Unlocking Insights: Exploring Victoria Metrics for Monitoring

Introduction

Victoria Metrics is a high-performance, open-source time-series database (TSDB) designed for handling large volumes of time-series data efficiently. With its scalability, reliability, and cost-effectiveness, Victoria Metrics is a powerful tool for organizations seeking to store, query, and analyze time-series data from various sources, making it an ideal choice for monitoring, IoT, DevOps, and financial analytics use cases.

Key features to remember!!

Here are the key highlights of Victoria Metrics:

1. Compatibility: Seamlessly integrates with Prometheus and Graphite.

2. Ease of Use: Simple setup and operation with a single executable and command-line configuration.

3. MetricsQL Query Language: Offers advanced querying capabilities similar to PromQL.

4. Global Query View: Enables unified data querying from multiple sources.

5. High Performance: Outperforms competitors like InfluxDB and TimescaleDB.

6. Resource Efficiency: Uses less RAM and storage space, ideal for high-cardinality data.

7. Data Protocols: Supports various protocols for data ingestion and backfilling.

8. Advanced Functionality: Includes features like stream aggregation and metrics relabeling.

9. Wide Applicability: Suitable for diverse time-series data workloads.

10. Open Source Cluster Version: Provides a scalable, open-source cluster version.

These highlights showcase Victoria Metrics as a powerful, efficient, and versatile time-series database solution.

Components of Victoria Metrics

The components in the below diagram are not the complete components included.

A POC setup—how to do it?

Installation in local minikube

Step 1: Add the helmchart repository in your local

helm repo add vm https://victoriametrics.github.io/helm-charts/
helm repo update

Step 2: Search for the VM repo

helm search repo vm/

Step 3: Get the values of the helm file in your local file, and you can edit accordingly.

helm show values vm/victoria-metrics-cluster > values.yaml

Step 4: Test the installation using the below command

helm install victoria-metrics vm/victoria-metrics-cluster -f values.yaml -n NAMESPACE --debug --dry-run

Step 5: Install it using the below command

helm install victoria-metrics vm/victoria-metrics-cluster -f values.yaml -n NAMESPACE

Step 6: Check that the pods are running in the cluster

kubectl get pods -A | grep 'victoria-metrics'

# or list all resources of victoria-metrics

kubectl get all -n NAMESPACE | grep victoria

if your installation is successful, you can see the above resources in your cluster

Installation of Prometheus and Grafana

Step 1: Add the helm repo for prometheus and install it. we are using community helm charts here

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm show values prometheus-community/prometheus > prom-values.yaml
helm install prometheus prometheus-community/prometheus
kubectl expose service prometheus-server --type=NodePort --target-port=9090 --name=prometheus-server-np

Step 2: Integrate Prometheus with Victoria metrics using the below configuration. Add it in /etc/prometheus/prometheus.yml

remote_write:
  url: http://<victoriametrics-address>:8482/api/v1/write

Step 2: Add the Grafana helm chart and install it

helm repo add grafana https://grafana.github.io/helm-charts
helm install grafana grafana/grafana
kubectl expose service grafana --type=NodePort --target-port=3000 --name=grafana-np

Step 3: After installing the grafana helm chart, add the prometheus data source in the grafana ui, For the prometheus URL you should give the victoria metrics url.

Real time case studies

For real time case studies, you can check the list of companies here https://docs.victoriametrics.com/casestudies/

Conclusion

Victoria Metrics streamlines monitoring with robust compatibility and efficient MetricsQL. Its scalability and low resource usage make it a top choice for modern infrastructures. Elevate your monitoring game with Victoria Metrics today.