Software architecture changes in the last dozen years

How have approaches to technology development changed over the past 5-10-15 years regarding architectures, missions, and tasks? What trends affect the development of IT solutions in the modern world? Why do they appear? What are they due to? Which of them will continue, and which will die out?

Technology development has changed significantly over the past 5-10-15 years regarding architectures, missions, and tasks.

Some of the main changes are:

• Cloud computing, edge computing, and 5G connectivity enable the shift from centralised to distributed architectures. These architectures allow for more scalability, flexibility, and resilience of IT systems and lower latency and cost. They also enable new applications and services that require high bandwidth, real-time data processing, and local intelligence, such as autonomous vehicles, smart cities, and industrial IoT
• The rise of artificial intelligence (AI) and machine learning (ML) as core technologies for solving complex problems and creating value across industries. AI and ML can augment human capabilities, automate tasks, optimize processes, generate insights, and enhance customer experiences. They can also enable new business models and innovations that were not possible before, such as personalized medicine, conversational agents, and generative design.
• The emergence of new programming paradigms and tools that make software development more accessible, efficient, and collaborative. These include low-code/no-code platforms, which allow users to create applications without writing code; codeless AI platforms, which enable users to build and deploy AI models without coding; and open-source platforms, which foster collaboration and innovation among developers.

Various factors, such as the increasing demand for digital transformation, the availability of large amounts of data, the advancement of hardware and software technologies, the evolution of customer expectations and behaviours, and the need for sustainability and social impact, drive these trends.

Some of these trends will likely continue as they have strong momentum and potential for further growth and improvement. For example, AI and ML will become more pervasive, powerful, and responsible; distributed architectures will become more ubiquitous, secure, and interoperable; and low-code/no-code platforms will become more sophisticated, user-friendly, and widely adopted.

Some trends may fade or change direction depending on the market dynamics, technological challenges, regulatory constraints, ethical issues, or social implications. For example, some low-code/no-code platforms may face competition from traditional coding platforms or codeless AI platforms; some distributed architectures may face trade-offs between performance and privacy; and some AI applications may face backlash from users or regulators due to bias or misuse.

How are the expectations, requests and requirements of customers and users changing? What should be the architecture of a complex IT system to satisfy them?

Customers today have higher and more diverse expectations than ever before. They want fast, convenient, personalized, and seamless experiences from any business they interact with, whether online or offline. They also want more choices, control, and value from the products and services they use. To meet these expectations, businesses must adopt a customer-centric approach that leverages digital technologies and data to deliver superior value propositions and outcomes.

However, many businesses face challenges transforming their IT systems to support this approach. Their legacy systems are often monolithic, rigid, and slow, making innovating, integrating, and scaling challenging. Their new systems are often complex, fragmented, and unstable, making it hard to maintain, secure, and optimize. Their IT teams are often siloed, conflicted, and overwhelmed, making collaborating, aligning, and delivering challenging.

To overcome these challenges, businesses must adopt a multispeed IT system architecture that can operate at different speeds for different purposes. A multispeed IT system architecture is a way of designing, developing, and deploying IT systems that can balance the trade-offs between speed, quality, and risk. It allows businesses to:

• Accelerate the delivery of customer-facing capabilities that require frequent changes and updates, such as digital products, channels, and experiences. These capabilities can use agile methods, cloud platforms, microservices architectures, and DevOps practices to enable faster feedback loops, shorter release cycles, and continuous improvement.
• Stabilize the delivery of core capabilities that require high reliability and security, such as data management, business processes, and regulatory compliance. These capabilities can use traditional methods, on-premise platforms, modular architectures, and ITIL practices to ensure quality assurance, performance optimization, and risk mitigation.
• Integrate the delivery of hybrid capabilities that require speed and stability, such as analytics, automation, and artificial intelligence. These capabilities can use hybrid methods, multi-cloud platforms, event-driven architectures, and DevSecOps practices to enable data-driven insights, intelligent workflows, and real-time responses.
• By adopting a multispeed IT system architecture, businesses can achieve several benefits:
• They can improve customer satisfaction by delivering faster, better, and more innovative solutions that meet their changing needs and preferences.
• They can increase business agility by enabling faster adaptation to market disruptions and opportunities.
• They can reduce IT complexity by simplifying the management and governance of IT systems across different environments and domains.
• They can optimize IT costs by leveraging the best-fit platforms and technologies for different purposes.

