TECHNOLOGY RADAR VOL.16 Insights into the technology and trends shaping the future thoughtworks.com/radar #TWTechRadar CONTRIBUTORS The Technology Radar is prepared by the ThoughtWorks Technology Advisory Board, comprised of: Rebecca Parsons (CTO) | Martin Fowler (Chief Scientist) | Badri Janakiraman | Bharani Subramaniam | Camilla Crispim Erik Doernenburg | Evan Bottcher | Fausto de la Torre | Hao Xu | Ian Cartwright James Lewis | Jonny LeRoy | Marco Valtas | Mike Mason | Neal Ford Rachel Laycock | Scott Shaw | Srihari Srinivasan | Zhamak Dehghani WHAT’S NEW? Highlighted themes in this edition: CONVERSATIONAL UI AND platforms. It appears that the “cloud wars” have NATURAL LANGUAGE PROCESSING moved from competing on storage and compute to cognitive capabilities, as witnessed by the willingness watch the video (thght.works/ConUI) to open-source previously differentiating tools such as Kubernetes and Mesos. Conversation—a new way to interact with applications— took the ecosystem by storm with tools such as Siri, All the big players have offerings in this space, along Cortana, and Allo, and then extended into homes with with interesting niche players worth assessing. Although devices such as Amazon Echo and Google Home. we still have reservations about the ethical and privacy implications of these services, we see great promise Building conversational and natural language user in utilizing these powerful tools in novel ways. Our interfaces, while presenting new challenges, has obvious clients are already investigating what new horizons they benefits. The team behind the Echo intentionally may expose by combining commodity cognition with omitted a screen, forcing them to rethink many human- intelligence about their own businesses. machine interactions. DEVELOPER EXPERIENCE AS THE The conversational trend is not just limited to voice; NEW DIFFERENTIATOR as messaging apps have grown to dominate both watch the video (thght.works/DevExp) phones and workplaces, we see conversations with other humans being supplemented by intelligent chatbots. As these platforms improve, they will learn User experience design has been a key differentiator to understand the context and intent of conversations, for technology product companies for many years. Now making interactions more lifelike and therefore more the rapid rise of developer-facing tools and products, compelling. combined with the scarcity of engineering talent, is driving a similar focus on developer experience. The explosion of interest in the marketplace and mainstream media leads to a corresponding rise in Increasingly, organizations evaluate cloud offerings developer interest in this new personal exocortex based on the amount of engineering friction they interaction mode. reduce, treat APIs as products, and spin up teams focused on engineering productivity. At ThoughtWorks, INTELLIGENCE AS A SERVICE we have always obsessed over efficient engineering practices and promoted tools and platforms that make watch the video (thght.works/IntSer) developers’ lives easier, so it excites us to see the industry beginning to adopt this approach. A family of platforms burst onto the scene recently that we call intelligence as a service. These platforms Key techniques include: treating internal infrastructure encompass a wide variety of surprisingly powerful as a product that needs to be compelling enough utilities from voice processing to natural language to compete with external offerings, focusing on self- understanding, image recognition, and deep learning. service, understanding the developer ergonomics of the APIs you produce, containing “legacy in a box”, and Capabilities that would have consumed costly resources committing to ongoing empathetic user research of the a few years ago now appear as open source or SaaS developers using your services. © ThoughtWorks, Inc. All Rights Reserved. TECHNOLOGY RADAR | 3 THE RISE OF PLATFORMS PERVASIVE PYTHON watch the video (thght.works/RiseOTP) watch the video (thght.works/PerPyt) The Radar themes emerge from observations and Python is a language that keeps popping up in conversations during the vetting process; recently, interesting places. Its ease of use as a general while compiling the Radar, we’ve noticed the number programming language, combined with its strong of new entries in the Platforms quadrant. We think foundation in mathematical and scientific computing this is indicative of a broader trend in the software has historically led to its grassroots adoption by the development ecosystem. academic and research communities. More recently, industry trends around AI commoditization and Notable Silicon Valley companies have illustrated applications, combined with the maturity of Python 3, how building a suitable platform can yield significant have helped bring new communities into the benefits. Part of their success comes from finding Python fold. a useful level of encapsulation and capabilities. Increasingly, “platform thinking” appears across the This edition of the Radar features a few Python libraries ecosystem—from advanced capabilities highlighted on that