Working across different time zones can present significant challenges when it comes to fostering a team culture. I came across a typical scenario in a geographically distributed team with their Engineering team members based in New York and Poland. They are set to welcome a new Director of Engineering based on the West Coast. With minimal daily overlap between the teams, the question arose about how to create and manage their team culture.

In modern times, the significance of digital experiences cannot be overstated across various industries. Thus, a well-designed and effective incident management system is essential to ensure the smooth running of businesses and prevent any revenue loss. The ability to respond and resolve incidents promptly enhances the dependability and trustworthiness of businesses in the eyes of their users. Conversely, failure to handle incidents efficiently can lead to negative consequences.

As software development continues to evolve and become more complex, the need for efficient and effective deployment strategies has become increasingly important. This is where deployment pipelines come in. When it comes to software development, a deployment pipeline is a powerful automated tool that facilitates the fast and accurate transition of new code changes and updates from version control to the production environment.

In recent years, the adoption of cloud computing has skyrocketed as more and more businesses realize the benefits of this modern IT solution. With its unparalleled reliability, scalability, and cost-effectiveness, cloud computing has become the go-to choice for many organizations. According to recent estimates, around 90% of businesses are already using some form of cloud computing, and this number is only set to rise in the coming years.

Managing a Kubernetes cluster requires a keen eye for detail and a deep understanding of its complex structure. To ensure smooth operation of your applications and optimal performance, it is vital to monitor a wide range of metrics across the different components of your cluster. In this article, we will discuss key metrics that can be used to monitor both self-managed and cloud-managed Kubernetes environments, helping you to keep your cluster running at its best.

If you’re familiar with the frustration of dealing with a poorly constructed web application or the challenges of providing tech support, you understand the importance of building a high-performing and scalable web application. However, with the numerous considerations involved, it can be overwhelming to determine the starting point. This article aims to provide guidance on how to avoid common pitfalls that negatively impact user experience and waste resources.

Experiencing failure at scale is as the popular Marvel character Thanos would say “Inevitable”. Memory leaks, software or hardware or network I/O failures are just a few. It’s a problem of simple mathematics, the probability of failing rises as the total number of operations performed increases. With each component used to scale the application, the failure quotient increases. So how do you tackle this so-called “Inevitable” problem that comes with scaling?

TL;DR: Data aggregation is the process of collecting and organizing large sets of data from multiple sources in order to provide a comprehensive view of a particular situation or system. It allows organizations to better understand and make sense of the vast amount of data being generated in the modern, highly connected world.

Learn how to prioritize tasks, get stuff moving by performing non-blocker tasks first, effectively create postmortems, perform RCAs faster and not have an overburdened high priority(P0) dashboard. The below article should help you plan your product/feature launch faster without having to compromise on the reliability of the existing services.

Over the last few quarters a couple of interesting patterns have emerged amongst our larger customers who are looking to catalyze cross-team collaboration during a major incident spanning members from multiple teams.