Operations | Monitoring | ITSM | DevOps | Cloud

May 2022

Improve Performance in your iOS Applications - Part 3

Although modern iOS devices are capable of handling a wide range of intensive and complex tasks, the device may seem slow if you are not paying close attention to how your application operates. Performance improvements mentioned in this article are intended to make your code more readable and performant; however, select cautiously as per your needs. Oftentimes, altering or improving architecture and code refactoring takes more time and effort.

Monitoring Performance and Errors in a Django Application with Sentry

Sentry is a monitoring platform that allows developers to track errors and performance data. In this tutorial, we’ll show you how to add Sentry to a Django application so that you can track and resolve any errors or performance issues that occur while your application is in production.

Exception Handling in Java (with Real Examples)

Java has been one of the most widely used programming languages among developers worldwide for years. So naturally, it is a popular choice for those beginning their careers in development. Learning Java requires more than just knowing the proper syntax and effective code hygiene. Any developer who hopes to use Java for commercial development must be able to quickly and competently identify and recognize errors in their code.

A Developer's Take On Solving Hard-to-Replicate Performance Problems In-Production

Causal is the business and financial planning platform that allows users to build models effortlessly, connect them directly to their data, and share them with interactive dashboards and visuals. Teams rely on them to build complex models with real business impact, so the UX needs to be fast and reliable, and for the team to guarantee that, they need detailed visibility into the performance of their application.

Time Saved Monitoring Deployments Is Time Spent Building Better Products

Bigeye is the data observability platform that teams at companies like Zoom and Instacart use to keep their data pipeline fresh, high quality, and reliable. Their customers depend on them to detect problems in their data pipelines 24/7 and to keep data reliable enough for production use cases of analytics and machine learning. In this environment, margins for error are razor thin and waiting for a user to let you know that something isn’t working means it’s already too late.

Improve Performance in your iOS Applications - Part 2

The performance of your iOS app is crucial when building and publishing it for any number of users. Your users expect it to be delightful, fast and responsive, so if your app seems sluggish or unresponsive, it will affect your reviews and you might lose valuable users. While solving this for your apps, it’s easy to overlook the influence of the choices made on performance throughout development.

Workflow 2.0

This is a conversation we had with our Engineering, Product, and Design (EPD) organization. We are publishing it as we believe it’s important to our customers and fundamental to our open source approach. You can join the conversation on GitHub. Lately, I am spending a lot of my time thinking about Sentry and its core developer story. I also consider why we haven’t been able to overcome the main challenges we recognized years ago.

A Pound of Cure - Why Sentry Matters

Benjamin Franklin was a smart dude. Among the many wonderful things he produced was an eternal bit of wisdom - an ounce of prevention is worth a pound of cure. To avoid a bigger problem, spend time early on the things that help you avoid it. That wisdom applies everywhere. Avoid nasty stuff with doctors by exercising and making healthier choices. Avoid getting hit by a car by looking both ways. Avoid sunburn by wearing sunscreen. You get it. So what does this have to do with Sentry? A lot.

Equipping Developers with the Tools to Succeed at Scale

Forethought is a leading AI company providing solutions that transform the customer experience. As a high-growth startup with 2x annual growth in their engineering team, they faced increasingly complex processes and found that what had worked in the past wasn’t going to cut it anymore.