have helped boost the ecosystem, including Scikit- the Radar such as natural language, to infrastructure learn in the machine learning domain; TensorFlow, platforms such as Amazon. Keras, and Airflow for smart data flow graphs; and spaCy which implements natural language processing to Businesses are starting to think about platforms help empower conversationally aware APIs. Increasingly, when exposing select capabilities via product-inspired we see Python bridging the gap between the scientists APIs. Development teams think more in terms of and engineers within organizations, loosening past building platforms for integration and improved prejudice against their favorite tools. developer experience. It seems the industry has finally latched onto a reasonable combination of packaging, Architectural approaches such as microservices and convenience, and usefulness. containers have eased the execution of Python in production environments. Engineers can now deploy One definition that we like is that platforms should and integrate specialized Python code created by expose a self-service API and be easy to configure and scientists through language- and technology-agnostic provision within a team environment—which intersects APIs. This fluidity is a great step toward a consistent nicely with another emerging theme, developer ecosystem between researchers and engineers, experience as the new differentiator. We expect to see in contrast to the de facto practice of translating further refinement in both the definition and capabilities specialized languages such as R to the production of platforms in the near future. environments. © ThoughtWorks, Inc. All Rights Reserved. TECHNOLOGY RADAR | 4 ABOUT THE RADAR ThoughtWorkers are passionate about technology. We value to a wide range of stakeholders, from developers build it, research it, test it, open source it, write about to CTOs. The content is intended as a concise summary. it, and constantly aim to improve it—for everyone. Our mission is to champion software excellence and We encourage you to explore these technologies for revolutionize IT. We create and share the ThoughtWorks more detail. The Radar is graphical in nature, grouping Technology Radar in support of that mission. The items into techniques, tools, platforms, and languages & ThoughtWorks Technology Advisory Board, a group of frameworks. When Radar items could appear in multiple senior technology leaders in ThoughtWorks, creates quadrants, we chose the one that seemed most the Radar. They meet regularly to discuss the global appropriate. We further group these items in four rings technology strategy for ThoughtWorks and the to reflect our current position on them. technology trends that significantly impact our industry. For more background on the Radar, see The Radar captures the output of the Technology thoughtworks.com/radar/faq Advisory Board’s discussions in a format that provides RADAR AT A GLANCE 1 ADOPT 2 TRIAL We feel strongly that Worth pursuing. It is the industry should be important to understand how adopting these items. to build up this capability. We use them when Enterprises should try this appropriate on our technology on a project that projects. can handle the risk. 1 2 3 4 HOLD ASSESS TRIAL ADOPT ADOPT TRIAL ASSESS HOLD 3 ASSESS 4 HOLD Worth exploring with the Proceed with caution. goal of understanding how it will affect your enterprise. 96 108 NEW OR CHANGED Items that are new or have had significant changes since the last Radar are NO CHANGE represented as triangles, while items that have not changed are represented as circles Our Radar is forward looking. To make room for new items, we fade items that haven’t moved recently, which isn’t a reflection on their value but rather our limited Radar real estate. © ThoughtWorks, Inc. All Rights Reserved. TECHNOLOGY RADAR | 5 THE RADAR TECHNIQUES 23 ADOPT 1. Pipelines as code 22 TRIAL 2. APIs as a product 17 3. Decoupling secret management from source code NEW 4. Hosting PII data in the EU 68 21 66 67 5. Legacy in a box NEW 69 6. Lightweight Architecture Decision Records 16 7. Progressive Web Applications NEW 15 8. Prototyping with InVision and Sketch NEW 70 9. Serverless architecture 14 71 20 ASSESS 7 59 10. Client-directed query 13 58 11. Container security scanning 8 57 72 12. Conversationally aware APIs NEW 13. Differential privacy 14. Micro frontends 6 9 73 15. Platform engineering product teams NEW 19 16. Social code analysis NEW 12 17. VR beyond gaming 5 60 61 74 HOLD 18. A single CI instance for all teams 62 19. Anemic REST 11 4 75 20. Big Data envy 21. CI theatre NEW 18 63 76 22. Enterprise-wide integration test environments NEW 3 55 23. Spec-based codegen NEW 10 1 64 56 65 77 PLATFORMS 2 ADOPT HOLD ASSESS TRIAL ADOPT ADOPT TRIAL ASSESS HOLD 24. HSTS 25. Linux Security Modules 32 33 81 89 103 TRIAL 34 26 80 26. Apache Mesos 35 24 78 102 27. Auth0 88 28. AWS Device Farm NEW 79 29. AWS Lambda 36 25 30. OpenTracing NEW 87 101 31. Unity beyond gaming 37 27 100 ASSESS 32. .NET Core 38 28 85 33. Amazon API Gateway 86 99 34. api.ai NEW 39 83 35. Cassandra carefully 29 31 98 36.