Cloud Computing Paradigm

“[Origin of the term]...Comes from the early days of the Internet where we drew the network as a cloud… we didn’t care where the messages went… the cloud hid it from us” – Kevin Marks, Google

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Cloud Computing Paradigm

May 30, 2023
mike@standardsmichigan.com

“The greatest danger in modern technology isn’t that machines will begin to think like people,
ut that people will begin to think like machines.”
— Michael Gazzaniga

NIST Cloud Computing Standards Roadmap

The “next big thing” will reveal itself in hindsight.  Some areas of interest and potential advancements include:

  1. Edge Computing: Edge computing brings computation closer to the data source, reducing latency and bandwidth usage. It enables processing and analysis of data at or near the edge of the network, which is especially important for applications like IoT, real-time analytics, and autonomous systems.
  2. Quantum Computing: Quantum computing holds the promise of solving complex problems that are currently beyond the capabilities of classical computers. Cloud providers are exploring ways to offer quantum computing as a service, allowing users to harness the power of quantum processors.
  3. Serverless Computing: Serverless computing abstracts away server management, enabling developers to focus solely on writing code. Cloud providers offer Function as a Service (FaaS), where users pay only for the actual execution time of their code, leading to more cost-effective and scalable solutions.
  4. Multi-Cloud and Hybrid Cloud: Organizations are increasingly adopting multi-cloud and hybrid cloud strategies to avoid vendor lock-in, enhance resilience, and optimize performance by distributing workloads across different cloud providers and on-premises infrastructure.
  5. Artificial Intelligence and Machine Learning: Cloud providers are integrating AI and ML capabilities into their platforms, making it easier for developers to build AI-driven applications and leverage pre-built models for various tasks.
  6. Serverless AI: The combination of serverless computing and AI allows developers to build and deploy AI models without managing the underlying infrastructure, reducing complexity and operational overhead.
  7. Extended Security and Privacy: As data privacy concerns grow, cloud providers are investing in improved security measures and privacy-enhancing technologies to protect sensitive data and ensure compliance with regulations.
  8. Containerization and Kubernetes: Containers offer a lightweight, portable way to package and deploy applications. Kubernetes, as a container orchestration tool, simplifies the management of containerized applications, enabling scalable and resilient deployments.

 

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