Cost Optimization
Cloud Cost Optimization for ITOps Teams
Gain clear visibility into multi-cloud spend. Prevent billing surprises and stay on budget. Get cost savings recommendations to cut wasteful spend while maintaining performance.
Why Cost Optimization
Shift from chaos to control over cloud costs
Empower ITOps and CloudOps teams to control costs, improve efficiency, and strengthen both operations and the bottom line.
Stop tool switching
See billing and performance data from major cloud providers in one place for fast answers and smart decisions.
Confidently plan ahead
Track spend trends and forecasting to plan ahead, prevent overruns, and invest savings where they drive value.
Maximize cloud value
Cut wasteful spend and keep high performance with observability data that gets ITOps involved in cost decisions.
Align across teams
Shared visibility unites finance, ITOps, and leadership to foster collaboration and communication.
Insight from day one
Make decisions with unified billing and performance data in one view for immediate clarity and value.
Long-term efficiency
Integrated workflows simplify daily cost management, helping teams manage anomalies, validate recommendations, and stay on budget.
WHAT YOU CAN DO WITH COST OPTIMIZATION
Turn FinOps into an
everyday ITOps practice
everyday ITOps practice
Equip ITOps and CloudOps with the tools to cut costs, streamline workflows, and improve operational stability.
Cost Analysis
Recommendations
AI Workloads
Unified Dashboards
Budget Alerts
Understand Spend in Real Time
Interactive dashboards enable deep analysis of costs. ITOps teams can conduct deep cost analysis so they can isolate cost drivers, diagnose spikes, and make adjustments.
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Explore cost data at the resource level
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Correlate with CPU, memory, and disk utilization
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Group spend by tag, project, or other billing specifications
Cut Costs With Confidence
Intelligent recommendations highlight underused or oversized resources and validate potential savings with live observability data, giving teams confidence to act without disrupting performance.
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Identify ways to save on compute, storage, database, and network resources
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Acknowledge, snooze, or ignore recommendations with added notes for transparency
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Validate changes quickly for AWS, Azure, and GCP resources
Get Predictability Over AI Workload Costs
Maintain cost control over compute resources and utilization changes that power your AI workloads and applications.
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Forecast AI workload cost trends
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Identify underutilized or overprovisioned GPU resources
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Balance performance and budget across high-demand workloads
Connect Cloud Cost and Performance
Unified dashboards combine multi-cloud billing and performance data so teams can see how resource utilization impacts spend in real time.
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View AWS, Azure, and GCP costs in one dashboard
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Filter and group data by account, region, resource type, and more
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Correlate performance metrics with spend trends
Stay Ahead of Budget Surprises
COMING IN EARLY 2026
Budget alerts use forecasted spend to warn teams before costs exceed thresholds. With proactive notifications, ITOps can adjust in real time, maintain financial control, and avoid unplanned overspend.
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Set and track budgets across clouds or teams
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Get notified before hitting forecasted limits
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Adjust resources early to prevent overspend
See how Cost Optimization transforms cloud billing chaos into predictable spend.
GET ANSWERS
FAQs
Get the answers to Cloud Cost Optimization questions.
How is LogicMonitor’s Cost Optimization different from other tools?
LogicMonitor’s Cost Optimization is purpose-built for ITOps and CloudOps teams, not just FinOps or finance. It integrates cloud cost data with real-time performance and utilization telemetry in the same observability platform ops teams already use. This allows engineers to validate cost-saving recommendations against live operational data, treat cost as another observability signal, and act before anomalies turn into budget overruns without switching tools or workflows.
Who is Cost Optimization designed for?
Cost Optimization is designed to bring FinOps principles into the daily workflows of ITOps and CloudOps teams, while providing shared visibility for Finance and leadership. It empowers ops teams to make cost-conscious infrastructure changes with confidence, while enabling collaborative understanding, forecasts, and normalized data.
Which cloud providers are supported?
LogicMonitor supports cost visibility across AWS, Azure, and Google Cloud, with unified dashboards that present multi-cloud spend in a single view. Cost data is standardized using the FinOps Foundation FOCUS format and property normalization for consistent reporting. Cost optimization recommendations for AWS and Azure include compute, storage, database, and networking resources powered by real utilization data.
Support for OCI is planned for 2026.
How quickly can I see value and savings with Cost Optimization?
Teams gain visibility into cloud spend as soon as cloud billing data is connected to the LogicMonitor platform. For customers already using LogicMonitor for cloud monitoring, recommendations populate immediately, leveraging existing performance and utilization telemetry to surface actionable opportunities and begin reducing cloud costs.
Can Cost Optimization help manage AI workload costs?
Yes. Cost Optimization provides visibility into cloud costs associated with AI workloads, including high-cost resources such as GPUs and GenAI token consumption. By correlating billing data with real-time utilization and performance telemetry, teams can clearly understand where AI spend is coming from. Cost optimization recommendations help identify idle, underutilized, or unattached infrastructure supporting AI workloads, enabling teams to control costs.
How does LogicMonitor help teams optimize costs without compromising performance?
Recommendations are grounded in real performance and utilization data collected by the observability platform, not static rules or billing data alone. Each recommendation is supported by metrics such as CPU, memory, throughput, and resource usage trends, giving teams clear context for why it’s suggested. Recommendations are intended to be reviewed and validated before implementation, allowing ITOps and CloudOps teams to move forward with confidence that changes will not negatively impact performance or SLAs.