A multispeed IT system architecture is not a one-size-fits-all solution. It requires careful planning, design, implementation, and evolution based on each business's specific context and goals. It also requires close collaboration between business and IT stakeholders to ensure alignment of vision, strategy, and execution. However, when done right, a multispeed IT system architecture can help businesses meet the changing expectations of customers in the digital age.

What technologies are the basis of modern complex IT systems? What systems architecture strategies are most important for achieving high availability, security, fault tolerance, and scalability?

Here is an article that I wrote about the technologies and strategies for modern complex IT systems:

Technologies and Strategies for Modern Complex IT Systems. Modern complex IT systems are composed of multiple components interacting with each other and external entities, such as users, devices, and other systems. To ensure their reliability, performance, and functionality, these systems must meet various requirements, such as high availability, security, fault tolerance, and scalability. To achieve these requirements, modern complex IT systems rely on various technologies and strategies that enable them to effectively operate and manage their complexity. Some of the technologies that are the basis of modern complex IT systems are:

• Cloud computing: Cloud computing delivers computing resources, such as servers, storage, databases, networks, software, and applications, over the internet. Cloud computing allows IT systems to access scalable, flexible, cost-effective resources on demand without investing in or maintaining physical infrastructure. Cloud computing enables IT systems to leverage various cloud services, such as analytics, artificial intelligence, machine learning, and the Internet of Things (IoT), to enhance their capabilities and value.
• Microservices: Microservices are a software architecture style that divides a complex application into smaller and independent services that communicate with each other through well-defined interfaces. Microservices allow IT systems to develop, deploy, and update each service independently without affecting the rest of the system. Microservices also enable IT systems to use different technologies, languages, and frameworks for each service, depending on their needs and preferences.
• Edge computing: Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, such as devices, sensors, or users. Edge computing allows IT systems to reduce latency, bandwidth consumption, and congestion by processing data locally or at the network's edge. Edge computing also enables IT systems to improve security, privacy, and reliability by minimizing data exposure and transmission failures. Some of the strategies that are most important for achieving high availability, security, fault tolerance, and scalability in modern complex IT systems are:
• Load balancing: Load balancing is a technique that distributes workloads across multiple servers or resources to optimize resource utilization, throughput, and response time. Load balancing allows IT systems to achieve high availability by ensuring that no single point of failure exists and that the most suitable resource always serves requests. Load balancing also enables IT systems to achieve scalability by adding or removing resources dynamically according to the demand.
• Encryption: Encryption is a process that transforms data into an unreadable form using a secret key or algorithm. Encryption allows IT systems to achieve security by protecting data from unauthorized access or modification during transmission or storage. Encryption also enables IT systems to comply with various regulations and standards that require data protection and confidentiality.
• Backup and Recovery: Backup and recovery are processes that create and restore copies of data in case of data loss or corruption due to hardware failures, human errors, cyberattacks, or natural disasters. Backup and recovery allow IT systems to achieve fault tolerance by ensuring that data can be recovered quickly and accurately during a disaster. Backup and recovery also enable IT systems to preserve data integrity and availability by preventing data loss or damage.

The Role of Big Tech and the Potential of Small Players: New technologies are being created in various ways, depending on the technology's nature, purpose, and scope. Enthusiasts, researchers, or hobbyists create technologies with a passion, curiosity, or vision for solving a problem or creating something new. Some technologies are created by small teams or start-ups with a niche, innovative, or disruptive idea they want to test, validate, or commercialize. Large corporations or biotechs create some technologies with a strategic, competitive, or market-driven goal they want to achieve, leverage, or expand.

