Operations | Monitoring | ITSM | DevOps | Cloud

When we launched Qovery in January 2020, our product was still a prototype, and we onboarded 53 developers to help them deploy their apps in the cloud. At the time, we were only 2 on the team, and our first employee (Patryk Jeziorowski) decided to join us after being one of our first users. 18 months later, 3004 developers from more than 110 countries use Qovery to deploy their apps on their AWS and Digital Ocean account.

Let's all face it, on call work isn't fun. But it can be better. Even if you have to work on call, it would be nice to have at least some of the work done for you, before you drag yourself out of bed at 3am to respond to an incident.

With the rise of microservices based cloud applications & its corresponding complexities, the need for observability is greater than ever. This blog looks into the what-why of distributed tracing along with few best practices to adopt for the same in microservices architecture. Distributed tracing for Microservices architecture is an emerging concept that is gaining momentum across internet-based business organizations.

Kubernetes enables teams to deploy and manage their own services, but this can lead to gaps in visibility as different teams create systems with varying configurations and resources. Without an established method for provisioning infrastructure, keeping track of these services becomes more challenging. Implementing infrastructure as code solves this problem by optimizing the process for provisioning and updating production-ready resources.

Infrastructure monitoring was difficult enough when entire businesses ran off a few bare metal servers in a dusty, forgotten closet. Other IT infrastructure monitoring tools fell short, unable to provide complete and granular-enough metrics in real time, even when we were only dealing with a handful of systems responsible for running every part of the application stack.