This month is the inaugural edition of Build, the monthly newsletter from Pivotal that provides a snapshot of the most relevant news and trends for developers and architects.
This month, we find that containers have broken out of their containment as the hottest news topic with moves from Amazon and Docker as well as Pivotal and CoreOS Rockets. We look at the latest news in mobile app development with a lesson about the need for scale from Best Buy, and explore some interesting use cases, techniques and releases. Lots of interesting news in app design including the intriguing idea that technology might be better if it could work without constantly nagging for the user’s attention. Lastly, we explore the importance of building for scale, how cloud has changed the economics of apps at scale, and how data-driven apps can perhaps save industries such as journalism.
Featured: Containers
Containers were the hottest topic across the software industry this past month, with key players making big moves to address the topic. Amazon announced a free EC2 container service that is a simpler and easier way of scheduling and maintaining Docker containers, breaking from the path that Google and Microsoft are on where Kubernetes orchestration is supported. CoreOS, with the support of Pivotal, highlighted how Docker has possibly become too many things and published Rockets as a more focused way to create a POSIX, portable operating system interface, equivalent for containers.
Recommended Reading:
- AWS squares up against Google in the Docker war
- Cue Some Docker Tensions. Arise The First Of The Breakaway Container Solutions
- Launching Rockets—Collaborating on Next Level Linux Containers
Mobile Development
With so many customer touchpoints being delivered via mobile, it is now mission critical to customer experience, and failing to scale can cost sales, as Best Buy found out on Black Friday. At the same time, mobile product leaders are looking more towards loyalty and retargeting as where the puck is headed and, as we highlight, considering numerous ways to improve their mobile apps, like with unbundling. Wearables and IoT industries continue to evolve with Apple Watch Dev Kit and a reflection on building IoT standards to work better than RFID standards.
Recommended Reading:
- BestBuy’s Black Friday: The Need for Highly Scalable E-Commerce Infrastructure
- Improving the The Loyalty of Mobile App Usage Through Retargeting
- 3 Killer Ways to Up Your Mobile Game in 2015
- Get Your iPhone Ready for Apple Watch – Dev Kit Available
- HBR: Setting standards for the Internet of Things
App Design
We heard some interesting insights recently on the important collaboration between design and technology as well as users and designers. Perhaps the future of application design leads to a place where apps work with us more symbiotically or consuming less of our attention—disappearing, not nagging us, and using natural language processing.
Recommended Reading:
- Four Examples of the Symbiosis between Design and Tech
- The Right Questions to Ask Before You Build Software
- The Amazing Case of the Disappearing Technology
- Rejoice: Tomorrow’s Tech Will Probably Stop Nagging Us
- Using Natural Language Processing and Text Analytics to Make Useful Software
Data & Scale
While a humorous retrospective is always fun, you can’t appreciate cloud economics unless you look back at history to compare the old and new models to see infrastructure begin to look like software for incremental cost. Adding this to open source economics really underscores what is happening in today’s world and how far we have to go in terms of scale. In addition, we are seeing companies like GE achieve the economics they envisioned for the industrial internet. Maybe data-driven apps at scale can even save fields like journalism that are under threat from digital transformation.
Recommended Reading:
- How Cloud Computing has Changed IT’s Underlying Economics
- The Scale Imperative, A Must Read Overview of Software and Cloud Economics
- How GE Uses Pivotal to Power Analytics and Scale Big Data
- Data can Save Journalism or Can It?
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