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Real-world insights for sharper web dev decisions Advertise with Us|Sign Up to the Newsletter @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } WebDevPro #115 The API Renaissance: From Endpoints to Products Real-world insights for sharper web dev decisions Hi , Welcome to the newest issue of WebDevPro! Every modern digital experience depends on an invisible API ecosystem. When you make a payment on Stripe, book a trip on Airbnb, or sign in with Google, dozens of APIs handle authentication, data exchange, and workflow coordination in milliseconds. They are the unseen architecture of our connected age: the roads, bridges, and traffic signals of the internet. For years, APIs were treated as plumbing: necessary infrastructure but not strategic assets. Teams built endpoints to enable integrations, often with little thought about usability, evolution, or governance. The result was what Jarzyna and Amzani, the authors of RESTful API Design Patterns and Best Practices, termed "API Sprawl": a proliferation of disconnected interfaces that solved immediate problems but created long-term complexity. Organizations found themselves unable to answer basic questions: How many APIs do we have? Where are they deployed? Why are they failing? That perspective is rapidly changing. According to Postman's 2023 State of API Report, 86% of developers now use REST APIs, and organizations with formal API contracts report 70% faster time to market for new features. More importantly, these same organizations experience 65% fewer API-related incidents, demonstrating that treating APIs as products isn't just good practice but a competitive advantage. This transformation marks what Jarzyna and Amzani call the API Renaissance: a fundamental shift from viewing APIs as integration afterthoughts to treating them as enduring digital products with audiences, lifecycles, and measurable value. But let’s catch up first. Here are the top links from the last issue in case you missed them: ⚡ React Conf 2025 unveiled React 19.2, new performance APIs, and major React Native updates ⚛️ Playwright introduced test agents that automate planning, coding, and fixing of tests 🤖 The HTML <output> tag was spotlighted as a powerful but overlooked tool for displaying dynamic results Have any ideas you want to see in the next article? Hit Reply! Advertise with us Interested in reaching our audience? Reply to this email or write to kinnaric@packt.com. Learn more about our sponsorship opportunities here. From Integration to Experience In the early years of distributed systems, an API's success was measured by a simple question: Does the data flow? Connectivity was the goal, not usability. Developers built endpoints that worked, documented them minimally, and moved on to the next integration challenge. Today's APIs compete on experience. A well-designed API reduces onboarding time from days to minutes, communicates intent clearly through self-describing responses, and feels predictable across different use cases. The interface has become part of a brand's identity, with companies like Stripe and Twilio treating their APIs as flagship products. This is how this shift manifests in practice: - Stripe's Documentation Philosophy: Their API documentation reads like an interactive tutorial, with embedded examples, live test modes, and clear error messages that explain not just what went wrong, but how to fix it. Every response includes contextual information that guides developers toward successful integration. - Twilio's Communication-First Design: Rather than exposing raw telecommunications infrastructure, Twilio's APIs speak the language of business outcomes—sending messages, making calls, managing conversations. Their error responses are human-readable, describing problems in terms that developers can act upon immediately. - Adidas's Governance at Scale: With thousands of point-to-point integrations, Adidas transformed its approach by implementing a Single Source of API Truth (SSOT). Every API specification serves as the master contract, not the implementation, ensuring consistency across hundreds of teams while accelerating delivery through automated validation. When organizations adopt this product mindset, design becomes a continuous practice rather than a one-time step. Developer portals evolve into customer-facing experiences, complete with interactive documentation, usage analytics, and feedback loops. APIs no longer hide behind applications; they become part of the story. The Maturity Spectrum: From Plumbing to Products These are not advanced techniques. They are the day-to-day moves that keep your application fast and legible. The material returns to them at every step, which is why the example app remains steady as features stack up. Not all APIs are created equal, and there are two critical frameworks for understanding API quality: Richardson Maturity