Linux of the cloud is OpenStack!

Recently, I have turned back to Linux [1] as I find it overwhelming to see the potential for what OpenStack [2]  has to offer to the community. Yes, in the world of the internet, Linux made a revolution by booting any OS on any Hardware. Similarly, I see only parallels with OpenStack and such open source tools, with respect to how these can scale the computing power in the cloud and beyond. This analogy describes far more reaching of any type of computing power, even needed with mechanics to thrive in the Quantum spaces. Hence, I am writing down here are few similarities I see that help support the open source nature of both technologies. The comparison highlights several key characteristics.

• Open Source: Just as Linux is a free and open-source operating system, OpenStack is an open-source cloud platform. This means its source code is publicly available, allowing for community collaboration, customization, and innovation.
• Foundation for Infrastructure: Linux serves as the foundation for many operating systems and applications. Similarly, OpenStack provides the foundational Infrastructure-as-a-Service (IaaS) layer for building and managing private and public clouds. It controls and orchestrates compute, storage, and networking resources.
• Flexibility and Customization: Linux offers immense flexibility and can be tailored to specific needs. OpenStack, with its modular architecture and numerous projects (components), also provides a high degree of flexibility, allowing organizations to build and customize their cloud environments to meet unique requirements.
• Vendor Neutrality: Linux is not tied to a single hardware vendor, promoting choice and avoiding vendor lock-in. OpenStack similarly aims for vendor neutrality, supporting multi-vendor hardware pools and allowing organizations to choose their preferred hardware and software components.
• Community-Driven Development: Both Linux and OpenStack benefit from large and active open-source communities that contribute to their development, maintenance, and support.

In essence, the analogy suggests that OpenStack provides an open, flexible, and community-driven platform for cloud infrastructure, much like Linux does for traditional operating systems. There will be a time when dominant cloud vendors like AWS, Google, and Microsoft, among others, assume a gatekeeper role for computing and dissolve their proprietary systems to OpenStack, as AT&T did with Unix, allowing Linux to become a powerful OS for over three decades since its invention. Red Hat [3] and Oracle [4], while settling scores themselves, the similarities will emerge for the benefit of end-users only. Ultimately, if the scientific community adopts OpenStack, industry players will follow suit. Hence, my Thesis is titled Elastic Intelligent Cloud Architecture for the academic community,[5] elucidating the frameworks that need strengthening. 

In the future, if AI holds features alongside OpenSource like OpenStack, why not Quantum Mechanics follow the same path? There is a lot of future work required to enable Quantum [6] as an open source to match and then to surpass its predecessors, like Linux, OpenStack. I welcome your comments and suggestions.

References

[1] Linux Foundation - Decentralized innovation, built with trust

[2] OpenStack: Open Source Cloud Computing Infrastructure

[3] Red Hat Announces Preview Version of Enterprise-Ready OpenStack Distribution

[4] Oracle announces Oracle OpenStack for Oracle Linux — and cooperation deal with Canonical seen as poking Red Hat

[5] Elastic Intelligent Cloud Architecture for the academic community,

[6] The Quantum Open Source Foundation

OpenStack could for quantum computing

 

Even though OpenStack does not directly manage quantum hardware, it can serve as the foundational classical infrastructure for a quantum cloud computing platform. In this article the several parameters that make the OpenStack cloud as fundamental model to extend techniques like quantamizing.

For example: 

Orchestration: An OpenStack-managed classical cloud can host the middleware and APIs that send quantum circuits to remote quantum processing units (QPUs).

Hybrid workloads: Many quantum problems are hybrid, meaning they require both classical and quantum processing. OpenStack could manage the classical portion of the workload, such as data preparation and post-processing, that runs alongside a quantum job.

Quantum simulators: Quantum simulators, which run on classical supercomputers, could be managed and made available to users through an OpenStack-based infrastructure. 

Distributed computing: In all computing requirements there is never a time one size fits for all. Coming to the way the resources discovered and distributed to only merge as qbits OpenStack cloud shall support a hybrd model.

OpenStack vs. Quantum Computing features  

Technology

An open-source suite of tools for building and managing classic cloud computing infrastructure.

An emerging technology that uses the principles of quantum mechanics (qubits, superposition, entanglement) to solve highly complex problems.

Primary Resources

Manages large pools of conventional compute (CPU/GPU), storage, and networking hardware.

Utilizes qubits, which can exist in multiple states simultaneously, to perform certain calculations exponentially faster than classical computers.

Use Cases

Deploying virtual machines and containers, managing storage, and running traditional enterprise and scientific applications.

Solving specialized problems in cryptography, drug discovery, financial modeling, and materials science.

Hardware

Runs on conventional server hardware, which can be virtualized.

Requires specialized hardware that often needs to operate in extreme environmental conditions, such as cryogenic temperatures.

