The Time for Cost-Intelligent Observability is Now
Organizations are rethinking cloud operations with cost and performance in one view—driving smarter decisions, eliminating surprises, and enabling sustainable growth.
Cost-Intelligent Observability shifts your organization into a proactive and collaborative cloud cost management powerhouse.
Traditional cost-management approaches fall short because teams don’t have shared, real-time visibility into what drives cloud spend.
Bringing cost data into everyday operational workflows empowers teams to spot waste, prevent surprises, and make smarter decisions without slowing innovation.
Aligning finance, engineering, and operations means organizations gain stronger accountability, steady optimization, and a dependable cloud strategy.
Cloud spending has skyrocketed globally, putting increased pressure on IT budgets. Worldwide end-user spend is forecasted to total US $723.4 billion in 2025, up from US $595.7 billion in 2024, according to Gartner. Hybrid and cloud environments have become a mainstay, with Gartner forecasting 90% of organizations will adopt a hybrid cloud approach by 2027. In response, IT leaders across industries are turning to familiar strategies: develop a cloud cost management plan, reevaluate workload placement, hold engineers accountable for spend, adopt a FinOps tool and review process, and reassess their overall cloud strategy. But even with these efforts, the problem persists. According to a Forrester Consulting study commissioned by Boomi, 72% of global companies exceeded their set cloud budgets, despite existing cloud cost reduction efforts. To successfully combat the ongoing rise in cloud costs, a new approach is needed. That means embracing Cost-Intelligent Observability and abandoning the traditional silos between financial cloud management and operational observability.
Why Cloud Optimization Efforts Keep Stalling
Cloud adoption has enabled modernization and innovation. To meet demand and adapt to changes, cloud and IT operations (ITOps) teams work tirelessly to keep cloud-based systems up and running while optimizing performance. As overruns have run rampant and surprise bills have broken budgets, many organizations have shifted the responsibility of cutting cloud costs from finance to their engineering teams, all while expecting them to maintain high levels of performance. Yet giving engineers responsibility over cloud costs hasn’t delivered the results organization were hoping for.
Historically, engineers were disconnected from cost analysis, and it resided with finance. When engineers don’t have visibility into cloud billing, they can’t see the cost implications of their day-to-day work. Did an engineering team forget to decommission the temporary test environment they spun up in the cloud? Did the over-provisioning from the last migration ever get right-sized? Did unattached storage get allocated to a new project? The line items increase, and the consequences caused by the disconnect between financial visibility and operations are pricey.
To minimize the consequences and transfer both visibility and some of the responsibility of cloud cost management to operations teams, the FinOps field and related tools were created with the purpose of combining finance and operations. This specialization enables these efforts, but its implementation affects its impact.
According to the FinOps Foundation State of FinOps 2024 survey, 76% of respondents reported an increased investment to train engineers in FinOps. By investing in training, engineers can contribute to cost control efforts, and these results suggest organizations are counting on their contributions. In the same survey, 82% of respondents reported engineering and operations teams are finding value in FinOps reports.
Organizations deploy FinOps tools to bridge the disconnect and tackle rising costs, yet the data shows these tools haven’t delivered meaningful impact.
A 2023 CloudBolt-commissioned survey found that while 98% of large enterprises have adopted or plan to adopt FinOps practices, only one out of 500 respondents reported having achieved a positive material impact from FinOps to date.
One reason this may be the case is what “visibility” looks like. Seeing the bills or conducting a monthly cost review may give engineers visibility into the numbers, but they are inherently reactive responses. They deliver one-time savings and rarely prevent future surprises. Simply adopting a FinOps tool isn’t the remedy. Nearly half of the engineers and developers in the same survey said they still believe that basic visibility and reporting is lacking. FinOps tools may surface cost insights, but current setups aren’t providing the visibility engineers need at the right time and in the right places. Consequently, giving engineers more tools leads to context switching, infrequent tool use, and ultimately inefficient workflows.
