication?
• Does it require replicated storage?
• Does it require customer-side monitoring?
• Does your architecture qualify?

Operations

• Is 24/7 support available?
• Is there a support response SLA?
• Are maintenance windows disclosed?
• Are outages communicated transparently?
• Is status page history available?
• Are incident reports provided?
• Are escalation paths clear?

Business Risk

• What is our cost per hour of downtime?
• What customer impact does downtime create?
• What internal team handles incidents?
• What is our RTO?
• What is our RPO?
• Do we need disaster recovery?
• Do we need multi-region architecture?

Score each provider from 1 to 5.

A provider with a high score on uptime but low score on support or architecture clarity may not be the best production choice.

Small Website or Blog

Recommended focus:

A very high SLA may not be necessary.

SaaS Startup

Recommended focus:

A SaaS startup should avoid relying on one VM for production.

Ecommerce Business

Recommended focus:

Downtime during sales campaigns can directly affect revenue.

Fintech or Payments Workload

Recommended focus:

Fintech workloads should review both provider SLA and sector-specific requirements.

AI Startup Using GPU Cloud

Recommended focus:

For AI workloads, interruption can waste expensive GPU hours.

Enterprise Application

Recommended focus:

Enterprise teams should connect SLA review with procurement, legal and security review.

Mistake 1: Comparing Only the Uptime Percentage

A 99.99% SLA sounds better than 99.9%, but it may require a more expensive architecture. Check conditions.

Mistake 2: Assuming SLA Covers the Full Application

Provider SLA usually covers specific services, not your entire application.

Mistake 3: Ignoring Database and Storage SLAs

Compute uptime is not enough if the database or storage layer becomes unavailable.

Mistake 4: Not Reading Exclusions

Scheduled maintenance, customer misconfiguration and unsupported setups may be excluded.

Mistake 5: Expecting Cash Compensation

Most SLA remedies are service credits, not cash payments.

Mistake 6: Not Tracking Downtime

If credits require a claim, you need monitoring evidence.

Mistake 7: Overpromising to Customers

Do not promise customers higher uptime than your provider setup and internal operations can support.

Mistake 8: Treating Backup as SLA

Backup protects data recovery. It does not automatically ensure service availability.

Mistake 9: Forgetting Support SLA

A strong uptime promise is less useful if incident support is slow.

Mistake 10: Not Testing Failover

Untested failover often fails during real incidents.

Step 1: Define Workload Criticality

Classify workloads as low, medium, high or mission-critical.

Step 2: Estimate Downtime Cost

Estimate revenue loss, support cost, customer impact and compliance risk per hour of downtime.

Step 3: Define RTO and RPO

Decide how fast service must recover and how much data loss is acceptable.

Step 4: Map Critical Dependencies

List compute, database, storage, DNS, CDN, network, GPU, APIs and third-party tools.

Step 5: Review Provider SLAs

Read SLA terms for each critical service, not only the homepage claim.

Step 6: Check Architecture Requirements

Confirm whether your planned deployment qualifies for the advertised SLA.

Step 7: Compare Support Plans

Check support response time, escalation, availability and cost.

Step 8: Calculate Total Reliability Cost

High availability may require multiple instances, load balancers, replicated storage, backups, monitoring and support plans.

Step 9: Test Failure Scenarios

Test instance failure, database failover, restore process, deployment rollback and provider support response.

Step 10: Document the SLA Decision

Keep a record of provider SLA, architecture design, failover plan, backup policy and monitoring approach.

Scenario 1: Startup Landing Page

A startup landing page can often tolerate short downtime.

Priority:

A complex high-availability setup may not be required.

Scenario 2: B2B SaaS Dashboard

A SaaS dashboard needs stronger reliability.

Priority:

The provider SLA should support the startup’s customer-facing uptime promise.

Scenario 3: Ecommerce During Campaign Season

An ecommerce company needs uptime during traffic spikes.

Priority:

The cloud SLA should be reviewed alongside application capacity planning.

Scenario 4: AI Training Workload

An AI team running long GPU training jobs needs job resilience.

Priority:

The cost of interruption may be measured in wasted GPU hours.

Scenario 5: Fintech Application

A fintech application needs stricter controls.

Priority:

Provider SLA should be matched with compliance and disaster recovery planning.

getInfra.cloud helps Indian buyers compare cloud providers beyond headline pricing.

You can use getInfra.cloud to:

• Compare Indian and global cloud providers
• Review VPS and GPU cloud pricing
• Check provider pages before shortlisting
• Compare providers side by side
• Understand hidden cloud costs
• Review INR vs USD billing risks
• Use cloud buying checklists before procurement

Useful pages:

• Cloud provider comparison
• GPU cloud pricing
• Cloud provider selection checklist
• Cloud pricing hidden costs guide
• INR vs USD cloud billing guide
• Data sovereignty cloud guide
• Methodology
• Data sources
• Corrections

Provider pages to review: