Python powers many applications we use in our day-to-day like Reddit, Instagram, Dropbox, and Spotify. The adoption of Python 3 has been a subject of debate in the Python community. While Python 3 has been out for more than a decade now, there wasn’t much incentive to migrate from the stable Python 2.7 in the earlier releases. If you’re still running on legacy python, it’s high time to migrate as it has reached the end of its life since Jan 2020.

At Rollbar we love workflow automation. With our new Notifications API, you can automate setting up of custom notification rules for all your Rollbar projects. As more of our customers switch to microservices, we wanted to build a programmatic way to set up these rules for multiple projects or services in just a few seconds, without having to go to the UI.

This blog post will explain how to effectively profile your website so that you can deal with performance pain points. We’ll go through the two most used tools in Google Chrome for profiling: Imagine that you optimized your backend and everything is running smoothly. However, for some reason, the load time of your pages is still unreasonably high. Your users might be experiencing sluggish UI and long load times. This post will help you sort these issues out.

The Swift Package Manager allows you to create standalone Swift applications both on Linux and macOS. You can build and run these apps and you have the ability to write unit tests for your codebase. Xcode ships with the XCTest framework, but you may not know that this is an open-source library. It's available on every single platform where you can install Swift.

We are excited to announce our new partnership with AppDynamics at their global event Transform 2020. Deep Code Insights (DCI) powered by Rookout will be generally available within the AppDynamics platform starting today. ‍ The partnership was a no-brainer: AppDynamics’ APM solution helps developers become aware of problems quickly; Rookout helps developers debug those problems easily. It’s a match made in devops heaven!

Today, service architecture is becoming increasingly complex with the explosion of new software techniques such as microservices. However, the performance of a system often is dependent on engineers’ ability to debug gnarly problems. The increase in complexity that comes with new microservices architectures makes debugging that much harder. In fact, some companies are considering reverting back to monoliths because of the increased difficulty of debugging, among a host of other challenges.

CAI stands for Continuous Application Improvement. It is a software improvement process that is implemented at each step of the SDLC, ensuring immediate feedback at each step rather than waiting till risk levels and impact has gone up. When you implement CAI you shift your improvement process as far left as possible and you catch software bugs and performance problems where they are introduced, eliminating countless hours of time spent chasing issues.

Let me start by introducing myself properly: I’m Renat Zubairov, CEO and Co-Founder of a Germany-based company elastic.io, part-time techie, part-time sales, full-time father of three. And I will be hosting a topic at the SaaStr Annual Braindates 2020. While working at our previous companies, Igor, Rico (the other elastic.io co-founders) and I realized how much of a challenge the traditional software business model posed for enterprises.

We are continuing our blog series about implementing real-time log aggregation with the help of Flink. In the first part of the series we reviewed why it is important to gather and analyze logs from long-running distributed jobs in real-time. We also looked at a fairly simple solution for storing logs in Kafka using configurable appenders only. As a reminder let’s review our pipeline again

Last September, the revised Payment Services Directive 2 (PSD2) went into full effect, shifting open banking from futurism to a regulatory requirement for retail banks. But the EU is not alone in wanting to open up consumers’ financial data via APIs (application programming interfaces) to trusted Third Party Providers (TPPs). Neobanks and fintechs have been marrying technology and customer data as a market-grabbing strategy, thus increasing their competitive edge.