One example of a technology that an individual enthusiast created is the C programming language, which Dennis Ritchie developed in the early 1970s at Bell Labs. Ritchie wanted to create a simple, efficient, and portable language for writing system software. He was inspired by the B language, created by his colleague Ken Thompson for the Unix operating system. Ritchie's C language became famous and influential as many operating systems, compilers, and applications adopted it.

One example of a technology created by a small team or start-up is the Dart programming language, developed by Lars Bak and Kasper Lund in 2011 at Google. Bak and Lund wanted to create a scalable, productive, and performant language for web development. They were motivated by the limitations of JavaScript, which was the dominant language for web browsers at the time. They designed Dart as a class-based, object-oriented language that could compile to JavaScript or run on its virtual machine.

One example of a technology created by a large corporation or big tech is the TensorFlow framework, developed by Google Brain in 2015 at Google. Google Brain wanted to create a framework that was flexible, powerful, and accessible for machine learning and artificial intelligence. They were driven by the need to scale up their research and production projects that involved deep neural networks and large-scale data. They built TensorFlow as an open-source platform that could run on various devices and platforms.

The role of big techs in determining technological trends is significant and complex. On the one hand, big techs can facilitate and accelerate technological innovation and adoption, as they have the resources, capabilities, and platforms to create, support, and distribute new technologies. They can also provide leadership, guidance, and standards for developing and using new technologies. For example, Microsoft has been promoting and developing cloud computing through its Azure platform, Apple has been advancing and popularizing mobile computing through its iPhone and iPad devices, and Amazon has been leading and expanding e-commerce through its online marketplace.

How to Become a Technological Trendsetter in the Age of Big Techs?
Technology constantly evolves and changes, creating new opportunities and challenges for developers and innovators. However, it may seem that the days of "garage development", when individuals or small teams could create breakthrough technologies from scratch, are over. Nowadays, all the niches may be occupied by giants like Microsoft and FAANG (Facebook, Amazon, Apple, Netflix, and Google), who have the resources, capabilities, and platforms to dominate the technology landscape.

However, this does not mean smaller players have no room for innovation and creativity. There are still many ways to become someone who sets technological trends, even in the age of big techs. Here are some tips and examples to inspire you:

• Find a problem that matters. One of the keys to creating a successful technology is to identify a real problem that affects a large or underserved market and then design a solution that addresses it in a novel, sound, or superior way. This can help you differentiate yourself from the existing solutions and attract customers and users looking for better alternatives. For example, Zoom was founded in 2011 by Eric Yuan, who was dissatisfied with the video conferencing solutions. He wanted to create a simple, reliable, and user-friendly service that could provide high-quality video and audio for various use cases. Zoom became one of the world's most popular and widely used video conferencing platforms, especially during the COVID-19 pandemic.
• Leverage emerging technologies. Another way to create a successful technology is to leverage the latest trends and developments in the technology landscape and apply them to new or existing domains or applications. This can help you create new value propositions and opportunities that were impossible before. For example, Shopify was founded in 2004 by Tobias Lütke, who was frustrated with the e-commerce platforms available at the time. He wanted a platform enabling anyone to quickly create and run their online store. Shopify leveraged cloud computing, web development, and artificial intelligence technologies to provide a comprehensive and customizable e-commerce solution for millions of merchants worldwide.
• Collaborate with others. A third way to create a successful technology is to collaborate with other developers, innovators, or organizations who share your vision or goal and combine your skills, knowledge, and resources to achieve it. This can help you overcome the challenges and limitations you may face as a minor player, such as lack of funding, expertise, or exposure. For example, Spotify was founded in 2006 by Daniel Ek and Martin Lorentzon, who wanted to create a music streaming service that could provide unlimited access to millions of songs for a low fee. Spotify collaborated with various stakeholders, such as record labels, artists, publishers, and distributors, to secure the rights and licenses for its music catalogue. Spotify also collaborated with various platforms, such as Facebook, Apple, Google, and Samsung, to integrate its service with their devices and applications.

