The latest News and Information on Observabilty for complex systems and related technologies.
Under the hood, Moogsoft Observability Cloud extends AI-based intelligence so that it starts with raw observability data analysis. It discovers your infrastructure services to collect and analyze the time-series metrics locally, along with turning time-series metrics and event data from your existing tools into actionable insights.
Over the past four days, Grafana Labs' ObservabilityCON 2020 brought together the Grafana community for talks dedicated to observability. We hope you enjoyed all of the sessions, which are available on demand now. (Link to them from the schedule on the event page). The conference wrapped up with predictions and advice from observability experts, lessons in failure, and Grafana Labs team members showcasing ways Grafana and other tools fit into an observability workflow.
Have you seen Lambda: A Serverless Musical? If not, you really have to. I love Hamilton, I love serverless, and I’m not trying to be a crank or a killjoy or police people’s language. BUT, unfortunately, the chorus chose to double-down on one of the stupidest and most dangerous tendencies the serverless movement has had from day one: misunderstanding and trash-talking operations.
Today, every company is a software company and digital business is a core strategy for many organizations. To gain the much-needed agility and efficient scalability, companies in all verticals are modernizing their infrastructure by moving to hybrid, multicloud and cloud-native environments. Realizing that modern applications run on modern infrastructure, IT leaders are prioritizing infrastructure modernization initiatives.
Observability is made up of metrics, logs, and traces. These pillars help us understand the behavior of applications under normal execution, which further accelerates identifying anomalies in case of application failure or deviation from normal execution. Logging is not about tracing each and every operation, it is about sensible, consistent, and machine-readable log messages that expose the application behavior.
We often say that Honeycomb helps you find a needle in your haystack. But how exactly is that done? This post walks you through when and how to visualize your data with heatmaps, creating a log scale to surface data you might otherwise miss, and using BubbleUp to quickly discover the patterns behind why certain data points are different.
