#qaas

Quantum-as-a-Service Agreement Drafting: Legal and Technical Considerations.

Quantum-as-a-Service Rise

Quantum computing (QC) could revolutionize materials science, optimization, and cryptography when it enters commercial use. Due to the exorbitant cost and technological complexity of maintaining qubits, most organizations and individuals will not own quantum computers. Third-party “Quantum-as-a-Service” platforms will provide this technology.

QaaS is a remote access service model that uses a subscription or “pay for what you use” pricing structure like SaaS and IaaS. Therefore, QaaS contracts start with stipulations included in SaaS and IaaS agreements. Legal experts must recognize that QaaS is very different from quantum computing methodologies and infrastructure.

Because quantum computing is experimental and unstable, especially in its early stages, lawyers must address its risks while creating or negotiating QaaS agreements.

Unique Quantum Technical Issues

Quantum infrastructure requires certain contractual limits due to its technicalities:

Developing and Maintaining Hardware

Quantum computing hardware is continually evolving, unlike regular computer hardware, which is well-researched and governed by international standards. QaaS firms build quantum computers using superconducting qubits, ion traps, and neutral atoms.

If the hardware design or maintenance is faulty, quantum computing services will be worth much less. Thus, QaaS agreements may require quantum computer development and maintenance language.

Error and Volatility Management

Quantum information is subject to the no-cloning theorem because qubits are highly vulnerable to ambient noise. Due to these considerations, quantum computing error detection and repair is challenging. SaaS contracts often declare that services are not “error-free,” but using this generic disclaimer to QaaS may allow the service provider to eliminate most responsibilities.

Instead, users should seek for contractual provisions to ensure that problems are kept below set limits and that the service provider takes proactive steps to fix them.

Record-keeping and storage limitations

Quantum information requires error-prone, short-lived quantum memory. The industry is creating topological qubits to stabilize quantum hard drives, which are not yet available. This necessitates customized contract terms, which puts into question SaaS audit and record keeping obligations and regulatory compliance.

Important Negotiation Hotspots

Beyond technology risks, QaaS agreements must be carefully negotiated for economic and operational factors that often violate SaaS norms.

Service Level Agreements

Meet SLA standards is very difficult. Customers may want 99.9% SaaS uptime, but quantum computing systems may not be able to deliver. QaaS contracts can involve shared risk for quantum technology's environmental and infrastructure challenges.

Pricing and Support Obligations

Pricing is difficult since consumers demand stable costs and expect rates to decline as quantum technologies grow cheaper. However, service providers may seek to boost prices due to the risks and expenses of maintaining pricey and space-intensive technology. Support agreements must also differ from normal SaaS contracts to incorporate hardware support.

Secure, compliant, and evolving regulatory risks

Hybrid quantum systems and immature regulations make legal compliance difficult.

Hybrid System Cybersecurity

While QaaS firms use quantum computers as hardware, they store and analyze consumer data using standard computing platforms. Traditional methods may use current encryption (ECC or RSA). Customers may worry about the long-term exposure of sensitive data shared and stored using these standards.

Customers can seek post-quantum or quantum-safe cryptography standards for classical components or a roadmap for future adoption. Since quantum-safe approaches are still evolving, providers may protest to such restrictions, citing performance or compatibility issues.

The Export Control

Clients and service providers must actively monitor QaaS hardware, software, and technology export rules. A foreigner's domestic system access may be an export. Providers can restrict access to export-controlled infrastructure, require exit clauses, or require client guarantees for QaaS-created technologies. In response, customers might limit data storage regions.

Allocating Changing Compliance Costs

Quantum computing laws and regulations, including as export controls and cybersecurity standards, are being established. Compliance requires constant commitment and adaptability. Contracts must clarify who pays for changing compliance requirements and costs.

Setting the Future Course

Quantum computing is difficult and developing swiftly, thus it's important to draft carefully and understand the technology. Lawyers must create new frameworks and reject SaaS contract templates.

Collaboration, like vested contracting, where parties agree on goals and results can be beneficial. This strategy lets parties add flexibility to their contracts, making them more useful and durable as technology progresses. Vesting contracts helps with shared challenges like adapting to new regulatory standards instead of viewing compliance as a one-sided job.