Model (RMM) Most APIs claiming to be "RESTful" actually operate at Level 2 of the Richardson Maturity Model: using proper HTTP methods and status codes but missing the hypermedia controls that enable true REST. The progression looks like this: Level 0 (The Swamp of POX): Single endpoint, everything via POST Level 1 (Resources): Multiple endpoints but still RPC-style Level 2 (HTTP Verbs): Proper use of GET, POST, PUT, DELETE Level 3 (Hypermedia Controls): Self-describing APIs with embedded navigation Web API Design Maturity Model (WADM) While RMM focuses on protocol usage, WADM examines data representation: Level 0 (Database-centric): Raw database exposure Level 1 (Object-centric): Internal object models exposed Level 2 (Resource-centric): External interface design Level 3 (Affordance-centric): User-need-driven design The progression from technical plumbing to user-centered products represents the core of the API Renaissance. Level 3 APIs in both models don't just expose data but also expose capabilities that align with what users actually need to accomplish. Designing for Context: Domain-Driven APIs A recurring theme in RESTful API Design Patterns and Best Practices is that meaningful APIs grow out of deep domain understanding. Domain-Driven Design (DDD) helps developers map APIs to the real language of business rather than internal implementation details. Instead of exposing technical data structures, a DDD-aligned API communicates business intent. Consider the difference. Database-centric approach: GET /user_orders_table?user_id=123&status=2 Affordance-centric approach: GET /customers/123/active-orders The second example speaks the language of the business domain. It describes what users care about (active orders for a specific customer), not how the system stores data internally. Pairing DDD with OpenAPI Specification creates what the authors call a "single source of truth" that both humans and machines can interpret. This shared vocabulary ensures alignment between business intent and technical implementation, enabling teams to evolve APIs without losing cohesion because the design is anchored in shared meaning. This combination allows organizations to build what they term "experience-based APIs": interfaces that orchestrate complex business workflows rather than just exposing CRUD operations. For example, instead of requiring multiple calls to add items, calculate shipping, apply discounts, and process payment, an experience-based checkout API handles the entire workflow in a single, atomic operation. The Complete API Lifecycle: Beyond Build and Deploy Every API lives through predictable cycles of creation, growth, and change. Here's a seven-stage lifecycle that most organizations overlook: Requirements Gathering: Understanding the "why" behind API creation Design: Creating the formal contract using OpenAPI Specification Development and Testing: Implementing against the contract with validation Deployment: Moving to production with automated quality gates Publishing: Exposing through API gateways with proper security and rate limiting Consuming and Monitoring: Observing real-world usage and performance Update: Evolving based on feedback while maintaining backward compatibility Retirement: Graceful sunsetting with proper deprecation strategies API Lifecycle Stages: This figure illustrates this continuous loop, showing how each stage feeds back into the others, creating a rhythm that balances innovation with reliability. Each phase creates a feedback loop that balances innovation with stability. When organizations skip these steps (particularly the design-first approach) they often face integration failures, duplicated functionality, and security vulnerabilities. Conquering API Sprawl Through Governance Significant attention should be dedicated to API Sprawl: a phenomenon where organizations create numerous APIs without a centralized strategy or oversight. The symptoms are telling: Unable to specify what APIs exist in the ecosystem Unknown deployment locations and access methods Lack of live monitoring data across APIs Inability to diagnose API failures effectively Governance might sound restrictive, but the authors reframe it as an ecosystem of shared patterns and automation that provides freedom through structure. When organizations define clear conventions for naming, authentication, and versioning, teams gain a common design language and spend less time debating structure. The Single Source of Truth Approach Let's take Adidas's API strategy as an exemplar of effective governance. Their approach centers on a Single Source of API Truth (SSOT) where every team works from unified specifications stored in shared repositories. This eliminates the drift between documentation and implementation that plagues many organizations. This is an extract from Adidas’s API Guidelines Key principles from Adidas's approach: API-first development: Design always