Curated articles, resources, tips and trends from the DevOps World.
Software deployment tools allow developers to ensure that software is properly installed with it’s required packages and implementation steps conducted in the correct order. Using these tools is a vital requirement for any business that creates its own software in-house.
When it comes to data processing, two names stand above all else; Hadoop and Spark. The comparison below looks at both tools across different categories, making it easier for you to decide which tool represents a better fit for your needs:
In our latest guide helping business analysts improve their knowledge of vital tools and resources we are covering BABOK also known as the Business Analysis Body of Knowledge, why is this such a popular resource for business analysts and where can you get a copy?
In our latest guide covering the essentials and best practices for software development we are detailing some of the necessary basics that you need to know about unit testing before you get started.
Choosing whether to go with PostgreSQL or MySQL depends on your needs as they are both great databases to use under different circumstances. In this article we will run through a few of the top reasons and use cases to help you choose between these choices for database creation.
Incident management tools allow technology and security teams to resolve major incidents faster including urgent issues that may lead to businesses seeing application and site downtime affecting their users.
Continuous Integration (CI), Continuous Delivery (CD) and Continuous Deployment (CD) are three processes that automate integrating software development into a product and deploying the modified product to test and production environments.
Python is a very popular high level programming language that is often compared to Perl, Java & Ruby. It is a general purpose scripting language that also implements the concepts of object oriented programming.
The realm of computing is endlessly vast, and programmers can utilize numerous programming languages that facilitate logging. Novice programmers often wonder, why is Python considered the ideal language to learn logging?
In our industry, we often like to use the analogy of building a house when we describe how we build software. In our house-building analogy, this would be the blueprint of the house or the process that we are going to follow to construct a home or software.
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