T-Systems' QaaS shows how cloud-based, flexible consumption models with scalability and security are making infrastructure available. These services often integrate multi-quantum computing hardware and multi-cloud settings with artificial intelligence, machine learning, cloud services, and high-performance computing to give clients an easy and profitable entry point.

In today’s fast-paced software delivery landscape, speed is the new currency. Teams are expected to push new features and fixes to production multiple times a day. CI/CD pipelines make this possible, but speed without safety (quality checks) is like driving a sports car with no brakes. 

Even mature DevOps teams still encounter high-severity incidents and outages. Insights from the 2024 State of DevOps Report by the DORA team highlight that elite performers deploy more frequently than average, but failures still occur unexpectedly. In production, a simple error can cost millions in downtime and erode user trust. 

So why do production incidents persist in this highly automated era?  

Often, it comes down to how quality is managed. Traditional QA tends to be reactive, discovering issues only after they surface. A more modern shift is underway: treating quality as a service, not just a stage. 

That’s where Quality-as-a-Service (QaaS) frameworks become transformative. They’re not just tools or test suites; they’re architectural and cultural systems built for predictive, proactive quality controls embedded throughout the delivery pipeline. 

Why Outages Still Happen in Mature DevOps Environments?

Many teams assume that once they’ve invested in automation, monitoring, and CI/CD, failures will become rare. Unfortunately, the complexity of modern systems often outpaces the safeguards. 

Here are some of the most common reasons: 

1. Rising System Complexity As applications evolve into distributed microservices, they depend on hundreds of interconnected APIs, databases, and infrastructure components. This web of dependencies can mask potential failure conditions until they appear under production traffic.

2. Blind Spots in Monitoring Dashboards typically track known metrics like response times, CPU usage, and error counts, but subtle anomalies like memory leaks or race conditions only appear under specific circumstances. 

3. Pressure to Ship Faster Business demands push teams to shorten test cycles or run only the “essential” checks. Automation runs, but exploratory testing, which often catches unexpected behaviour, gets sidelined. 

4. Dependency Volatility Even if your code is perfect, a breaking change in a third-party service, an upstream API, or an open-source library can cause outages overnight. 

5. Ownership Gaps In some organizations, the team writing the code isn’t entirely responsible for operational stability. This slows down root cause analysis and remediation when incidents happen. 

What Are QaaS Frameworks?

QaaS (Quality-as-a-Service) is an approach where quality checks are packaged as reusable, independent services that can be invoked at any stage of your pipeline. Instead of QA being a siloed phase at the end, QaaS frameworks integrate multiple layers of verification into the entire delivery cycle. 

Key characteristics of a QaaS framework: 

1. Predictive Risk Scoring – Uses historical data, code changes, and operational metrics to flag potentially risky releases before they go live. 

2. Service-Like Quality Gates – Acts like plug-and-play microservices, running checks for performance, security, compliance, and functionality. 

3. Developer Self-Service – Engineers can trigger quality modules on demand, without waiting for centralized approval. 

4. Continuous Learning – Feedback from production incidents feeds into the scoring model, making it smarter over time. 

This modular approach means teams can scale quality enforcement without slowing down innovation. 

Also, read QaaS vs. Traditional QA: Which One is Better 

How QaaS Predicts and Prevents Release-Level Failures? 

An efficient QaaS framework goes beyond pass/fail testing; it predicts potential failures and prevents them from impacting production through multi-layered defense. 

Here’s how it works: 

1. Data-Driven Risk Profiling - Every release is evaluated against historical incident patterns, code churn levels, test coverage, and infrastructure health. A “release readiness score” is assigned. 

2. Canary Deployments with Deep Monitoring - Releases are pushed to a small, controlled environment that mirrors production. Performance, error rates, and unusual patterns are closely tracked. 

3. Security Gates - QaaS modules run vulnerability scans, license checks, and compliance validation before a build is promoted. 

4. Chaos Engineering - Chaos Engineering is the practice of injecting-controlled failures like outages, latency spikes, or resource exhaustion to reveal system weaknesses before users are impacted. The goal isn’t random breakage but building resilience.    Its core principles include: 

Define steady state – Know what “normal” looks like (latency, error rates, throughput). 

Form a hypothesis – Predict how the system should behave under stress. 

Inject realistic failures – Simulate outages, traffic surges, or resource limits. 

Test safely in production – Run controlled experiments with safeguards. 

Automate & monitor – Repeat continuously and learn from results. 