precedes implementation Specification as contract: The OpenAPI document, not the code, serves as the binding agreement Automated validation: CI/CD pipelines enforce consistency without manual overhead Minimal API surface: Following the YAGNI principle to avoid over-engineering This structured approach promotes transparency and consistency while turning governance from manual review into automated safeguards that accelerate delivery. The Hypermedia Advantage: APIs for Humans and AI One of the most forward-looking insights are hypermedia: the often-overlooked REST constraint that makes APIs self-describing. While most APIs require clients to hardcode endpoint knowledge, hypermedia APIs embed navigation controls directly in responses. Consider the difference. Traditional Level 2 API response: { "id": "wand-1", "name": "Oak Wand with Dragon Heartstring", "price": 75.0, "inStock": true } Level 3 Hypermedia response: { "id": "wand-1", "name": "Oak Wand with Dragon Heartstring", "price": 75.0, "inStock": true, "_links": { "self": {"href": "/items/wand-1"}, "add-to-cart": {"href": "/cart/items", "method": "POST"}, "similar-items": {"href": "/items?type=wand&powerLevel=8"}, "compatible-potions": {"href": "/items/wand-1/compatible-potions"} } } The hypermedia version doesn't just return data but provides a map of what's possible next. Clients can discover capabilities dynamically rather than relying on external documentation. This becomes particularly powerful for AI consumption. As the authors note, "hypermedia APIs are going to be especially important in the coming years" because AI systems can explore and navigate them without tedious implementation of hardcoded endpoints. Large language models excel at following structured navigation patterns, making hypermedia the ideal interface for autonomous agents. Change Management: Evolution Without Disruption There are detailed frameworks for managing API evolution, one of the most challenging aspects of treating APIs as products, with three primary strategies outlined: Global Versioning Entire API versions (v1, v2) that provide clear upgrade paths but increase operational complexity. Evolution-Only Approach Continuous backward-compatible improvements without versioning, following strict extension rules: - Never remove anything - Never change processing rules - Never make optional things required - Anything added must be optional Hybrid Model Combining evolution for non-breaking changes with versioning for breaking changes: the approach used by companies like Stripe. RESTful API Design Patterns and Best Practices highlights a MagicStore case study that demonstrates this in practice. When replacing their confusing /catalog endpoint with /products, the team didn't force immediate migration. Instead, they: - Introduced /products alongside existing /catalog - Added deprecation headers: Sunset: Wed, 30 Sep 2025 23:59:59 GMT - Provided comprehensive migration guides - Monitored usage analytics to track transition progress - Only removed /catalog after ensuring complete migration This disciplined approach transformed a potentially disruptive breaking change into a trust-building demonstration of thoughtful stewardship. Observability: APIs That Learn and Adapt Once deployed, an API's behavior in production becomes the ultimate measure of design quality. Observability must be embedded from the start, not retrofitted later. Effective API observability goes beyond basic uptime monitoring to include: Usage patterns:Which endpoints create value vs. friction Performance metrics:Latency, throughput, and error rates by operation Developer feedback:Integration pain points and feature requests Business impact:How API changes affect downstream applications Organizations with robust API contracts and observability report not just faster delivery, but 45% faster incident resolution times. APIs become self-improving systems that reveal optimization opportunities through real-world usage data. The authors recommend treating every production incident as a learning opportunity. When APIs are observable, they tell their creators what works and what needs refinement, creating a virtuous cycle of continuous improvement. The Future: APIs as Conversation Partners The API Renaissance represents more than technical evolution: it's a cultural shift toward empathy, transparency, and long-term thinking. As AI systems increasingly become API consumers alongside human developers, the need for self-describing, navigable interfaces grows exponentially. Jarzyna and Amzani highlight that successful organizations treat APIs as the connective tissue of digital transformation. They create environments where experimentation thrives within coherent frameworks, allowing companies to innovate at speed without sacrificing stability. Hypermedia controls guide AI agents through complex workflows, while OpenAPI specifications provide the semantic context needed for autonomous