WHY IT MATTERS: Digital Transformation

One way to avoid fly-by architecture is to have a set of principles that are generally accepted, which become the anchor for discussion as well as learning path for budding architects.

In this recorded briefing RSG founder Tony Byrne takes you on a tour of a new reference model for the omnichannel era. Tony shows you how to guide your future stack investments towards supporting omnichannel needs, and what this means for content, data, decisions, and operations. If you manage one of these tech stacks, this is a must-see educational session.

This document is intended to help those with a basic knowledge of machine learning get the benefit of Google's best practices in machine learning. It presents a style for machine learning, similar to the Google C++ Style Guide and other popular guides to practical programming. If you have taken a class in machine learning, or built or worked on a machine­-learned model, then you have the necessary background to read this document.

IT operations teams struggle to maintain service quality when they apply legacy approaches to monitoring. Infrastructure and operations leaders responsible for monitoring should take the steps outlined here to increase their effectiveness and limit their exposure to challenges raised by the cloud.

A simple introduction for those who always wanted to understand machine learning. Only real-world problems, practical solutions, simple language, and no high-level theorems. One and for everyone. Whether you are a programmer or a manager.

The Technology Radar is an opinionated guide to technology frontiers. The Radar captures the output of the Technology Advisory Board’s discussions in a format that provides value to a wide range of stakeholders, from developers to CTOs. The content is intended as a concise summary.

For the past few months Tesla has been slowly sharing details of its upcoming “Hardware 3” (HW3) changes soon to be introduced into its S/X/3 lineup. Tesla has stated that cars will begin to be built with the new computer sometime in the first half of 2019, and they have said that this is a simple computer upgrade, with all vehicle sensors (radar, ultrasonics, cameras) staying the same. Today we have some information about what HW3 actually will (and won’t) be.

I usually avoid the A-word (architecture) because it's such a slippery term. In this case I'll be following my preferred definition of architecture - "the important stuff (whatever that is)" - from Ralph Johnson. This means I'll talk about what I think is interesting about the system's design, based both on my judgement and on the judgement of the team that's been involved in its development.

This is an industry report designed to establish benchmarks for how organizations are developing and maintaining the quality of software in 2018.

Whether it was here on Hackaday or elsewhere on the Internet, you’ve surely heard more than a few cautionary tales about the “Internet of Things” by now. As it turns out, giving every gadget you own access to your personal information and Internet connection can lead to unintended consequences. Who knew, right? But if you need yet another example of why trusting your home appliances with your secrets is potentially a bad idea, [Limited Results] is here to make sure you spend the next few hours doubting your recent tech purchases.

More than 1,300 people mainly working in the tech, finance and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey.

Test-driven development, or TDD, involves writing tests first then developing the minimal code needed to pass the tests. TDD is an established practice for feature development that can improve code quality and test coverage. What about other, non-functional requirements such as scalability, reliability, observability, and other architectural “-ilities”? How do we ensure operability and resiliency of features when they go to production? How can we encourage teams to build in these architectural standards, just as test-driven development builds in code quality and test coverage?

Now you can add state of the art machine learning features to your applications. Production ready Docker containers that you can run, deploy, and scale.

What Ron and Alex did might might seem like too much work, but really, it isn’t much more than you’d be expected to do in a real job. And that’s the whole point: when you don’t have work experience doing X, hiring managers will look for things you’ve done that simulate work experience doing X.
Fortunately you only need to do build a project at this level once or twice — Ron and Alex’s projects got reused over and over for all their interviews.
So if I had to summarize the secret to a great ML project in one sentence, it would be: Build a project with an interesting dataset that took obvious effort to collect, and make it as visually impactful as possible.

Bjarne Stroustrup, the inventor of the C++ programming language, defends his legacy and examines what’s wrong with most software code.

When comparing or evaluating Customer Data Platforms, people tend to default to feature comparisons. This seems logical, but can risk missing the business forest for the technical trees.

Application leaders engaged in digital transformation must include event-driven computing in their portfolio of skills and technology, including the key related responsibilities for event brokering and event stream analytics.

Continuous Delivery provides great benefits not only for the team developing the software, by increasing their confidence, but also for the product team, since the delivery of new features becomes a pure business decision.

What do an iPaaS, an event-driven architecture and an advanced event broker have in common?

They’re probably all critical to the success of your enterprises’ digital transformation.

Read this paper to learn how you can leverage these tools in unison, to integrate your new and old technologies with modern frameworks and design patterns, and enable real-time event-distribution across all your environments and geos.

Developing fully native applications is like buying a sports car: it’s a fun, full-featured option, but typically expensive and not always the most practical. It should be done after carefully weighing the product’s budget, the mobile app’s strategic importance, and capabilities of the current team.

Below are some guidelines to help you decide which tech stack would best fit your application. The best decision is rarely obvious and can usually only be made after a thorough cost-benefit analysis.

In our 26-criterion evaluation of web content management system (web CMS) providers, we identified the 15 most significant ones — Acquia, Adobe, Amplience, Automattic, BloomReach, Contentful, CoreMedia, Crownpeak, Episerver, Kentico Software, Magnolia, OpenText, Progress, SDL, and Sitecore — and researched, analyzed, and scored them. This report shows how each provider measures up and helps digital experience (DX) and strategy professionals make the right choice.

With such fast-paced change in the technology landscape it's impossible for us to keep everything in view on the latest Radar. Using this A-Z you can browse everything that has ever been featured on the Radar, as well as search for specific technologies that you're interested in.

The Technology Radar is our thoughts on emerging technology trends in the industry. Read the latest here.