Related Content
 |
2 Familiar Problems for Software Developers In the quest for writing good code and delivering the right thing to customers, developers have several challenges. But most of them can be boiled down to two main problems: discovering the real scope, and how to do the work. Interestingly, they’re very similar to the problems faced by testers and others in non-dev roles. |
|
 |
Software Features to Avoid in a Production Environment When developing an application, it’s best practice not to use certain software features in a production environment. These include features related to programming language, the OS, the database, a framework, a web or application server, or a tool. You have to consider the production setup to avoid bugs or server crashes. |
|
 |
Choosing a Linux Distribution for Docker Containers In the Linux operating system, each Docker container does not use a complete operating system kernel; multiple Docker containers can share the same one. Which Linux distribution should you use as the host? Let’s look at the factors that govern the choice of a host OS, as well as the Linux to run within a Docker container. |
|
 |
Breaking Down Apache’s Hadoop Distributed File System Apache Hadoop is a framework for big data. One of its main components is HDFS, Hadoop Distributed File System, which stores that data. You might expect that a storage framework that holds large quantities of data requires state-of-the-art infrastructure for a file system that does not fail, but quite the contrary is true. |
|
 |
Lessons the Software Community Must Take from the Pandemic Due to COVID-19, organizations of all types have had to implement continuity plans within an unreasonably short amount of time. These live experiments in agility have shaken up our industry, but it's also taught us a lot of invaluable lessons about digital transformation, cybersecurity, performance engineering, and more. |
|
 |
Comparing Apache Hadoop Data Storage Formats Apache Hadoop can store data in several supported file formats. To decide which one you should use, analyze their properties and the type of data you want to store. Let's look at query time, data serialization, whether the file format is splittable, and whether it supports compression, then review some common use cases. |
|
 |
5 Pitfalls to Avoid When Developing AI Tools Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of. |
|
 |
Code Integration: When Moving Slowly Actually Has More Risk Many decisions about code branching models are made in the name of managing risk, and teams sometimes pick models that make integration harder in the name of safety. Moving slowly and placing barriers to change can seem safer, but agile teams work best when they acknowledge that there is also risk in deferring change. |