At its core, the challenge isn’t only technological—it’s organizational. Without cross-functional alignment between engineering, finance, and operations, cloud cost accountability will always be fragmented and reactive.
Practices must evolve. Simple up-down monitoring matured into hybrid observability to help teams stay ahead of issues with real-time metrics. Integrating cost metrics is the next evolution, extending that same proactive capability to cloud spend by making it equally observable, actionable, and embedded in daily operations.
The Convergence of Performance and Cost
Engineers need deep, real-time insight into cloud spend to drive meaningful change. That means cloud billing data belongs alongside performance data. Integrating cost into performance dashboards is the efficient solution for ITOps teams to optimize cost and performance. In addition, a collaboration between finance, leadership, and IT Ops teams is the cultural shift needed for successful cloud cost management. Cost-Intelligent Observability means shared ownership of cloud outcomes. The evidence supports that disconnection and silos negatively impact decision-making.
According to the Forrester Consulting study commissioned by Boomi, 67% of respondents agree that an integrated and collaborative approach would improve cloud efficiencies and reduce spend from the planning stage.
Instead of reacting to spend after completing a project, including its associated spend data from the beginning would have the largest long-term impact. Collaboration between teams and transparent data are key ingredients in solving the current struggle of cost optimization.
What Cost-Intelligent Observability Looks Like for ITOps
For ITOps, embedding cost telemetry into the same workflows they already use is the essence of Cost-Intelligent Observability.
When billing and performance data are together, engineers see the real-time costs associated with their decisions and instinctively react. With the ability to visualize this data together, engineers can quickly adjust and validate changes, so reliability and performance stay safe while accounting for the cost. This makes optimization efficient and as natural as managing uptime.
Scenario 1: A test environment quietly driving up spend
A team spins up a temporary test environment that quietly continues running long after the work is complete. With Cost-Intelligent Observability, engineers immediately see that usage has dropped while the cost remains steady. They decommission it to prevent wasted spend and an unnecessary month-end surprise.
Scenario 2: Right-sizing after a migration without risking performance
During a migration, teams over-provision cloud resources to ensure stability, but those oversized instances linger and inflate spend. Cost-Intelligent Observability highlights the high cost and consistently low utilization. Engineers can right-size confidently and validate that performance remains stable, all within the same operational workflows. They’re able to reduce overall spend by optimizing efficiently.
Scenario 3: Rapid detection of an unexpected cost anomaly
A misconfigured scaling rule doubles infrastructure overnight, creating a sudden and unexpected spike in spend. Because the organization’s cost and performance telemetry are correlated, engineers catch the anomaly the moment it occurs. They correct the configuration immediately and watch the cost curves normalize in real time, preventing a costly runaway incident.
How to Put Cost-Intelligent Observability Into Practice
Turning cost into a manageable discipline for engineers requires a framework with an insight-to-action cycle that connects real-time data, action, and outcomes. But it’s not just a technical framework. It requires cross-functional collaboration at every stage, ensuring that finance, engineering, and operations work from the same set of shared insights. Here’s how to put Cost-Intelligent Observability into practice.
Integrate —> Correlate —> Validate —> Forecast (add arrow back to correlate)
Integrate: Bringing cost data into the observability workflow
Start by pulling your cost telemetry into your observability platform. By surfacing billing data within the dashboards and workflows teams already rely on, optimization naturally becomes part of daily operations. Integrating provides the necessary visibility for ITOps and supports cross-team collaboration. This step differentiates from current practices by building visibility into ITOps for ease of use and transparency. Teams can then align on governance practices, goals, success metrics, and review cadence.
Correlate: Connecting cost to performance for impactful insights
With shared data, each team can contribute their expertise to make decisions that align with varied goals. ITOps teams can turn the numbers into actionable insights by diagnosing what is contributing to wasted spend or causing unexpected spikes. A single view for usage metrics and cost bridges the gap between information and insight. Interpreting data together and connecting performance to dollars reveals how decisions impact both uptime and spend, enabling confident action.
