Choosing a programming language is one of the most crucial decision when developing software - the choice can influence the way you and your team think about your problem domain and how you model it.
Is this new language just hype, or will it actually help our team to be more productive?
As developers, we need to be aware of the languages topping the hype curve and focus on the production-ready ones that provide real functionality. We also need to understand the exciting updates to older languages like Java and how ones like C++ are still incredibly important in a newer era.
Automation has improved productivity across entire sectors. Software has driven much of this automation, but many workflows still require decisions by humans.
The promise of machine learning is to automate the decision-making process by training algorithms, based on empirical evidence. That promise is becoming very real and tangible for developers who are now able to leverage massive amounts of data with cloud computing power via learning libraries like TensorFlow and frameworks like MXNet.
How can today's engineers take advantage of modern learning methods?
What are the main ideas and pitfalls when trying to automate decisions?
How can organizations harness the power of machine learning to power their business?
It would be almost impossible to build a modern application without APIs. With the rise of Mobile and IoT, more and more companies are offering public APIs to developers to to create an integrated and seamless experience for their users. For modern enterprise systems, which are often distributed, good APIs are the glue holding it all together - making sure the right services have the right information at the right time.
The talks in this topic are filled with practical lessons to help you build, use and maintain APIs while enhancing application security.
Is your child’s doll listening to their conversations? Is someone else controlling the heating in your house?
Everything nowadays seems to be “smart” and connected but are we prepared for the Internet of Things to be the new normal?
IoT no longer just means controlling a device from your smartphone. IoT equals ecosystems – some isolated, some connected, and some ready to be connected in a near future.
As more devices communicate with cloud-based systems, our world should be getting smarter but more connected devices also creates new unforeseen risks, with security being the most prevalent.
In this track, speakers will provide a 360-degree view on IoT covering topics like balancing security needs against intuitive user experience. We will look into the future of IoT and present concrete examples from the current world of connected devices and ecosystems.
We live in a time where the hierarchical structure of teams with managers is moving to a new model of tribes with leaders. In the ideal version of this new landscape, the expertise of developers and specialists is recognized and everyone is involved in the decision-making process.
How can we make this transition?
How do we cope with our new roles?
What works and what doesn’t?
Behind every online interaction is a real live person with their own unique background, perspectives, biases and context. To be successful we must embrace and nurture our relationships with other humans, whether they are community members in an open source project, founded start-up or work for a huge corporation.
Cloud Native means building apps designed specifically to leverage cloud computing, often defined as container-packaged, dynamically managed and microservices-oriented. This architectural pattern allows systems to be self-healing, auto-scaling and highly available.
Organizations can radically reduce costs leveraging the efficiency of cloud computing when using Cloud Native technologies.
But which problems will adopting Cloud Native solutions actually solve?
Where do we start and how can we best strategize for a successful Cloud Native journey?
Testing is an increasingly integral part of how development teams deliver software. Gone are the days of outsourcing testing and quality assurance to some other person, team or department. With the adoption of microservices-based architectures and continuous integration processes, many tests can, and in fact should, be automated.
But testing automation doesn’t spell the end traditional testing methods such as end-to-end or exploratory testing. In fact, with modern architectures running in the cloud, new ways of testing have emerged, such as canary testing, resilience testing and chaos engineering. For the modern development team, delivering secure, relatively bug-free software with the features users want requires an integrated, collaborative and robust approach to all levels of testing.
50 years ago, quantum computing was just a theory. Today, quantum programming is getting close to becoming the new reality for software developers.
Quantum computers have the potential for disrupting how we fundamentally store, process and utilize data and could provide significant breakthroughs in the optimization of complex systems, artificial intelligence and many other areas. Universities around the world are investing heavilty in quantum computer research. Companies like Google, IBM, Microsoft and Rigetti Computing are making it possible for the rest of us to actually leverage quantum processors in the cloud.
So, how we can we, as developers, get started with quantum programming? And what kinds of problems will quantum computers actually solve?