The Future of Desktop and Mobile OSes: Competition, Innovation, and Unification
Desktop and mobile operating systems (OSes) enable users to interact with various devices, such as PCs, laptops, tablets, smartphones, and smartwatches. The OSes provide the essential functions and features of the devices, such as user interface, file management, network connectivity, security, and application support. The OSes also influence the devices' performance, functionality, and user experience.

The current market of desktop and mobile OSes is dominated by a few significant players, such as Microsoft's Windows, Apple's iOS and macOS, and Google's Android and Chrome OS. Over the years, these OSes have established a large user base, a robust ecosystem, and a loyal fan base. They have also evolved and improved their OSes to meet their customers' and users' changing needs and preferences.

However, this does not mean there is no room for new desktop or mobile OSes to compete with the existing ones. Several factors can create opportunities and challenges for new OSes to enter and succeed. Some of these factors are:

• The advancement of technology. Technology constantly develops and changes, creating new possibilities and demands for desktop and mobile devices. For example, the emergence of cloud computing, artificial intelligence (AI), machine learning (ML), Internet of things (IoT), 5G connectivity, edge computing, and blockchain technology can enable new applications and services that require new or improved OSes to support them. New OSes can leverage these technologies to create new value propositions and competitive advantages for their devices.
• The diversification of user needs. User needs are becoming more diverse and complex as users expect more from their desktop and mobile devices. For example, users want their devices to be more personalized, secure, accessible, sustainable, and socially responsible. Users also want their devices to be more compatible, interoperable, and integrated with other devices and platforms. New OSes can cater to these needs by providing more customization options, security features, accessibility tools, environmental solutions, and social impact initiatives for their devices.
• The innovation of niche markets. Niche markets are segments or areas poorly served or satisfied by the existing desktop or mobile OSes. For example, niche markets can be based on specific regions, languages, cultures, industries, or hobbies. New OSes can target these niche markets by providing tailored solutions that meet their unique requirements and preferences. Some examples of new desktop or mobile OSes that have entered or attempted to enter the market in recent years are:
• Linux distributions: Linux is an open-source operating system that can run on various devices and platforms. Linux distributions are Linux variants or versions with different features, packages, and interfaces.

As a Software Architect at Microsoft in Devices Org, I have learned much from working on projects and collaborating with different teams. Some of the main lessons that I have learned are:

• Communication is critical. As a Software Architect, I communicate effectively with stakeholders such as customers, business analysts, developers, testers, managers, and executives. I have to be able to explain complex technical concepts in simple terms, present clear and convincing arguments for my design decisions, listen actively to feedback and suggestions, and resolve conflicts constructively.
• Collaboration is essential. As a Software Architect, I have to collaborate closely with other architects, developers, testers, and engineers to ensure that our systems align with the organisation's overall vision and strategy. I have to be able to work in cross-functional teams across different locations and time zones. I have to be open-minded and respectful of different opinions and perspectives.
• Continuous learning is vital. As a Software Architect, I have to keep up with the latest trends and developments in the technology landscape. I have to be curious and eager to learn new skills and knowledge. I have to be willing to challenge myself and step out of my comfort zone.
• Diversity is valuable. As a Software Architect at Microsoft, I have worked with people from different backgrounds, cultures, languages, and experiences.

• The impact is meaningful. As a Software Architect at Microsoft, I have had the privilege to work on systems that make a positive difference in the lives of people and organizations worldwide. I have seen how our systems can empower people to achieve more, connect more, learn more, and create more. I have also seen how our systems can contribute to social good, such as education, healthcare, environmental sustainability, and accessibility.

The Future of Big Tech: Evolution, Innovation, and Transformation
Big tech companies dominate the information technology (IT) industry, with a significant market share, a strong influence, and a high valuation. Some of the most well-known big tech companies are Microsoft, Apple, Amazon, Google, and Facebook, collectively known as MAAGF. These companies have been leading and shaping the IT industry for decades by creating and offering various products and services across domains, such as cloud computing, artificial intelligence (AI), e-commerce, social media, and entertainment. However, the future of big tech is not specific or static. Big tech companies will face various opportunities and challenges affecting their evolution, innovation, and transformation.