Validate: Confirming and measuring impact with real data
Monitor the impact of changes with real-time data. Scale the adjustments that lower cost without affecting performance, and refine anything that doesn’t deliver results. Optimization becomes an ongoing process of continuous refinement—not a one-time or once-a-quarter audit. Collaborative assessments create a feedback loop grounded in shared accountability.
Forecast: Preventing surprises and proactively planning
Check forecasts to ensure decisions lead to the intended downstream outcomes. With forecasting, cost management can become proactive— shifting from chasing cost problems to preventing them altogether. Collaborative forecasting ensures financial plans reflect technical realities and vice versa, allowing teams to anticipate risks together rather than react in isolation. As a result, engineers become partners in financial strategy rather than operators responding to incidents.
What This Means for Your Organization
Adopting Cost-Intelligent Observability creates a systemic shift that enables sustainable cloud optimization across an organization.
This approach replaces short-term fixes and one-off initiatives with a long-term operational strategy that drives efficiency and resilience. It’s a discipline that empowers organizations to continuously optimize operations, reduce unplanned costs, maintain reliability, and adapt to changing demands. When workflows, tools, and roles are designed to align with cost-intelligent observability, daily optimization becomes a natural practice that elevates the overall organization. IT is no longer overhead — it’s an investment with return.
Cultural Shifts Create Transparency, Accountability & Alignment
Organizations adopt a mindset of shared responsibility, promote cross-team knowledge sharing, and make optimization decisions collaboratively. This cultural shift is a model of cross-functional alignment, where goals, metrics, and success criteria are shared. Transparency and openness build organizational trust and foster a collaborative environment where performance, cost, and business outcomes are managed together. As a result, organizations with this cultural foundation become more resilient and can innovate with less risk.
Real-Time Visibility Prevents Surprises and Supports Proactive Action
Continuous monitoring of cost and performance enables teams to identify abnormal patterns, inefficiencies, or runaway spend as they emerge, not weeks later. This means money saved overall, as well as money saved from unexpected events. Forecasts are more reliable and annual spending is predictable. Organizations can confidently plan for future projects and recommit their savings to new priorities.
Leaders gain the clarity they need to steer the organization effectively—turning cloud operations into a predictable, strategic lever that supports long-term growth and innovation. This shift ultimately delivers what leaders value most: control over risk, clarity in investment, and confidence that the business is optimizing resources where they matter most.
The Strategic View Forward
Cost-Intelligent Observability is more than an operational upgrade—it signals a new way for organizations to understand and run their digital environments. As systems grow more dynamic, leaders need clearer insight into how performance, architecture, and cost truly connect.
By elevating observability to a strategic discipline, organizations embrace a more intentional operating model where decisions are guided by shared intelligence and resources are invested with purpose. Ultimately, the bigger picture isn’t just about controlling spend, but giving leaders the clarity and confidence to drive sustainable growth in a constantly evolving landscape.
The future of observability lies in bringing together technical, financial, and cultural intelligence to provide leaders with a holistic, trustworthy view of the business and enable more confident strategic decisions.
Leaders strengthen their ability to connect engineering investments to measurable outcomes, ensuring growth is intentional, sustainable, and aligned with real business impact.
Uncover how LogicMonitor’s Cost Optimization within LM Envision embodies Cost-Intelligent Observability.
Take the first step toward predictable cloud costs, stronger financial control, and faster optimization across your environments.
Teia Jensen is a Product Marketing Specialist at LogicMonitor, where she spends her time turning powerful platform capabilities into clear, compelling stories—basically, helping customers understand not just what the platform does, but why it matters. She started her LogicMonitor journey as a BDR working with enterprise customers before moving into product marketing, with a strong focus on education and enablement. She’s driven by making complex problems and solutions feel approachable, especially across observability, cost optimization, product announcements, and platform packages. Outside of work, she plays padel and is chasing the perfect bandeja.
Disclaimer: The views expressed on this blog are those of the author and do not necessarily reflect the views of LogicMonitor or its affiliates.
