Engineering teams are staring down the barrel of a massive cloud cost crisis. If you're not managing your Azure expenses, you're not managing your business.
The foundation of cloud cost management starts with resource tagging – the key to allocating costs to teams, products, and environments. You need five tags on every resource: team, project, environment, cost centre, and creation date. Azure Policy with DeployIfNotExists effect takes care of automatic tagging at resource creation, while deny policies block resources without required tags. And Azure Cost Management tag filters give you per-team reporting.
Let me tell you, it's not just about slapping on some tags and calling it a day. We had a production database that was eating through costs because it was running on a Standard SKU. But with Azure Advisor's cost recommendations, we were able to identify the opportunity to downsize to a lower-priority SKU, which saved us around 30% on the monthly bill. And then, of course, there's the matter of Reserved Instances and Savings Plans. We implemented Azure Savings Plans for our development environment, which gave us a 40% discount on our compute costs. The key is to have a clear understanding of your usage patterns and adjust your commitments accordingly.
Right-sizing is a workflow that's essential for any cloud migration. Azure Advisor's cost recommendations pinpoint over-provisioned VMs, idle resources, and Reserved Instance opportunities. Our right-sizing workflow involves monthly Advisor reviews, automated reports to team leads, and scheduling sizing changes during low-traffic windows. Before-and-after comparisons of cost and performance metrics reveal a typical 20-30% cost reduction for mature workloads.
Reserved Instances and Savings Plans are two sides of the same coin. They offer 40-70% discounts for known-stable workloads like production AKS node pools and production databases. Azure Savings Plans provide flexible compute commitments that apply to any VM usage, regardless of SKU or region. The discipline is to right-size before committing to reservations, review utilisation reports monthly, and convert on-demand spend to reservations as workloads stabilise.
We've also set up Azure Cost Management to alert us when actual or forecasted spend exceeds configured thresholds. This way, we can catch cost overruns early and adjust our budgets accordingly. And with cost anomaly detection, we can identify unexpected spend spikes before they snowball. It's not just about avoiding budget blowouts; it's about making data-driven decisions that drive business value.
Budget alerts scream when actual or forecasted spend exceeds configured thresholds. We're talking weekly cost reviews by team, monthly budget variance reports, and engineering-owned dashboards that track per-service spend trends. And with cost anomaly detection, you can identify unexpected spend spikes before they snowball.