Purpose of Information sharing for scaling organisations

 Information sharing is crucial for scaling an organization because it fosters collaboration, accelerates decision-making, and reduces inefficiencies. By breaking down silos and promoting a culture of transparency, organizations can leverage collective knowledge, improve performance, and achieve sustainable growth. [1, 2, 3, 4, 5, 6, 7]  

Here's a more detailed breakdown: 

1. Fosters Collaboration and Teamwork: 

• Breaking down silos: Information sharing ensures that teams and departments have access to the same information, preventing duplication of efforts and promoting a more unified approach. [3, 6]  

• Cross-functional collaboration: Open information exchange enables teams to collaborate effectively on projects, share expertise, and leverage diverse perspectives. [1, 8]  

• Building trust: Transparency in information sharing builds trust and strengthens relationships within the organization. [3]  

2. Accelerates Decision-Making: 

• Informed decisions: Access to relevant information allows leaders to make quicker and more informed decisions, leading to faster execution and better outcomes. [3, 9]  

• Reduced bottlenecks: Timely access to information streamlines processes and reduces bottlenecks, particularly in large organizations where information can be difficult to locate. [3, 6]  

3. Improves Efficiency and Productivity: 

• Reduced redundancy: When information is readily available, employees avoid spending time searching for it, leading to increased productivity. [3, 3, 6, 6]  

• Streamlined processes: Shared information can optimize workflows, identify areas for improvement, and enhance overall operational efficiency. [5, 5, 6, 6, 10, 11, 12]  

• Faster time to insights: Data sharing can accelerate the process of gaining insights from data, allowing organizations to identify trends, opportunities, and potential problems more quickly. [6, 6]  

4. Drives Innovation and Growth: 

• New ideas and perspectives: Open information sharing encourages diverse perspectives and fosters a culture of innovation. [1, 1, 3, 3]  

• Adaptability to change: With access to a wider range of information, organizations can adapt more quickly to market changes and emerging trends. [1, 1, 11, 11, 13, 14]  

• Improved performance: By leveraging collective knowledge and insights, organizations can improve overall performance and achieve sustainable growth. [6, 6, 11, 11]  

5. Enhances External Relationships: [6, 10]  

• Collaboration with partners: Sharing data with partners can lead to increased reach, improved customer service, and greater operational efficiency. 

• New revenue streams: Data sharing can also open up opportunities for new data products and services, creating new revenue streams. 

By prioritizing information sharing, organizations can create a more collaborative, efficient, and innovative environment that supports sustainable growth and success. [1, 6, 10, 11, 15]  

Reference s

[1] https://zeenea.com/what-is-data-sharing-benefits-challenges-and-best-practices/

[2] https://www.sciencedirect.com/science/article/pii/S0740624X10001322

[3] https://blogs.joinassembly.com/blog/how-to-share-information-with-team-members-effectively

[4] https://disprz.ai/blog/workplace-knowledge-sharing-barriers-best-practices

[5] https://www.joinassembly.com/blog/how-to-share-information-with-team-members-effectively

[6] https://www.databricks.com/glossary/data-sharing

[7] https://redlearning.org/breaking-down-silos-effective-communication-and-collaboration-in-lean-six-sigma/

[8] https://www.starmind.ai/blog/sharing-knowledge-with-others

[9] https://www.tandfonline.com/doi/full/10.1080/23311975.2023.2195028

[10] https://www.atscale.com/blog/data-sharing-make-smarter-decisions-at-scale/

[11] https://www.freedomgpt.com/wiki/information-sharing

[12] https://www.easygenerator.com/en/blog/knowledge-sharing/benefits-knowledge-sharing/

[13] https://www.crownrms.com/insights/information-management-scalability-flexibility/

[14] https://affine.pro/blog/shared-knowledge-app

[15] https://www.linkedin.com/advice/1/what-main-goals-benefits-developing-knowledge

Generative Pre-trained Transformer's words on the Top 10 roles from my current curricula vitae

Potential roles and corresponding descriptions that align with skills, experience, and aspirations:

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1. Program Director – Digital Transformation / Enterprise Solutions

Description:
Lead cross-functional enterprise programs leveraging SAP, AI, cloud computing, and digital technologies. Collaborate with business leaders to drive innovation, streamline operations, and scale delivery excellence across global teams.

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2. Head – Technology Consulting / Practice Lead (SAP & Cloud)

Description:
Drive SAP practice strategy and growth, overseeing delivery excellence, solutioning, and capability building. Manage pre-sales, delivery, and talent development for large SAP landscapes and BTP migrations.

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3. Director – Learning & Development / Corporate Training

Description:
Design and lead organization-wide learning initiatives, especially in emerging technologies such as AI, Cloud, and Agile. Combine industry and academic insights to develop future-ready workforce programs.

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4. Professor of Practice / Academic-Industry Liaison

Description:
Bridge academia and industry through curriculum design, skill-building initiatives, and faculty-industry collaboration. Mentor students on cloud, blockchain, AI, and lead university-industry partnerships.

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5. Agile Coach / Enterprise Scrum Master

Description:
Guide agile transformations at scale across departments. Coach teams on Lean, Kanban, and Agile methodologies, improving delivery cycles, stakeholder collaboration, and product evolution.

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6. Product Manager / Solution Architect (SAP & Cloud Platforms)

Description:
Lead end-to-end lifecycle of SAP and cloud-based products—from ideation to sunset. Manage solution architecture and integration, especially with BTP, SAP HANA, CRM, and analytics platforms.

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7. Innovation & Research Leader (AI / Cloud / EdTech)

Description:
Drive applied research in AI, cloud, and educational technologies. Innovate scalable solutions using generative AI, intelligent architectures, and cloud platforms aligned with academic and business needs.

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8. Digital Skills Evangelist / Technology Coach

Description:
Promote digital fluency through workshops, certifications, and thought leadership. Coach professionals and students in technologies such as AWS, SAP, generative AI, and Python.

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9. Pre-Sales / Bid Manager – Enterprise Solutions

Description:
Lead pre-sales solutioning, proposal design, and client engagement for large-scale SAP and cloud transformation programs. Collaborate with stakeholders to deliver winning RFP responses.

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10. Chief Learning Officer (CLO) / Strategic Education Partner

Description:
Shape the future of corporate learning through curriculum innovation, strategic partnerships, and institutional capability building. Align L&D with organizational goals and technology advancements.

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A Journey Rekindled After Two Decades

 

A Presentation with Purpose

What began as a long and steady professional journey eventually started to feel less meaningful. It was then that pursuing a PhD brought a renewed sense of curiosity, purpose, and intellectual challenge into my life.

On a quiet morning at CHRIST University, I found myself once again behind a podium—not only as a student this time, but as a speaker, mentor, and researcher. Presenting on VM scheduling policies in a research forum, I stood before a group of curious minds and experienced faculty, sharing insights shaped over years of exploration and persistence.

An Unexpected Reunion
But the day held more than just academic exchanges. Amid the bustle of post-session chats and handshakes, a familiar face emerged—my MCA classmate from two decades ago. We greeted each other with the warmth only time can deepen. What began as a catch-up soon became a powerful moment of realization: she was not only a friend from the past but my PhD guide for the past seven years.

A Community of Scholars
We posed for group photos with our peers, fellow presenters, and organizers—some in person, while others joined virtually. Each face in the frame told a story of dedication and academic camaraderie. These were not just colleagues but co-travelers on the same challenging yet rewarding path of knowledge creation.

Capturing Bonds

As we stood together once more, smiling under the soft lights of the seminar hall, I couldn’t help but feel grateful for the chance to collaborate, for the encouragement shared through every milestone, and for the constant reminder that the best journeys are walked together.

A Milestone Preserved
Later, in a quieter corner of campus, we held the symbol of years of research—a bound PhD thesis. Surrounded by mentors and teammates, this moment celebrated more than just an academic milestone; it acknowledged resilience, teamwork, and the unbreakable bond between a student and her guide.

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Gratitude, Guidance, and Growth
What began as a university friendship has grown into a mentoring relationship that continues to inspire me every day. Seven years into this PhD journey, with countless drafts, presentations, and reflections behind us, I remain deeply thankful for a friend who became my guide—and for a guide who continues to believe in me. The road ahead looks bright, especially when walked with such strong support and shared purpose.

AI Tools for Education

 In the previous week, I was studying the tools and techniques that can be augmented for educators. Here we could classify the tools based on the issues we need to solve. Some tools are very specific to a type of teaching. During the online teaching and learning process, the employment of such tools are part of the online meeting tools. Listed a few of them

1. Readai is part of a Google meeting, can summarize the participants, content discussed, etc.
2. Copilot from Microsoft, a Generative AI tool, helps by automating tasks like grading and feedback, allowing educators to focus on critical, human decisions.
3. Kahoot!: Uses AI to create interactive quizzes and simulations. 
4. Canva is a tool used not only for brochures but also to present classroom content.
5. Google Gemini is very useful for generating charts of students' performance, participation, etc.

Here are few of the example for all above from the daily usage

Artificial Intelligence for Learning & Development

Here, I like to explore how artificial intelligence (AI) is revolutionizing corporate training by enhancing personalization, efficiency, and strategic alignment. Here is a five-point agenda that I foresee in the next 5 years.

1. Personalized Learning Experiences: AI enables the creation of tailored training programs by analyzing individual learning patterns, preferences, and performance metrics. This personalization ensures that employees receive content that is most relevant to their roles and learning needs.

2. Enhanced Efficiency and Cost Reduction: By automating administrative tasks such as content curation, scheduling, and progress tracking, AI reduces the workload on training managers. This automation leads to significant cost savings and allows L&D professionals to focus on more strategic initiatives.

3. Data-Driven Insights: AI provides real-time analytics on learner engagement and progress, enabling organizations to make informed decisions about training effectiveness and areas needing improvement. These insights help in continuously refining training programs for better outcomes.

4. Scalability of Training Programs: AI-powered platforms can efficiently scale training initiatives across large organizations, ensuring consistent learning experiences regardless of geographical locations. This scalability is crucial for maintaining uniform standards and knowledge across the workforce.

5. Continuous Learning Culture: The integration of AI in L&D promotes a culture of continuous learning by providing employees with ongoing, accessible, and relevant learning opportunities. This approach supports employee growth and adaptability in a rapidly changing business environment.

In summary, the article highlights that incorporating AI into learning and development strategies leads to smarter, more effective training solutions that are personalized, efficient, and aligned with organizational goals.