Limit the blast radius – Contain impact to a small scope.   

By following these principles, teams shift from firefighting to proactive resilience, using chaos experiments in CI/CD pipelines to ensure stability under real-world stress. 

5. Health-Based Rollbacks – If production rollout metrics breach predefined thresholds, the QaaS system can auto-rollback changes without human intervention. 

Also, read Why Is QaaS the Future of Scalable QA Solutions 

Embedding Quality Gates into CI/CD Pipelines

Integrating QaaS involves the strategic placement of quality gates. Here’s how a typical pipeline might look: 

1. Pre-Commit Stage - Developers run lightweight QaaS modules, linters, unit tests, and static checks locally. Predictive scoring can be triggered for high-risk features. 

2. Build Phase - Upon merge, the pipeline triggers complete test suites, security scans, performance benchmarks, and quality scoring. Builds that fail are blocked from advancing. 

3. Staging / Canary - Deploy to a limited production-like environment. Chaos modules inject failure scenarios while performance is stress-tested. 

4. Production Rollout - Live metrics are closely monitored against SLOs. Any anomaly triggers an automatic halt or rollback. 

5. Post-Deployment Feedback Loop - Real-world telemetry is fed back into QaaS analytics to refine future scoring model. 

Also, read Is QaaS the Future of Regulatory-Ready QA? 

Use Case: How a GenAI Workflow Can be Protected by a QaaS Strategy

Consider a startup, GenPromptAI, which updates its large language model daily to improve customer support accuracy. While this keeps the product fresh, it also risks introducing regressions in quality and speed. 

QaaS Implementation: 

1. Model Accuracy Testing – Benchmark prompts measure factual correctness and hallucination rates before promotion. 

2. Latency Checks – Canary deployments run performance tests under peak load. 

3. Synthetic Load Simulation – QaaS modules mimic sudden traffic surges to verify auto-scaling behavior. 

4. Continuous Feedback – User feedback and human-reviewed samples feed into the risk model. 

5. Automated Rollback – If latency exceeds a predetermined timeframe or accuracy drops below thresholds, QaaS halts deployment instantly. 

Outcome:  The company can maintain up to 99.95% uptime while shipping daily model updates—a stability level difficult to achieve without proactive quality enforcement. 

Building a Scalable, Multi-Layered QaaS Framework

If you’re considering QaaS, here’s a practical roadmap: 

1. Define Quality Metrics – Decide what “good” looks like in performance, security, and compliance. 

2. Modularize Checks – Build independent services for each quality domain. 

3. Centralize Orchestration – Use a workflow engine to run QaaS modules in sequence. 

4. Enable Machine Learning – Let the system learn from past successes and failures. 

5. Empower Developers – Give engineers tools to run checks anytime. 

6. Iterate and Improve – Regularly review thresholds and incident reports to refine the framework. 

Also, read QaaS Enhances ServiceNow ATF Testing Outcomes 

Conclusion 

Even with advanced CI/CD and DevOps maturity, outages remain a threat. Complexity, dependency volatility, and the speed of modern releases mean that traditional QA isn’t enough. 

QaaS frameworks address this by making quality proactive, predictive, and embedded at every stage of delivery. They transform testing from a single phase into a continuously running service that learns and adapts over time. 

Whether you’re managing a microservices platform or deploying cutting-edge GenAI models, adopting a QaaS mindset can be the difference between a smooth release and a midnight outage. In an era where user patience is short and competition is fierce, building for zero-defect deployments isn’t just an advantage, it’s survival. 

At inMorphis, we help enterprises embed proactive quality frameworks like QaaS into their DevOps pipelines, balancing speed with resilience. If you’re looking to minimize release risks while accelerating innovation, our team can guide you in building scalable, defect-resistant delivery models. 

Reference:

inMorphis operationalizes ServiceNow’s Value Realization Framework by aligning KPIs, OKRs, and platform performance metrics with business outcomes. We build tailored dashboards, enable real-time tracking, and ensure that platform adoption translates to measurable ROI at every phase. 

Read More Information:

As we delve further into this book, we will take an in-depth look at what QaaS technology means and why it is fast becoming an often preferred option among many organizations. We will then determine the benefits and practical implementations of QaaS, running the gamut from automated testing to integration with DevOps practices. We will then discuss the challenges that companies may face by adopting this technology and the key considerations to be kept in mind in doing so. By the time you have finished reading this article, you will come to understand what QaaS is and how it is evolving in the technological world in the context of quality assurance.

