Working with Prometheus and Grafana Using Helm

Varun Saharawat12 Jan, 2026

Working with Prometheus and Grafana via Helm provides a streamlined way to manage monitoring and observability within a Kubernetes cluster. By utilizing Helm charts, you can automate the deployment of these complex tools, ensuring that your metric collection and data visualization are consistent, scalable, and easily reproducible across different environments.

Why Modern Teams Use Helm for Working with Prometheus

Deploying monitoring stacks manually is often a tedious and error-prone process. When working with Prometheus, you deal with multiple components like the server, Alertmanager, and various exporters. Helm simplifies this by packaging all these resources into a single unit. Instead of writing dozens of YAML files, you use a pre-built chart. This approach is a vital part of maintaining a clean Kubernetes architecture. Many developers ask questions like "is susan williams working with prometheus" or "is evelyn working with prometheus" when looking for community-led configurations or specific contributor branches. In the DevOps community, people often wonder "why is artemis working with prometheus" in the context of specific open-source projects or internal team assignments. Regardless of who is managing the stack, the goal remains the same: efficient data scraping and alerting. Using Helm ensures that whether it's Susan, Evelyn, or Artemis at the helm, the configuration stays standardized.

Detailed Steps for Working with Prometheus and Grafana

First, you need to add the official Helm repositories to get started. To get the most recent charts, run helm repo add prometheus-community. You can install the stack with a simple install command after you update your local repo. This sets up the Prometheus server, which gathers metrics, and the node-exporter, which gets info on the hardware on your Kubernetes nodes. You will need to use the web interface after the pods are up and running. By default, Prometheus services are internal, therefore you'll need to employ port forwarding to see the dashboard on your own computer. This lets you perform PromQL queries right away. It's a quick way to check that your scrapers are working well. You don't want to wait until something goes wrong in production to find out that your metrics are missing.

Also Read:

What Is Devops? Simple Explanation 2026 [Updated]

DevOps Career Path

DevOps And Its Working

Why DevOps? Understanding The Shift From Traditional SDLC To Modern Software Delivery 2026 [Updated]

History Of DevOps: How It Is Today With DevOps? 2026 [Updated]

DevOps Goals: What It Aims To Achieve In Modern Software Development 2026 [Updated]

DevOps Learning - A Comprehensive Guide 2026 [Updated]

DevOps Roadmap: How To Become A DevOps Engineer? 2026 [Updated]

DevOps Engineer Job Description Skills, Roles And Responsibilities 2026 [Updated]

DevOps Vs Software Engineer: Roles, Skills, And What Sets Them Apart 2026 [Updated]

Configuring Grafana for Advanced Dashboards

While Prometheus is great for data storage, Grafana is where the visual magic happens. After installing the Prometheus-stack via Helm, Grafana is usually included automatically. You just need to retrieve the admin password, which is stored in a Kubernetes secret. We recommend changing this password immediately after your first login to ensure your monitoring data stays secure and private.

Adding Prometheus as a Data Source

Inside the Grafana UI, you must link it to your Prometheus service. You'll enter the internal service URL, usually http://prometheus-server.monitoring.svc.cluster.local. Once connected, you can import pre-made dashboards from the Grafana library. These dashboards provide instant visibility into CPU usage, memory consumption, and network traffic across your entire cluster without requiring you to build charts from scratch.

Setting Up Persistent Storage

By default, some Helm charts might use emptyDir for storage, which means you lose data if a pod restarts. You'll want to configure a Persistent Volume Claim (PVC). This ensures your historical monitoring data survives pod crashes or scheduled upgrades. Adjusting the values.yaml file in your Helm chart allows you to specify the storage size and class, making your monitoring stack resilient and production-ready.

Enhancing Your Monitoring Stack Strategy

The most important thing is to standardize your deployment. If Susan is working with Prometheus or another team member, having a values.yaml file in a Git repository lets you handle things in a "GitOps" way. This implies that every modification you make to your monitoring configuration is logged and checked by other people. It stops configuration drift and makes it much easier to get back on track after accidentally deleting anything or making a mistake in the setup.

Fixing problems with Helm-based Prometheus Deployments

Pods can sometimes get stuck in a "Pending" state. This frequently happens because there aren't enough resources or there are problems with storage binding. Check how much space your node has. Depending on how many metrics you scrape, Prometheus can use a lot of memory. Use kubectl to describe pods to find out what's wrong if the pods aren't beginning. In many cases, all you need to do is raise the RAM restrictions in your Helm settings.

Keeping an eye on the monitor

It may seem like a waste of time, but you need to keep an eye on Prometheus itself. You can't see anything on your machine if the Prometheus server goes down. Many helm charts come with "self-monitoring" tools. If the scraper is slow or the disk is almost full, these notifications will let you know. A Senior DevOps Engineer's daily job includes staying on top of these problems.

Making Scrape Intervals Your Own

Not every app needs to be scraped every five seconds. You can set the scrape interval to 30 or 60 seconds for programs that aren't really important. This makes your Prometheus server work less and saves space on your hard drive. You can easily change these settings for all jobs or just one job in the Helm chart values. This makes for a very personalized monitoring environment.

FAQs

Is it better to work with Prometheus using Helm than by hand with YAML?

Yes, it's a lot better. Helm handles dependencies, versions, and complicated configurations all in one package. This makes deployments repeatable and lowers the chance of making mistakes when setting them up.

Why do a lot of cloud-native systems use both artemis and prometheus?

"Artemis" is a term that typically refers to certain project responsibilities or internal toolsets that are meant to make Prometheus better. In a broader sense, these tools work together to keep your monitoring data safe and available for a long time.

Is Susan working with Prometheus to meet certain dashboarding needs?

If you mean Susan Williams or other community specialists, a lot of professionals help make Grafana dashboard layouts. You can see Prometheus data right away with these templates, without having to write complicated queries yourself.

How do I use Helm to change my Prometheus settings?

You don't have to get rid of everything. Just change your values.yaml file and run helm upgrade. This just applies the changes you made, so your monitoring services will be as little affected as possible when you change settings or versions.

What should I do if my Prometheus pod keeps crashing?

First, look at the logs. "Out of Memory" (OOM) faults or broken storage segments are the main causes of most crashes. Make sure your Helm chart has enough RAM and that your persistent disks are mounted and written the right way.