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Robert Chang piece on how data products have always been an instrumental part of Airbnb’s service. However, engineers have long recognized that it’s costly to make data products.

Robert describes how auto machine learning tools worked together to expedite the modeling process and hence lower the overall development costs for a specific use case of life time value modeling — predicting the value of homes on Airbnb.

He describes:

• What customer life time value is (LTV)
• Machine learning workflow or LTV modeling
• Feature engineering they use (Zipline)
• Prototyping and training in Python
• How they perform model selection

and more. Example of code are included. Great article!

Robert C. Martin (Uncle Bob) post about how move to functional programming began and happened.

He starts with Moore’s law and processor development and how multi-core processors changed the way we design software.

One of software designers responses was to learn Functional Programming (FP). One of our responses was to learn Functional Programming (FP). FP strongly discourages changing the state of a variable once initialized. This has a profound effect upon concurrency.

Authors argues that FP is easier to write, easier to read, easier to test, and easier to understand. Why? Because you don’t have to keep track of the state of the system. The state of variables can’t change; so the state of the system remains unaltered.

Interesting article with bit of code in Clojure.

George Crump wrote introductionary blog post about scale-out storage - which provides data centers the ability to create infrastructures that can scale to meet the capacity demands of hyper-scale environments. He focuses on the challenge involving storage scale in docker environments.

The problem is that most scale-out architectures, whether they are dedicated to storage or share CPU with application and services, are hard set to the amount of CPU power they will use per node.

Project Longhorn

Storage compute challenge in hyperconverged architectures is more obvious in container environment with potentially thousands of new instances. Project Longhorn is a block storage system. It essentially containerizes each block storage volume into a dedicated controller, and runs each controller on the same host the storage is consumed.

Project Longhorn is 100% open source software. It takes data protection very seriously - and it is not just for docker. How? Read more …

Kenneth White excellent blog post exploring his experience with using Chromebook as his main development station after 2 weeks of usage.

Author fully appreciates Google’s Chrome OS design. The architecture benefited from a modern view of threat modeling and real-world attacks. Chromebook is also the daily driver for many of Google’s own senior developers and security engineers.

The point of this exercise was to retain the hardened posture of the platform and have a flexible, safe development environment without depending on the crutch of privileged access.

Author describes in depth:

• What his motivation and goals were
• Chromebook supported gear
• Lists hardware
• Authentication and security
• Android apps used for daily development work

… and much much more. Great!

Harrison Davis has written article in which he collected 9 tips how to become better front end developer.

Whether you are a newbie or professional, chances are that some of these points will help you to bring your front-end development career to the next level.

Some tips he mentions:

• Take automation to the next level
• PLan your project
• Be proactive

… and more. Each tip contains explanation why it is useful, the tooling you may use and links to other resources related to the tip. If you are not going forward, you are going backwards, especially in web development ;)

Recommended reading!

@AshNuq from Lightbend posted about usage of akka streams in mission critical systems by large online payment industry leaders including PayPal, Credit Karma and Flipkart. These are collectively worth well over $50 billion in market capitalization.

Reactive Streams - asynchronous stream processing with non-blocking back pressure - which ensures that fast data sources don’t overwhelm the stream destination.

For enterprises dealing with streaming workloads that may never end, Akka Streams has proven to provide the availability, scalability, and resilience needed for production systems.

Author then looks into how each of above mentioned companies use akka to process terabytes of data transferred from browsers and mobile devices to their and ensures the data flow reliably, without data volumes overwhelming target data stores.

Charts included. Interesting reading!

Nick Chase from Mirantis quick intro into what we can expect from Kubernets 1.7. This release focusing on production features such as security, extensibility, and stateful applications.

Security - the most notable feature is that data that remains “at rest” such as Secrets and other resources stored in etcd, you now have the ability to protect that information from prying eyes (and programs) with encryption. The Network Policy API enables users to create rules that determine which pods can communicate with each other.

There are other interesting features related to:

• Application development
• Stateful workloads (databases, etcd, Zookeeper)
• Extensibility

and the most intresting Api aggregation which enables new functionality to be added by user that can be accessed in a method similar to the core Kubernetes features.

Thomas Oppong founder of @alltopstartups shares his thoughts on productivity systems and truth about getting work done. What is the inconvenience then?

Many people who hear or read what productivity hacks and strategies won’t do anything with the information. However,author argues that even if you have the system:

• There is no perfect system
• Getting started is the biggest hurdle
• You will never be able to do it all
• Distraction is the enemy!
• There is no perfect time!
• … and … Sometimes the best thing to do is: nothing

We are currently exposed to an unprecedented flood of information and requests than ever before. Being selective, doing less, is the path of the productive. Good read. Also visit Postanly Weekly.

Zach Church interviewed Christian Catalini - an MIT expert - on why distributed ledgers and cryptocurrencies have the potential to affect every industry.

If you haven’t noticed, blockchain is one of big disruptor in fintech industry. In interview they explain:

• What is a blockchain
• How is blockchain related to bitcoin
• Which industries could blockchain disrupt

They also look into time frame when disruption will happen and what impact it will have on markets. Short but informational article. New research, writing, and videos from Catalini and other MIT Sloan faculty members is also available at blockchain.mit.edu.

Lech Głowiak wrote a short blog post titles Why you should know Monix - a library for asynchronous programming in Scala and Scala.js. He tries in 10 minutes or less, to present what Monix library is and convince you that it is good to know it.

Monix contains several abstractions that are useful and sometimes can be found superior to vanilla Scala or Akka counterparts. Some useful abstraction mentioned and compared to vanilla Scala in post:

• Task abstraction that can be seen as a replacement for Future
• MVar inspired by Haskell’s MVar
• Back-pressured streams

Full code example is available in GitHub repository. Dive in for more info!