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+# Victoria k8s Stack
+
+We use [Victoria Metrics k8s stack](https://docs.victoriametrics.com/helm/victoriametrics-k8s-stack/) and [Vector](https://docs.victoriametrics.com/helm/victorialogs-single/#sending-logs-to-external-victorialogs).
+
+## Why do we use it?
+
+* compare it with competitors like ELK, Loki, Prometheus
+* it delivers logging and metrics
+
+* in ELK we replaced the 'E'(ElasticSearch) by VictoriaLogs and VictoriaMetrics, L(Logstash) is replaced by Vector, 'K'(Kibana) by Grafana 
+* Loki (also the 'E'): has 5 components (like distrubutor, querier, querier-frontend....), VM 
+* ELK is hard to manage
+* Durability: We need to store logs for years, there should be a 'shrink' process 
+* Challenge: Scaling, there are huge amounts of data (like TB/d)
+* we urde for simplicity, cost, scalability
+
+
+## Big Picture
+
+### Architecture
+
+The high level deployment picture of VictoriaMetrics k8 s Stack looks like this:
+
+![alt text](./_assets/vm-deployment-architecture.png)
+
+### Deployment
+
+In detail, after having deployed it, we see the following components:
+
+![alt text](./_assets/vm-pods.png)
+
+1. vector-vector: the log shipper to victorialogs, twice because it is a daemon-set and thus deploed on each node in the cluster
+2. prometheus-node-exporter: a metrics generator and metrics endpoint of node metrics, also deployed on each node
+3. vmagent: the central agent scraping data from the metrics collectors
+4. vmalert: not used yet
+5. vmsingle-victoria-metrics: the metrics server, getting the data from vmagent
+6. vlogs: the logging server, getting the data from vector
+7. victoria-metrics-operator: the operator providing and managing the custom resources we deploy