Cabify, a leading ride-hailing company, revolutionized its mobile engineering process by focusing on improving app quality and performance, resulting in faster release cycles and top-notch user experiences.
A hands-on guide to using Bitrise Pipelines to speed up your mobile CI/CD Workflows.
A paradigm shift is overdue in the realm of software observability. While Site Reliability Engineers (SREs) have been having fun with metrics, traces, and logs, software developers have been left in the lurch, shackled to the conventional, low-fidelity tool of logs. Why should SREs have all the fun, right? Welcome to the dawn of a new era. An era where developers, too, can enjoy superior observability engineering. That’s where the fourth pillar of observability comes in: Snapshots.
Enterprises are investing in data mesh initiatives to accelerate how decisions are made and to create novel experiences based on machine learning models. Similarly, enterprises are investing in API platform initiatives to productize business domains (or bounded contexts in domain-driven design parlance) as self-service digital assets that accelerate innovation and improve business agility. Both initiatives are typically run as separate work streams.
You're overseeing your delivery logistics from your dashboard when an alarming notification surfaces - one of your drivers has had a minor accident and they're unable to finish their route. You start considering your options. Is there a replacement driver close by? Is there a spare vehicle available for the original driver? Just as you're figuring things out, another alert arrives: your driver is okay and the delivery is still on time.
Exploratory testing has become a more common topic amongst testers. Exploratory testing provides valuable quality related insights that otherwise would escape unnoticed. Unfortunately there’s still a long way to go until everyone can unlock the full potential exploratory testing. Not everyone has heard about it, not everyone understands exactly what it is, not everyone has taken the most out of it.
In our last post, we examined the most common ways to organize business logic in Ruby on Rails. They all have advantages and drawbacks, and essentially, most do not leverage the full power of Object Oriented Programming in Ruby. This time, we will introduce another alternative that more naturally fits the mental models we apply when reasoning about the behavior of our applications: DCI.
Puppeteer is a powerful browser automation library for web scraping and integration testing. However, the asynchronous, real-time API leaves plenty of room for gotchas and antipatterns to arise. This article is part of a series, starting with Avoiding Puppeteer Antipatterns and Puppeteer in Node.js: Common Mistakes to Avoid. In this post, we'll add another dozen antipatterns to the list. There will be no overlap with previous installments, so you may wish to start with those.
Do you know that log files in Linux can quickly consume disk space if not managed properly? This can lead to performance issues and even system crashes. Log files? What exactly are they, and why should they matter to anyone using Linux-based systems? Log files are essential components of any Linux-based system. They are text files that contain information about system events, including errors, warnings, and other important messages.
