How do emerging technologies in systems design affect your work?
Systems design is the process of creating the architecture, components, interfaces, and behaviors of a system that meets the needs and requirements of its users and stakeholders. As a systems designer, you are constantly faced with new challenges and opportunities to apply your skills and creativity to solve complex problems. But how do emerging technologies in systems design affect your work? In this article, we will explore some of the trends and innovations that are shaping the future of systems design and how you can adapt and benefit from them.
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Bahadir KayaPrincipal Technology Consultant @ DefineX | MEng, TOGAF, Event Storming Domain Driven Design, ISO 27001 22301 LA
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Aniket SoniAssociate - Projects @Cognizant | 2x GCP Certified | Databricks Certified Data Engineer | AFCEA 2024 40U40 | IAF Young…
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Sudipta BahaliProgram Management | Product Management | Digital Transformation consulting | Research & Innovation | Solution, GTM…
Artificial intelligence (AI) and machine learning (ML) are transforming the way systems are designed, developed, and deployed. AI and ML can help systems designers to automate tasks, optimize performance, enhance user experience, and generate insights. For example, you can use AI and ML to design systems that can learn from data, adapt to changing environments, provide personalized recommendations, and detect anomalies. However, AI and ML also pose new challenges and risks, such as ethical, legal, and social implications, data quality and security, explainability and accountability, and human-machine collaboration. As a systems designer, you need to be aware of these issues and design systems that are fair, transparent, robust, and human-centered.
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In my previous experience the company created AI organisation and they started to solve business needs with ML, AI . But this technologies come with lots of open source technologies that most of them not supported officially. It was a huge compliance issue for Companies that must comply with strict regulations. They got GPU supported infrastructure, setup tens of middleware technologies. But the problem is they can not move this systems to prod environment because of compliance requirements. They used as test environment . The Companies should choose 2 way. If regulations restricted for cloud systems Companies can pay huge licence payments to supported systems or create infrastructure knowledge to support themselves.
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Emerging technologies in systems design are automating tasks, optimizing performance, enhancing user experience, and generating insights. This is affecting work by making it more efficient, effective, and collaborative. It is also enabling new ways of working, such as remote work and the gig economy
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We are at a an interesting intersection where AI and ML has two faces to every great story. Intelligent systems handle security and risk Management protocols around the globe. The same intelligent systems wreck havoc via brute force and other counter-security methods. Every use case has this two face situation and it makes me wonder, What should be the single important objective for systems design to tip the systems in the favour of the Responsible AI goals.
Cloud computing is the delivery of computing services over the internet, such as servers, storage, databases, networking, software, analytics, and intelligence. Cloud computing enables systems designers to access scalable, reliable, and cost-effective resources and services, without having to manage or maintain physical infrastructure. Cloud computing also supports the development of distributed, microservice-based, and serverless systems, which can improve agility, scalability, and resilience. Edge computing is the practice of processing data closer to the source, such as devices, sensors, or users, rather than in centralized cloud servers. Edge computing can reduce latency, bandwidth, and cost, as well as enhance privacy, security, and reliability. As a systems designer, you need to consider the trade-offs and benefits of cloud and edge computing, and design systems that can leverage both paradigms.
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The convergence of these two paradigms is not just about where computation happens but how we fundamentally reimagine system architectures for the future. In the era of high connectivity and explosive data generation, centralizing everything in the cloud may not be sustainable. Edge computing emerges, acting as a bridge that complements the expansive capabilities of the cloud while attending to real-time, localized needs. Utilizing the vast resources of the cloud with the immediacy of edge processing, devs can not only achieve global scale but also local nuance. This duality is not just a matter of technological choice but a strategic enabler for businesses to deliver richer, more responsive and context-aware experiences.
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Though the definition here limits edge computing to the IoT sphere, it is interesting to consider the edge as being as close to the user as possible. The cloud and the edge are not mutually exclusive. With the availability of more and more compute regions, devs can design their apps to intelligently distribute the data across these regions, to boost performance. Or, if such services exist that cater to the edge experience for minimal costs, these should be considered instead.
The internet of things (IoT) is the network of physical objects that are embedded with sensors, software, and connectivity, enabling them to collect and exchange data. IoT can enable systems designers to create systems that can interact with the physical world, monitor and control processes, and provide new services and value. For example, you can design systems that can automate smart homes, optimize smart cities, enhance smart health care, and enable smart manufacturing. 5G is the fifth generation of mobile network technology, which can provide faster speed, lower latency, higher capacity, and more reliability than previous generations. 5G can enable systems designers to support more IoT devices, enable real-time communication, and facilitate new applications and use cases. As a systems designer, you need to understand the capabilities and limitations of IoT and 5G, and design systems that can integrate and utilize them.
Blockchain is a distributed ledger technology that can store and verify transactions without the need for a central authority or intermediary. Blockchain can enable systems designers to create systems that are secure, transparent, and decentralized, and can support peer-to-peer exchange, smart contracts, and digital identity. For example, you can design systems that can facilitate cross-border payments, streamline supply chains, empower social impact, and protect intellectual property. Crypto is the term used to refer to cryptocurrencies, digital tokens, and protocols that are built on blockchain technology. Crypto can enable systems designers to create systems that are innovative, disruptive, and inclusive, and can challenge the status quo of existing systems and institutions. For example, you can design systems that can enable decentralized finance, web 3.0, non-fungible tokens, and metaverse. As a systems designer, you need to be familiar with the concepts and principles of blockchain and crypto, and design systems that can leverage and contribute to them.
DevOps is a culture and practice that aims to unify the development and operation of systems, and to improve collaboration, communication, and efficiency. DevOps can help systems designers to deliver systems that are faster, safer, and better quality, and to respond to changing needs and feedback. Continuous integration (CI) and continuous delivery (CD) are key aspects of DevOps, which involve automating the processes of building, testing, and deploying systems. CI/CD can help systems designers to ensure consistency, reliability, and security of systems, and to accelerate innovation and value delivery. As a systems designer, you need to adopt and embrace DevOps and CI/CD, and design systems that are modular, testable, and deployable.
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Creating automated DevOps system has lots of advantages to improve their time to market. But this technology can not adapt for all development lifecycle because of old technology stack. And they can not make everything automated without operational work . The best way is piloting DevOps pipeline on target architecture’s first project. After that, you can disseminate step by step. Installing retroactive devops does not always produce the expected benefit.
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Embracing DevOps and CI/CD practices in systems design is paramount for streamlining development and operations, promoting efficiency and enhancing the quality of delivered systems. By adopting modular, testable and deployable design principles, systems designers can ensure the consistency and reliability of their systems while accelerating innovation and value delivery.
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