Operations | Monitoring | ITSM | DevOps | Cloud

One of the great pleasures of life, next to sunbathing parallel to a swimming pool, walking along the beach at sunset or eating chocolate in all its aspects, is the fact that we can relate, in this blog, elements of science fiction with elements that we can count on today in real life and that no one seems to have noticed. That’s why today, in “Pandora FMS News“, we’ll talk about temperature monitoring, something that’s already available to everyone.

In this article you will learn how to generate Jaeger model classes and gRPC services from protobuf definitions. The generated code can be used to write integrations or it can be used in tests to query tracing data from Jaeger-query service. This is the use case we are going to look at in more detail.

The Software Development Life Cycle (SDLC) refers to a methodology with clearly defined processes for creating high-quality software. in detail, the SDLC methodology focuses on the following phases of software development: This article will explain how SDLC works, dive deeper in each of the phases, and provide you with examples to get a better understanding of each phase.

We’re excited to share our first-ever alpha feature: sensuctl prune, which will help you easily (and safely!) remove resources you no longer need.

While the recent pandemic has removed much of the traffic from the roads, it has led to an unusual increase in traffic on the internet. Online services are reporting a huge increase in the number of visitors and requests, making it tough to keep up with seamless service delivery. While service providers and experts say the internet can hold up for now, organizations are already implementing measures to prevent network congestion and interruptions in service during the continuing pandemic.

With a service designed to help remote teams run more efficiently, Tability’s success relies on application reliability and deliverability to help its users keep complicated projects on schedule. This is why Tability has relied on Sentry error monitoring to identify issues in code and scale development work efficiently.

Historically, the monitoring landscape has been a mess; today, it still is. It’s even worse given how software architectures have changed with all of the cloud-native principles. As “techies”, we need to do something about this. Otherwise, we’ll remain chained up by an inability to properly observe our own platforms and applications.