Over the years, we’ve heard many versions of the same familiar story: large businesses struggling with observability data living in several different systems. At Grafana Labs, our “big tent” philosophy is based on the belief that our users should determine their own observability strategy and choose their own tools. Grafana allows them to bring together and understand all their data, no matter where it lives.

In the first post of this series, we covered the general idea and benefits of model-driven observability with Juju. In the second post, we dived into the Juju topology and its benefits with respect to entity stability and metrics continuity. In this post, we discuss how the Juju topology enables grouping and management of alerts, helps prevent alert storms, and how that relates with SRE practices.

As I said before, Speed is King. Business requirements for applications and architecture change all the time, driven by changes in customer needs, competition, and innovation and this only seems to be accelerating. Application developers must not be the blocker to business. We need business changes at the speed of life, not at the speed of software development.

As developers, we spend a lot of time in our IDEs writing new code, refactoring code, adding tests, fixing bugs and more. And in recent years, IDEs have become powerful tools, helping us developers with anything from interacting with HTTP requests to generally boosting our productivity. So you have to ask — what if we could also prevent security issues in our code before we ship it?

Register for the webinar and download the full study to see and apply Forrester’s financial model to determine the observability ROI for your organization. Many teams want to adopt observability and Honeycomb—but run into budget roadblocks because budget holders may not clearly understand the quantifiable benefits to their end users, their teams, and the bottom line.

A fundamental element of the Kubernetes microservices system is the services model, which gives teams greater understanding of how their applications are deployed. These objects running within pods and containers, by extension, are RESTful since they’re based on APIs. However, DevOps teams can’t hope to run a tight ship without managing their services. Communication and visibility are absolutely crucial in a Kubernetes system.

In the first post of this series, we covered the general idea and benefits of model-driven observability with Juju, but did not dive deep into the idea of contextualization and how it makes observability more actionable. In this post we start addressing what contextualization means in model-driven observability, starting from adding Juju topology metadata added to telemetry, and how that improves the processing and querying the telemetry for charmed applications.

Companies are always looking for transparency and visibility when it comes to monitoring, but as monitoring requirements and methods evolve, it’s not always easy to keep up. That’s why Opsdis, an observability consulting company based in Göteborg, Sweden, was founded. The firm focuses solely on helping clients implement systems for monitoring and metrics so they can keep up with the ever-expanding world of cloud computing and containerized environments.