decision-making. In this emerging landscape, the APIs built with product thinking, domain alignment, lifecycle discipline, and hypermedia navigation will become the foundation for intelligent automation. They won't just connect systems but will enable new forms of collaboration between human creativity and machine capability. Key Takeaways for API Practitioners There's a comprehensive blueprint for organizations ready to embrace the API Renaissance: Start with Purpose:Understand your API's audience and business value before designing endpoints Design First:Use OpenAPI specifications as binding contracts, not afterthought documentation Embrace Domain Language:Align APIs with business vocabulary, not database schemas Plan for Evolution:Implement change management strategies that preserve trust while enabling innovation Measure Everything:Build observability into APIs from day one to enable continuous improvement Think Beyond CRUD:Design experience-based APIs that orchestrate workflows, not just data operations Prepare for AI:Include hypermedia controls that enable autonomous navigation and discovery Got 60 seconds? Tell us what clicked (or didn’t) Closing Note This article draws directly from RESTful API Design Patterns and Best Practices by Andrzej Jarzyna and Samir Amzani, published by Packt. The book provides a complete blueprint for designing, governing, and evolving APIs at scale, supported by real examples from companies like Stripe, Twilio, Adidas, and others who have successfully navigated the transition from integration tools to digital products. As software continues to connect everything from mobile apps to AI agents, APIs will remain the universal language of digital systems. The organizations that treat them as products today (with proper lifecycle management, domain alignment, and user-centered design) are writing the architecture of tomorrow's connected world. The API Renaissance isn't coming. It's here. The question is whether your organization will lead it or be left behind by it. For teams ready to implement these principles, RESTful API Design Patterns and Best Practices offers detailed guidance on OpenAPI specification, JSON Schema modeling, hypermedia implementation, and change management strategies that have been proven in production environments across multiple industries. Cheers! Editor-in-chief, Kinnari Chohan SUBSCRIBE FOR MORE AND SHARE IT WITH A FRIEND! *{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0}#converted-body .list_block ol,#converted-body .list_block ul,.body [class~=x_list_block] ol,.body [class~=x_list_block] ul,u+.body .list_block ol,u+.body .list_block ul{padding-left:20px} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

Exploring Unit 42's findingsDon't miss out!Sign up today!#221: Digging into Social Engineering, part 1Welcome to another_secpro!This week, we're poking the brain of CISO expert David Gee to deliver you some insights which line up nicely with his new book: A Day in the Life of a CISO. We've also included our popular PDF resource again, to help you improve your training sessions and help the non-specialists amongst us to make the right moves in the age of AI. Check it out!Check out _secpro premiumIf you want more, you know what you need to do: sign up to the premium and get access to everything we have on offer. Click the link above to visit our Substack and sign up there!Cheers!Austin MillerEditor-in-ChiefThis week's articleUnit 42 on non-phishing vectorsRecently, along with a wealth of other industry-critical information and resources, Palo Alto’s Unit 42 published their incident response report concerning social engineering. As an area of practice that has always fascinated me—as more art than science—this immediately grabbed my attention and almost forced me to start taking notes. With this in mind, we as a team are heading out over the next few weeks to dig deeper into social engineering and help you discern the golden kernels that you need to access.Check it out todayNews BytesUnit 42 Threat Bulletin – October 2025: Published 21 October 2025, this monthly bulletin by Unit 42 (the threat-research arm of Palo Alto Networks) surfaces multiple emerging threats. Highlights include the self-propagating supply-chain worm “Shai-Hulud”, an advanced supply-chain attack targeting npm packages; detailed technical IOCs; and spotting a new Chinese-nexus APT “Phantom Taurus” targeting government/telecom across Africa/Middle East/Asia.PacketWatch Cyber Threat Intelligence Report: Crafted by Intelligence Team and published 20 October 2025, this bi-weekly briefing highlights: (a) the major breach incident at F5 Networks (source code + undisclosed vulnerabilities); (b) a list of critical and high-severity vulnerabilities across major platforms (Oracle, Microsoft, Veeam, SAP, 7-Zip, Ivanti); and (c) a renewed emphasis on user-targeted attacks such as credential phishing, fake CAPTCHA software, and