DeveloperWeek 2019

Companies are increasingly disaggregating their architectures with approaches like microservices, serverless and APIs to scale. We have seen these disaggregated components become network accessible. We call them endpoints. Whether it is data, apps, APIs, microservices, or serverless functions, everything is becoming a programmable endpoint. The apps we develop today increasingly depend on these endpoints, and these apps can also become programmable endpoints. We need programming languages with much higher level network-aware abstractions to model such applications. Ballerina is a strongly typed, concurrent general purpose language optimized for integration and writing network services and applications. It combines fundamental concepts and tools of distributed systems with direct support for network services, distributed transactions, reliable messaging, stream processing, security, and workflows. It is intended for commercial adoption and provides familiarity for users of Java, C#, and JavaScript. While it looks like Java and other popular languages in some ways, it is very different from those in fundamental ways. This talk will explore how Ballerina is different, why it is different and how those differences give Ballerina an unfair advantage when it comes to writing resilient, performant and secure network services and applications.

Want to take your Xcode skills to the next level? Join me as we take a literal journey through various tips, hacks, and tricks that can make you a more efficient iOS developer. Aimed at iOS developers from beginner to advanced, in this session attendees will walk away with at least one new trick up their sleeve to impress and delight their fellow iOS engineers.

Python has quickly become THE language for network automation and programmability due to it’s combined simplicity and power. Add to that the robust assortment of tools, libraries and modules related to networking available to “import" and I doubt another language will take over the title anytime soon. In this session we’ll explore some of the most useful libraries for network engineers and developers looking to interact with the network from a configuration and operational perspective. Plenty of code will be shown, and all examples will be available to take away and leverage in your own environments. Through the session you'll learn how to leverage the tried and true interfaces of CLI and SNMP to manage your network before we jump up to newer options like NETCONF, RESTCONF and REST APIs. We'll even explore full configuration management solutions and discuss when and how they should fit into your overall automation strategy. Some of the great modules that will be covered include: netmiko PySNMP ncclient requests Ansible NAPALM

Having API client libraries in multiple languages is great, but what happens when you make a change to your API and need to update all those libraries? Are you efficiently keeping them consistent and up-to-date? In this session, I'll speak about effective methods of keeping those libraries updated, and show you how Kaltura's been doing it easily, and efficiently, for years. I'll also discuss what I learned while creating a new Client Library Generator in GO, and how you can easily create one on your own.

Since Facebook released GraphQL to the world, there has been a lot of traction on the frontend world about it. But somehow, this trend hasn’t reached backend developers. Let’s take a look into how we can introduce GraphQL into our Ruby environments to take advantage of it’s power. Let’s look into the state of GraphQL in Ruby and see how we can benefit of the amazing power that GraphQL APIs can provide us. We’ll also take a deep-dive into a tool I wrote called GQLi, a GraphQL client that enables users to write queries in native Ruby code. I’ll describe it’s philosophy, how to use it, and some cool meta-programming tricks used to create it.

GPU computing has becoming an important part of scientific computing and machine learning. Although somewhat different than traditional programming, GPU computing has become much more accessible thanks to a number of Python projects, such as TensorFlow, CuPy and Numba. In this talk, we’ll survey the Python GPU projects available in Anaconda, discuss some use cases for different projects, and review best practices for GPU computing.

As the complexity and volume of data grows, data teams are optimizing their analytics workflows to support more complex logic, advanced transformations and customized visualizations that will be crucial in future proofing your business. There isn’t an abundance of external conversation about the languages used to analyze these massive quantities of data, but analysts and developers are becoming more sophisticated as their field matures, evolving to work with bigger datasets and integrating new techniques into their workflow. This means more than just finding new ways to innovate with SQL — advanced languages like R and Python have become a more critical part of everyday analysis and should be a centerpiece in the developers “day zero” strategy when building any technology stack. In this presentation, Leon Tchikindas, Head of Data Science & Analytics at Periscope Data, will discuss the advantages of implementing SQL vs. Python & R as part of your developer tech stack strategy and explain how to bring the workflows of all three together on one platform. To illustrate how SQL and Python work together to answer complex data questions, Leon will share real-life examples of how adopting this strategy can impact your business now and in the future. 

PHP still powers over 80% of all websites, despite the frequent criticism it tends to receive. On the other hand, .NET is considered more robust, secure and performant, albeit more complex and not as user friendly. PeachPie compiler is a project that bridges this gap by allowing real-world PHP applications (e.g. WordPress, MediaWiki, Symfony etc.) to run on the cross-platform .NET Core framework.

It's easy to stand up a new .Net Core API in AWS Lamba; the built-in templates can have your api deployed in minutes! Lambda is also incredibly cost effective! Now that you've committed to build your next project on Amazon's serverless platform, it's time to learn about all the little piece the demo didn't tell you. In this session, we will learn about: Debugging serverless applications How to increase performance when there is no server Handling file up- and downloads Managing long-running requests Deploying to AWS Lambda using the Dotnet CLI and Visual Studio Team System Updating configuration information without redeployment, without access to the file system Integrating your api with other Amazon offerings AWS Fargate, when Lamda isn't enough