IT Cloud - страница 21

** snmp_exporter – SNMP protocol metrics;

** mysqld_exporter – MySQL database metrics;

** consul_exporter – Consul database metrics;

** graphite_exporter – Graphite database metrics;

** memcached_exporter – Memcached database metrics;

** haproxy_exporter – HAProxy balancer metrics;

** CAdvisor – container metrics;

** process-exporter – detailed process metrics;

** metrics-server – CRU, Memory, File-descriptors, Disks;

** cAdvisor – a Docker daemon metrics – containers monitoring;

** kube-state-metrics – deployments, PODs, nodes.

Prometheus supports remote data writing (https://prometheus.io/docs/prometheus/latest/configuration/configuration/#remote_write), for example, to TSDB distributed storage for Prometheus – Weave Works Cortex, using a setting in the configuration, which allows data analysis from multiple Prometheus:

remote_write:

– url: "http: // localhost: 9000 / receive"

Let's consider his work on a ready-made instance. I'll take www.katacoda.com/courses/istio/deploy-istio-on-kubernetes for this and go through it. Our Prometheus is located on its standard port 9090:

controlplane $ kubectl -n istio-system get svc prometheus

NAME TYPE CLUSTER-IP EXTERNAL-IP PORT (S) AGE

prometheus ClusterIP 10.99.70.170 9090 / TCP 6m59s

To open its UI, I'll go to the WEB tab and change the address 80 to 9090: https://2886795314-9090-ollie08.environments.katacoda.com/graph. In the input line, you need to enter the desired metric in the PromQL (Prometheus query language) language, as well as InfluxQL for InfluxDB and SQL for TimescaleDB. For example, I will enter "CRU", and it will display me a list containing it. There are two tabs under the line: a tab with a graph and a tab for displaying in a tabular form. I will be looking at a tabular view. I selected machine_cru_cores and clicked Execute. Common metrics usually have similar names, for example machine_cru_cores and node_cru_cores. The metrics themselves consist of the name, tags in brackets and the value of the metric, in the same form they need to be requested, in the same form they are displayed in the table.

machine_cpu_cores {beta_kubernetes_io_arch = "amd64", beta_kubernetes_io_os = "linux", instance = "controlplane", job = "kubernetes-cadvisor", kubernetes_io_arch = "amd64", kubernetes_io_hostname "=" controlplane ", kubernetes_io_hostname" = "controlplane"

machine_cpu_cores {beta_kubernetes_io_arch = "amd64", beta_kubernetes_io_os = "linux", instance = "node01", job = "kubernetes-cadvisor", kubernetes_io_arch = "amd64", kubernetes_io_hostname = "node01", kubernetes_io_hostname = "node01", kubernetes_io_hostname = "node01"

If the network is MEMORY, then you can select machine_memory_bytes – the size of the RAM on the machine (server or virtual):

machine_memory_bytes {beta_kubernetes_io_arch = "amd64", beta_kubernetes_io_os = "linux", instance = "controlplane", job = "kubernetes-cadvisor", kubernetes_io_arch = "amd64", kubernetes_io_hostname "}

machine_memory_bytes {beta_kubernetes_io_arch = "amd64", beta_kubernetes_io_os = "linux", instance = "node01", job = "kubernetes-cadvisor", kubernetes_io_arch = "amd64", kubernetes_io_hostname = "node901", kubernetes_io_hostname = "node901"

But in bytes it is not clear, so we will use PromQL to translate to Gb: machine_memory_bytes / 1000/1000/1000

{beta_kubernetes_io_arch = "amd64", beta_kubernetes_io_os = "linux", instance = "controlplane", job = "kubernetes-cadvisor", kubernetes_io_arch = "amd64", kubernetes_io_hostname = "controlplane", kubernetes_io25}