fake downloads.Disrupting malicious uses of AI(PDF): Released by OpenAI, this October 2025 update (PDF) details how threat actors are increasingly leveraging multiple AI tools (e.g., using one model for planning and another for execution), integrating AI into existing cyber-attack workflows, rather than inventing wholly new attack methods. The report also gives case studies of misuse (scams, code-signing abuse, social engineering) and how defence and detection are adapting.Microsoft Digital Defense Report 2025: Lighting the path to a secure future(PDF):Published by Microsoft 21 October 2025, this annual-style report provides their threat intelligence view: major uptick in AI-enabled adversary operations, increasing geopolitical cyber-conflict, supply chain risk, and the imperative for defenders to rethink traditional security models given the speed and scale of modern attacksENISA Threat Landscape 2025 (PDF):Published 7 October 2025 by ENISA (European Union Agency for Cyber Security), this comprehensive PDF analyses 4,875 incidents (1 July 2024–31 June 2025) to map global threat trends: shift toward mixed/campaign-style operations, AI-enabled threat activity, supply chain convergence, and increased adversary speed. Though slightly earlier than your window, its release date is timely and gives context for many of the current week’s incidents.This week's academiaFrom Texts to Shields: Convergence of Large Language Models and Cybersecurity (Tao Li, Ya-Ting Yang, Yunian Pan & Quanyan Zhu):This paper explores how large language models (LLMs) are increasingly converging with cybersecurity tasks: for example, using LLMs for vulnerability analysis, network and software security tasks, 5G-vulnerability assessment, generative security engineering and automated reasoning in defence scenarios. The authors highlight socio-technical challenges (trust, transparency, human-in-the-loop, interpretability) when deploying LLMs in high-stakes security settings, and propose a forward-looking research agenda to integrate formal methods, human-centred design and organisational policy in LLM-enhanced cyber-operations.Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation (Tharcisse Ndayipfukamiye, Jianguo Ding, Doreen Sebastian Sarwatt, Adamu Gaston Philipo & Huansheng Ning): This survey conducts a PRISMA-style review (2021–Aug 2025) of how Generative Adversarial Networks (GANs) are being used both as attack tools and defensive tools in cybersecurity. They analyse 185 peer-reviewed studies, develop a taxonomy across four dimensions (defensive function, GAN architecture, cybersecurity domain, adversarial threat model), and identify key gaps: training instability, lack of standard benchmarks, high computational cost, limited explainability. They propose a roadmap towards scalable, trustworthy GAN-powered defences.Securing the AI Frontier: Urgent Ethical and Regulatory Imperatives for AI-Driven Cybersecurity (Vikram Kulothungan): This article examines the ethical and regulatory challenges arising from the deployment of AI in cybersecurity. It traces historical regulation of AI, analyses current global frameworks (e.g., the EU AI Act), and discusses key issues including bias, transparency, accountability, privacy, human oversight. The paper proposes strategies for enhancing AI literacy, public engagement, and global harmonisation of regulation in AI-driven cyber-systems.A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems (Benyamin Tafreshian & Shengzhi Zhang):The authors propose a multi-layer defensive framework aimed at ML‐based Network Intrusion Detection Systems (NIDS) which are vulnerable to adversarial evasion. Their framework integrates adversarial training, dataset balancing, advanced feature engineering, ensemble learning, and fine-tuning. On benchmark datasets NSL-KDD and UNSW-NB15, they report on average a ~35% increase in detection accuracy and ~12.5% reduction in false positives under adversarial conditions.Cyber Security: State of the Art, Challenges and Future (W.S. Admass et al.): This article presents an overview of the state of the art in cybersecurity: existing architectures, key challenges, and emerging trends globally. It reviews tactics, techniques, and procedures (TTPs), current defence mechanisms and future research directions.DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks (Jing Chen, Onat Güngör, Zhengli Shang, Elvin Li & Tajana Rosing): This paper introduces “DYNAMITE”, a framework for dynamically selecting the optimal defence mechanism for ML-based Intrusion Detection Systems (IDS) when under adversarial attack. Instead of applying a static defence, DYNAMITE uses a meta-ML selection mechanism to pick the best defence in real-time, reducing computational overhead by ~96.2% compared to an oracle and improving F1-score by ~76.7% over random defence and ~65.8% over the best static defence.*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}