AI Agent Observability with IBM Instana
May 12, 2026
How enterprise IT teams are breaking down silos, reducing waste, and gaining control of hybrid infrastructure costs
Download the expanded whitepaper below:
Modern infrastructure is no longer confined to a single environment.
Applications that once ran on dedicated servers or centralized data centers now operate across a complex ecosystem of public cloud platforms, Kubernetes clusters, virtual machines, containers, and legacy on-premises systems. Most organizations manage workloads across multiple providers, internal infrastructure, and rapidly scaling architectures.
93% of organizations now operate a multicloud strategy, with global spending on public cloud services continuing to accelerate year over year.
What began as a way to increase flexibility and innovation has evolved into a new operational challenge: managing a rapidly expanding and fragmented infrastructure environment.
Engineering teams can provision resources instantly using infrastructure-as-code. Kubernetes clusters dynamically scale workloads across nodes and regions. Cloud providers offer a near-limitless array of services and pricing models.
This flexibility enables speed—but breaks traditional models of financial oversight.
Unlike traditional IT procurement, cloud introduces:
Organizations today face three simultaneous challenges:
Cloud adoption has increased demand for compute, storage, and networking. AI, analytics, and distributed applications are driving costs upward across industries.
Applications now span microservices, containers, APIs, and hybrid environments. Monitoring tools operate in silos, forcing teams to manually correlate metrics, logs, and traces.
Up to 30% of cloud spending is wasted due to overprovisioning, idle workloads, and lack of visibility.
The consequences extend beyond infrastructure budgets.
Understanding where IT spend originates and how workloads consume resources has become critical.
What organizations need is not more infrastructure—
but greater intelligence about how that infrastructure is used.
Traditional monitoring tools were built for static environments. Modern infrastructure is dynamic, distributed, and constantly evolving.
Applications are no longer monolithic—they are composed of microservices and containerized workloads that can scale automatically.
A single user transaction may traverse dozens of services across multiple environments.
Legacy tools:
This creates a reactive operating model where engineers spend time responding to issues instead of preventing them.
Observability provides real-time visibility into infrastructure and applications by collecting:
This allows teams to:
Automation enables organizations to respond dynamically:
Together, automation and observability represent a fundamental shift:
From reactive infrastructure management → to continuous optimization
As hybrid environments evolve, a new ecosystem of tools has emerged. These tools address different layers of infrastructure management.
These platforms address financial opacity by connecting infrastructure consumption to business outcomes.
They enable organizations to:
This forms the foundation of Technology Business Management (TBM).
These tools provide granular visibility into how applications consume infrastructure.
In Kubernetes environments, they:
These platforms ensure resources are used efficiently by:
They align infrastructure supply with application demand.
These tools provide visibility into distributed systems by:
They are essential for maintaining reliability in complex environments.
Each category represents a different perspective:
Together, they form the operational intelligence layer of modern infrastructure.
Organizations rarely deploy these capabilities in isolation. Instead, they operate as a layered system.
Provides:
Provides:
Provides:
Provides:
While these tools provide valuable insights, they often operate in silos.
This becomes a major issue in hybrid environments.
Most FinOps tools were designed for cloud:
Enterprise infrastructure includes:
These lack:
Visual One Intelligence addresses this gap by unifying financial and operational data across environments.
Converts on-prem costs (hardware, power, labor) into normalized daily costs comparable to cloud spend.
Resolves inconsistent tags into consistent business dimensions without requiring perfect tagging.
Provides a unified view across cloud, virtualization, and physical infrastructure.
These capabilities enable organizations to:
Effective FinOps adoption starts with evaluating key capabilities.
Do you have:
Without this, performance issues become difficult to diagnose.
Are resources:
Optimization platforms help align supply with demand.
Can you:
This is critical in containerized environments.
Can you:
This is where TBM platforms play a key role.
Traditional FinOps was built for cloud environments.
But enterprise infrastructure is hybrid.
Without a unified model:
Hybrid FinOps normalizes infrastructure economics across environments by:
Organizations move from:
To:
A unified model where performance, efficiency, and cost are managed together
Hybrid infrastructure is not becoming simpler—it is becoming more distributed, dynamic, and financially complex.
The organizations that succeed will not be those with the most infrastructure,
but those with the clearest understanding of how it operates and what it costs.
