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Central logging for Kubernetes users
Shape Shifter
In conventional setups of the past, admins had to troubleshoot fewer nodes per setup and fewer technologies and protocols than is the case today in the cloud, with its hundreds and thousands of technologies and protocols for software-defined networking, software-defined storage, and solutions like OpenStack. In the worst case, network nodes also need to be checked separately. If you are searching for errors in this kind of environment, you cannot put the required logfiles together manually.
The Elasticsearch, Logstash, and Kibana (ELK) team has demonstrated its ability to collect logs continuously from affected systems, store them centrally, index the results, and thus make them searchable. However ELK and its variations prove to be complex beasts. Getting ELK up and running is no mean achievement, and once it is finally running, operations and maintenance prove to be complex. A full-grown ELK cluster can massively consume resources, as well.
Unfortunately, you don't have a lot of alternatives. In the case of the popular competitor Splunk, a mere glance at the price list is bad for your blood pressure. However, the Grafana developers are sending Loki [1] into battle as a lean solution for central logging, aimed primarily at Kubernetes users who are already using Prometheus [2].
Loki claims to avoid much of the overhead that is a fixed part of ELK. In terms of functionality, the product can't keep up with ELK, but most admins don't need many features that bloat ELK in the first place. Unfortunately, ELK does not allow you to sacrifice part of the feature set for reduced complexity. Loki from Grafana opens up this door. In this article, I go into detail about Loki and describe which functions are available and which are missing.
The Roots of Loki:Prometheus and Cortex
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