What does the term QaaS Technology mean?

QaaS technology, or Quantum-as-a-Service, is a new approach changing the game in this field of computing. It further propels the move to make quantum computing more accessible and stands at the front lines of this movement: it is just the service model that provides access to quantum computing over the cloud to run quantum algorithms and perform complex computations without expensive quantum hardware.

Definition and Key Concepts

QaaS is fundamentally about making quantum computing more accessible and democratized. It describes the paradigm of cloud computing, which is to make available computing power as a service over the internet. This opens up quantum computing capabilities to researchers, developers, and enterprises without having to invest in and maintain its quantum infrastructure.

QaaS is not only an access tool to a quantum processor. It usually contains a package of services, including high-level interfaces and development tools for testing quantum algorithms. It is thereby especially easy for users to explore quantum computing and integrate it into their work.

History of QaaS

It’s interesting to think through QaaS’ journey so far. Quantum computing has been a focus area for tech companies since 2000 with consistent progress toward achieving what is called the “quantum advantage,” that is, the point where quantum computers can solve problems no feasible simulation can solve on a classical computer in a reasonable time.

This implies that as QaaS evolves, so does the diversity of offerings available through the framework of this science. As such, the current options are availed in terms of quantum computing services, which include the superconducting modalities through platforms such as IBM Quantum and Rigetti Quantum Cloud Services. Other service providers include Leap Quantum Cloud Service, which offers quantum annealing through D-Wave Systems, while photonic devices are availed using Xanadu Cloud.

What are your top five favorite actors?

Benedict Cumberbatch, Martin Freeman, Tom Hanks, Brian Holden, David Tennant

How would you like to spend your Saturday if money and time weren’t an issue?

I'd like to go to an art museum and then a large field where I can lay to look at clouds.

Would you ever go on a cross-country trip? and what country?

Visiting the beautiful forests in Russia would be nice. I'd also love to go to the red light district in Amsterdam.

Where do you feel the most safe?

Up high away from crowds.

Who is your favorite Harry Potter character(not including Harry, Ron or Hermione)?

I really love Remus and James. Molly as well.

Is there someplace in the world that you have been and never want to go back to? If so, where and why? 

During the stretch of time where my mother, sister and I were homeless, we stayed with this one man for a few nights. I never want to go back there for a few reasons.

Do you believe in the paranormal and why or why not? 

I'd like to. I think it links up with space and sience and such. Astrophysics and constant energy and dark matter and the like.

Are you pessimistic or optimistic? 

Why can't anyone just be mistic?

Do you have someone that you feel that you couldn’t function without? 

Yes.

What is your biggest fear(that you don’t mind sharing)? 

You know that feeling in dreams sometimes where you try to speak but you can’t, and you feel like you have cotton shoved in your mouth and you can only muffle out cries and no one can hear you? That.

What is your favorite band/song?

Thanks Annie!

1. Hi! Give me a quick seven word synopsis of yourself. It doesn’t have to be a sentence, it can just be adjectives.

Still the only one in the world

2. What’s your favorite color and why?

White because it is so naive. 

3. Do you enjoy roller coasters?

Very much so! Being so tall I was able to go on all of Disney's rides at age 4.

4. Are you the romantic type, or not so much?

Not at first. But after confirmed commitment from the other person, very much so (but more in a possessive way.)

5. Who’s your favorite pony? Why?

Probably Fluttershy. I mean, I love each of the main six but there's something about how she handles situations that is different from the others and very endearing.

6. What’s your dream career as opposed to your intended one? Are they the same?

My dream career is Batman so... My intended career is to be a cosplay and event photographer.

7. What is oddest dream you’ve ever had? Describe it.

Well, it's funny you should ask. I had a sex dream about my best friend last night. It was odd on many parts, such as the fact that I have a girlfriend and this friend is like my sister and we could never think of each other like that oh god no.

8. Dogs or cats?

Cats. 

9. What do you love more than anything else in this world?

My little sister. She is the first person I would die for.

10. If you had the opportunity to look in the book or records and find out your death day- given you wouldn’t create any paradoxes in changing it, would you take it?

Of course. 

11. What is your biggest fear?