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IBM Turbonomic

Automatic resource optimization: it analyzes demand and capacity in real time and decides where to move, resize and switch off — guaranteed performance and costs that drop, by themselves.

FOCUS · PERFORMANCE AND COST, RECONCILEDNot dashboards saying "you have a problem": actions that solve it — from data center to cloud to Kubernetes
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YoctoIT material for clients and partners · IBM, IBM QRadar, watsonx, Turbonomic e Apptio sono marchi di IBM Corporation.
01 · What it is

IBM Turbonomic, made clear.

The eternal dilemma: over-provision and waste, or save and risk the crash. Turbonomic dissolves it: it continuously analyzes application demand and infrastructure capacity — VMs, Kubernetes containers, public cloud, databases — and generates concrete actions (resize, move, suspend, buy) that guarantee performance at minimum cost. Not another dashboard to watch: decisions that can run automatically.

Real-time
continuous analysis of demand and supply, not monthly reports
Actions
not alerts: what to do, how much, where — executable
Full-stack
data center, cloud, Kubernetes and databases in one model
IBM Turbonomic
OFFICIAL BRANDING IBM
02 · How to use it well

The things that make the difference.

The decision engine

Application demandSLA, load, seasonality
Continuous analysis
Demand/supply model
Actions
resize · move · suspend · buy
Turbonomicthe automatic optimizer
Executionmanual, approved or full automation
Guaranteed performance at minimum cost

Actions, not alarms

The difference from classic monitoring: Turbonomic doesn't say there's a problem, it says how to fix it — and can do it itself.

The cloud that doesn't waste

Continuous instance rightsizing, idle shutdown, right-tier choice: the cloud bill comes back under control.

Kubernetes that breathes

Requests and limits optimized on real pods: no more OOM, no more half-empty nodes.

Gradual automation

Start with suggested actions and human approval, reach full automation where you trust it: you decide the control.

03 · In depth

The demand-supply model: how it decides

Turbonomic builds an economic model of the environment: each entity (VM, container, host, volume, database) is a buyer/seller of resources (CPU, memory, storage, IOPS); continuous analysis prices them by congestion and finds the allocation keeping every application within its SLAs at minimum cost; the resulting actions — resize, move, suspend, provision — integrate with vCenter, the clouds, Kubernetes and ticketing; with Instana upstream, decisions start from real application metrics, not infrastructure averages.

  • Economic model — resources as a market: optimal allocation emerges from prices
  • Continuous rightsizing — VMs and containers sized on the real load, always
  • Cloud cost control — idle off, right tier, correct instances: -30% typical
  • Kubernetes-native — optimized requests/limits, better scheduling
  • Instana integration — decisions start from real application metrics
  • Automation of choice — suggested, approved or automatic: control is yours
04 · Numbers and lifecycle

The numbers that matter.

-30%
the typical cut in cloud/infrastructure costs
SLA
performance guaranteed, not sacrificed to savings
K8s
native container optimization
auto
from suggested action to full automation
Buying capacity "just in case" is the data center's biggest hidden cost: Turbonomic calibrates it itself — guaranteed performance, waste eliminated.
05 · Use cases

Where it really pays off.

Cloud cost control

The bill drops without performance risk.

Data center consolidation

More load on the same iron, safely.

Kubernetes FinOps

Containers sized on the real, not by guess.

How much are you paying for capacity you don't use? An assessment with Turbonomic tells you in numbers.