Kristian Zhelyazkov is a developer at SAP working on Gardener, the SAP-driven Kubernetes-as-a-service open source project. In this guest blog post, he explains why the project is moving its logging stack to Loki.
Production environment stability and high availability are the holy grail of every SaaS company. R&D organizations put a lot of effort into achieving these goals by implementing different monitoring and alert methodologies and by utilizing a variety of systems and tools. Mean-time-to-detect (MTTD) and mean-time-to-repair (MTTR) are two crucial KPIs that help R&D management personnel determine the efficiency and proficiency of their teams’ responses to production incidents.
This article provides an overview of managing and analyzing Docker logs and explores some of the complexities that may arise when looking through the log data. We will go through the default logging approach, as well as look at some more advanced configurations that will make diagnosing issues in your Docker-hosted applications much easier going forward.
Kibana is considered the “window” to Elasticsearch and indeed it’s a powerful UI for searching, filtering, analyzing, and visualizing Elasticsearch data, but Kibana settings are also used to configure, administer and monitor the Elasticsearch cluster. In this lesson, we’re going to explore how Kibana settings can be tweaked for collaborative teamwork. Without further ado let’s jump right into spaces!
