After some time the metric was remove from the results because there were no new errors. After a period of empty Three more errors occurre we will not see them anymore Unfortunately Prometheus in particular the PromQL function rateand similar ones are not able to cope with such gaps in the data. Instead it expects the metric to continue to flow throughout the period. To address this limitation we modifie the Vector code to remove the . This evasive maneuver was successful. Case No. Kubernetes control layer failure.
Potential cardinality bom
One day we notice that the Kubernetes control layer was crashing when Vector pods were restarte at the same time. After analyzing the dashboards we found out that the problem is relate to excessive memory usage primarily etcd To better understand the reason we had to Panama WhatsApp Number List dive into the internal kitchen of the Kubernetes API. When a Vector instance starts up it makes a LIST request to the Kubernetes API to populate its cache with pod metadata. As state earlier Vector uses this metadata to enrich the log entries Accordingly each Vector instance aske the Kubernetes API for the metadata of the pods on the node on which Vector was running. At the same time for each individual request the Kubernetes.
The three main parameters
API reads data from etcd . etcd is a keyvalue database. The keys contain the type namespace and resource name registrykindnamespacename Vector uses kubeapiserverfieldSelector to request only data from the pods on average pods on its node . But since there are no data Bosnia and Herzegovina Phone Number List when querying etcd you nee to get the data of all pods in the cluster filter them and give Vector its pods. This leads to a sharp increase in memory consumption for both kubeapiserver and etcd and ultimately ends in a crash There are two ways to solve this problem. First you can use reading from the cache.
