How to Control and Optimize Azure Costs Without Losing Visibility

This is the ninth post in our Azure Monitoring series, and it’s all about taking control of your cloud costs without losing visibility. We’ll unpack why Azure bills tend to spiral, where native tools fall short, and what it really takes to cut spend while keeping performance on point. You’ll walk away with practical ways to spot waste early, act fast, and stay ahead of surprise invoices. Missed the earlier posts? You can catch up anytime.
Cloud costs have a way of creeping up, often without warning. In fact, 69% of organizations exceeded their cloud budgets in 2023. One month, spending looks predictable. The next, an unexpected charge appears, unused resources running 24/7, misconfigured instances scaling up unnecessarily, or storage costs ballooning due to poor tiering decisions. These issues make it harder for teams to invest in innovation.
For many organizations, the challenge is reducing cloud costs without losing visibility into performance and security. Cutting the wrong resources or limiting monitoring to save money can create blind spots that lead to downtime, performance bottlenecks, and security risks.
With Cost Optimization in LogicMonitor Envision, teams don’t have to choose between cost control and operational insight. Instead of reactive cost-cutting, LogicMonitor provides real-time intelligence, automated optimization, and proactive anomaly detection to reduce spending without sacrificing visibility.
Azure cost tools aren’t built to save you money. LogicMonitor is.
Azure’s cost tools aren’t built to help you spend less. They’re built to help you use more, which makes it tough to spot waste before it turns into a surprise bill. | Trying to save money by cutting monitoring? That move will bite you later. It creates blind spots, breaks stuff, and leads to more work for your team. |
LM Cost Optimization shows you what’s costing too much and what’s safe to scale back. You get real-time cost data, smart recommendations, and full performance context, all in one view. | The goal isn’t just savings—it’s sanity. With LM Cost Optimization, you can stop firefighting cloud spend and start making confident, data-backed decisions. |
Azure includes native tools, like Cost Management and Advisor, to track spending, but they’re not designed for proper cost optimization. Azure’s goal isn’t to help you spend less. It’s to help you use more. And that works until it doesn’t.
That’s where the cracks start to show because tracking spend isn’t the same as optimizing it.
And while Azure offers some cost management features, they’re reactive by design. Think: budget alerts that show up after you’ve already crossed the line. Or generic recommendations that ignore your team’s unique workloads and dependencies.
When budgets tighten, the first instinct is often to reduce monitoring or scale down resources based on averages. But that creates blind spots that hurt you in the long run:
And here’s the kicker: the more custom SOPs you create to work around Azure’s limitations, the more complex (and expensive) your operations become. What started as “saving a few bucks” turns into tech debt that drags you down.
The whole point of operations is normalization. Not more duct tape.
With LM Cost Optimization, teams get real-time tracking, automated savings recommendations, and intelligent alerting that optimize costs without introducing risk.
LM Cost Optimization provides immediate visibility into cloud spending, breaking down costs by team, application, environment, and custom tags. This helps organizations pinpoint exactly where money is being spent and where it’s being wasted.
Unlike Azure’s delayed cost data, LM Cost Optimization tracks spending in real time, allowing teams to:
Instead of forcing engineers to dig through cost reports, LM Cost Optimization provides actionable recommendations that balance cost and performance.
These recommendations incorporate performance data to ensure optimizations don’t introduce risk.
LM Cost Optimization eliminates the artificial divide between cost and performance monitoring. Instead of managing them separately, teams get a unified view that reveals:
This end-to-end visibility allows teams to optimize spending without compromising availability, security, or user experience.
For organizations running workloads in Azure, AWS, or hybrid environments, LM Cost Optimization provides cross-cloud cost comparisons to identify:
This big-picture view prevents cost-cutting decisions that merely shift expenses elsewhere, rather than addressing the root problem.
Azure’s tools will always have a bias: they’re designed to help you buy more Azure. LogicMonitor doesn’t have that bias. We’re here to help you:
Cloud cost control doesn’t have to mean giving up visibility. With LM, you get both.
The next blog in our Azure Monitoring series will focus on the critical role of events, logs, and traces in achieving true observability. We’ll show you why metrics alone tell an incomplete story, how logs provide crucial troubleshooting context, and why distributed tracing has become essential for complex cloud environments. You’ll learn practical ways to integrate all three observability pillars to dramatically improve how you detect, diagnose, and resolve issues across your Azure infrastructure.
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