1. Microservices Architecture:

• The rise of microservices architecture has been one of the most significant changes. It involves breaking down large monolithic applications into smaller, loosely coupled services that can be developed, deployed, and scaled independently. This architecture enables agility, scalability, and resilience in modern software systems.

2. Cloud-Native Architecture:

• Cloud-native architecture emphasizes the use of cloud computing platforms and services to build and deploy applications. It leverages containerization, orchestration (e.g., Kubernetes), and serverless computing to enable scalability, elasticity, and resilience in distributed systems.

3. DevOps and Continuous Delivery:

• DevOps practices have become mainstream, integrating development and operations teams to automate and streamline the software delivery process. Continuous integration, continuous delivery (CI/CD), and infrastructure as code (IaC) are integral to modern software architecture, enabling rapid and reliable deployment of code changes.

4. Event-Driven Architecture:

• Event-driven architecture (EDA) has gained popularity for building responsive and scalable systems. It involves decoupling components by using asynchronous event-driven communication patterns, such as message queues, publish-subscribe systems, and event sourcing.

5. Serverless Architecture:

• Serverless architecture, also known as Function as a Service (FaaS), allows developers to run code without managing servers or infrastructure. It abstracts away the underlying infrastructure, enabling developers to focus on writing code and delivering value without worrying about scalability or maintenance.

6. Reactive Systems:

• Reactive systems architecture emphasizes responsiveness, resilience, and elasticity in distributed systems. It employs reactive programming principles to build asynchronous, message-driven, and resilient systems that can handle high concurrency and fault tolerance.

7. Distributed Data Management:

• With the growth of distributed systems and big data, distributed data management has become crucial. Architectures like distributed databases, data lakes, and stream processing systems enable efficient storage, processing, and analysis of large volumes of data across distributed environments.

8. Edge Computing:

• Edge computing architecture brings computation and data storage closer to the source of data generation, reducing latency and improving performance for real-time applications. It enables processing and analysis of data at the edge devices or edge nodes, such as IoT devices and edge servers.

9. AI and Machine Learning Integration:

• Integrating artificial intelligence (AI) and machine learning (ML) capabilities into software architecture has become increasingly common. Architectures that support ML model deployment, inference at scale, and real-time analytics enable intelligent applications and personalized user experiences.

10. Security-First Architecture:

• Security has become a primary concern in software architecture design. Security-first architecture involves implementing security measures at every layer of the software stack, including secure coding practices, encryption, authentication, authorization, and continuous monitoring.

These changes reflect the evolving landscape of software development, driven by the need for agility, scalability, resilience, and innovation in today's digital era. Software architects must adapt to these changes and embrace modern architectural principles and practices to design and build robust, scalable, and future-proof software systems.

Some of these opportunities and challenges are:

• The advancement of technology. Technology constantly develops and changes, creating new possibilities and demands for IT products and services. Big tech companies must keep up with the latest trends and developments in the technology landscape, such as quantum computing, biotechnology, blockchain technology, and augmented reality. They will also have to leverage these technologies to create new value propositions and competitive advantages for their products and services.
• The diversification of customer needs. Customer needs are becoming more diverse and complex as customers expect more from their IT products and services. They want their products and services to be more personalized, secure, accessible, sustainable, and socially responsible. They also want their products and services to be more compatible, interoperable, and integrated with other products and services. Big tech companies must cater to these needs by providing more customization options, security features, accessibility tools, environmental solutions, and social impact initiatives for their products and services.
• The regulation of the market. The market is becoming more regulated and scrutinized by various authorities and stakeholders, such as governments, regulators, courts, media, and activists. They are concerned about the impact of big tech companies on various aspects of society, such as privacy, democracy, competition, innovation, and diversity. They also impose rules and restrictions on big tech companies to ensure accountability, transparency, and responsibility.