This article discusses four bottlenecks in BigData applications and introduces a number of tools, some of which are new, for identifying and removing them. These bottlenecks could occur in any framework but a particular emphasis will be given to Apache Spark and PySpark.
When Jackie Edwards wrote “Keep On Running” back in 1965, he certainly wasn't thinking about the future of computing. But, it's the Spencer Davis Group grooves that is the soundtrack playing in my head when I think about Kubernetes and the business value it brings. Enabling your environment to “Keep On Running” is just one of many of Kubernetes’ value adds.
Customer experience is a key factor in competitive differentiation in the digital economy. The online business model has changed, and today, the focus has shifted from brands to customers. It would not be an exaggeration to say that customer experience plays a central role in any business model.
When requirements change for your product, there arises a need to change not only the codebase but also the existing data that already lives in production. If you’re performing the changes locally, the whole process seems fairly simple. You test your new feature against a sparkling clean database, the test suite is green, and the feature looks great. Then you deploy, and everything goes to hell because you forgot that production was in a slightly different state.
Have you ever been neck-deep building a new feature? You're working at capacity. You need to test something out so you paste an API key into your source file with every intention of removing it later. But you forget. You push to GitHub. It's an easy mistake, and potentially a very expensive one. In this article, Julien Cretel explores the nuances of this kind of data leak, offers suggestions for recovery when leaks happen and gives us options for preventing them in the first place.
Deciding whether to hire and build an API analytics platform vs purchasing from a third party vendor can be a daunting task. Not only do you need to investigate ROI, you also have to navigate politics and may run into Not Invented Here syndrome, among other things. In the long run, by purchasing a ready made solution like Moesif, your product and engineering teams will be able to focus on what they do best: building products that customers love.
The PHP INI setting memory_limit is important to configure right for two reasons. To help you finding the right memory_limit setting Tideways now offers two additional ways to see the maximum memory in use.
