You're (probably) wrong about IBM Turbonomic

By Jeremy Hazlett posted 5 days ago

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Think IBM Turbonomic is just a FinOps tool? Think again. It’s not just about cost savings - it’s about intelligent automation, ensuring your applications never starve for resources or waste them needlessly.

Over the past year, I’ve had too many people refer to IBM Turbonomic as a FinOps tool: “It’s a tool that helps optimize cloud spending by rightsizing workloads and cutting costs.” While it can do that, stopping there would be like calling a supercomputer a “pretty good calculator.”

The reality is maybe a bit more daunting and difficult to describe, but in a nutshell, Turbonomic manages resources across the entire application stack, optimizing performance, cost, and compliance across hybrid and multi-cloud environments.

Beyond Cost Savings: Performance at Scale

IBM Turbonomic is about ensuring applications always have the resources they need, when they need them. It continuously analyzes demand and makes intelligent, automated resourcing decisions to prevent performance issues before they happen.

Self-Managing Infrastructure: Turbonomic can automatically scale VMs, storage volumes, containers, and databases across hybrid environments based on real-time demand, without over-provisioning. This can be scheduled to prescribe to maintenance windows, or integrate with pipeline and deployment tools for IaC managed environments.
SLO-Driven Optimization: Instead of just looking at cost, balance performance, availability, and compliance needs to deliver optimal outcomes. Make sure you meet your Service Level Objectives (SLOs) without overcommitting and understand where you need to invest in order to keep your application’s users happy.
End-to-End Visibility: Connect your infrastructure to application performance, from Kubernetes clusters to legacy virtual machines, ensuring smooth operations across environments.

The Misconception of "Just a Cloud Savings Tool"

Yes, Turbonomic can optimize your cloud spend, but that’s a byproduct of its real mission: ensuring applications perform with the minimum necessary resources. If resources were free, application performance would be a solved problem – just over-provision. Turbonomic is the analysis engine that helps shrink that gap between being overly wasteful and the peace of mind that you have the capacity to deal with spikes in utilization.

Go beyond FinOps:

Data Center Optimization: Ensure your private cloud (VMware Hyper-V, Nutanix, and Red Hat OpenShift Virtualization) environments aren’t over-provisioned, reducing hardware costs and extending infrastructure life. Consolidate licensing, whether at the hypervisor level, or for applications that require entire hosts to be licensed.
Kubernetes Workload Scaling and Scheduling: Dynamically move and adjust pod sizes and add and remove nodes to optimize containerized environments, preventing wasted resources without performance risk. The native scheduler will not relocate pods when capacity is free, potentially leaving barely utilized nodes provisioned and costing you money unnecessarily.
Automation: Don’t just generate reports – that’s a waste of time. Proactively move, scale, and tune workloads to prevent congestion and resource contention.
GPU optimization: Optimize GPU utilization and performance for GPU-dependent workloads such as ML and Gen AI LLM Inference workloads.
Sustainability: Need to meet environmental goals by reducing energy consumption and the carbon footprint of IT infrastructure.

The Future of Intelligent Automation

Let’s be real. SREs, DevOps, SysAdmins, and Application teams don’t have the time or resources to babysit every VM, container, and database. This is where Turbonomic steps in. If you think Turbonomic is just another FinOps tool, you’re doing it wrong. It’s not just about cost savings. It’s about delivering autonomous, intelligent workload optimization across your entire IT stack. Let’s make it a bit more personal:

E-commerce: prevent resource shortages during those Memorial Day, 4th of July, or Black Friday sales.
AI/ML workloads: Ensure your GPUs are optimized for your GenAI models.
Finance & banking: Keep your mission critical applications performant without wasteful over-provisioning.

Balancing all factors (performance, efficiency, and compliance) in applications is paramount for organizations, and we’ve taken technology to a point that solving this is well beyond human scale. Let’s automate this.