Before the cloud, engineers could only dream about allocating servers without involving anyone on the business side of things. Today, they can spin up a virtual instance in a few minutes without consulting anyone.
No wonder engineers aren’t used to adding costs into the equation, especially when they have other competing priorities.
Building a solid FinOps culture and incentivizing all cloud users to participate in cloud cost management is a key step – and challenge – to cloud cost control.
The monitoring and observability tool Grafana can help you tackle it if you find a way to bring cost data into it (spoiler alert: we found it at CAST AI).
Keep on reading to learn why adding cost insights to Grafana is worth the effort and how to do that.
3 ways to keep your cloud costs in check with Grafana
1. See which workloads are costing you way too much
Dealing with shared costs is the second biggest challenge teams face today. This is especially true in cloud-native environments like Kubernetes.
But a good cost reporting solution paired with Grafana offers a way out.
CAST AI allows you to allocate cloud costs at the level of namespace, label, and workload. You can easily integrate cluster metrics with Grafana to create a handy dashboard that lets you check the cost per workload and link it to a specific team within seconds.
This will save you when workload expenses start spiraling out of control, and you need to remediate the situation as quickly as possible.
Here’s what an example dashboard looks like with CAST AI metrics on it:
2. Get alerts about cost spikes in real time
Nobody has the time to constantly keep an eye on the infrastructure.
But what if a team member leaves a job running for way longer than it should? You might end up with a surprise cloud bill of over $500k as Adobe did. Or burn $72k on testing one thing for just a few hours like the Silicon Valley startup Milkie Way. One alert acting on real-time usage and cost data could have prevented this.
If you integrate real-time cost data into Grafana, you can set usage/cost thresholds and get alerts every time your Kubernetes cluster cost goes above it.
You’ll never be caught by surprise when checking your bill at the end of the month, and your CFO will sleep better at night.
3. Spread cost awareness across your teams
The State of FinOps survey revealed that getting engineers to act on cost optimization recommendations is a top FinOps-related difficulty for almost 40% of respondents – regardless of their maturity level.
By adding cost metrics to Grafana – an industry-standard tool most teams use today – you’re making them easily accessible. Engineers are using Grafana for monitoring and observability anyway. What’s one more dashboard?
That way, you’re not forcing anyone to switch context and work with another tool on top of the dozens they’re already using, just to check how much their cluster costs.
If you’re taking the first steps towards building a FinOps culture at your company, I shared a few tips on how to convince your dev team that cloud cost management is important.
But here’s the best part: bringing cost data to Grafana works like a shortcut.
That’s why we built the capability of moving cost metrics from CAST AI to Grafana via Prometheus.
CAST AI is an autonomous Kubernetes solution that helps to keep cloud costs in check. You can try it out by getting a free Savings Report.