Enterprise organizations running SAP workloads on hyperscaler infrastructure — AWS, Microsoft Azure, Google Cloud Platform, or STACKIT — consistently overspend on cloud resources. The causes are predictable: compute instances provisioned for peak capacity running at low average utilization, storage tiers mismatched to actual data access patterns, unmonitored resources accumulating charges, and licensing arrangements that made sense at migration time but are no longer optimal.
Novarto’s Hyperscaler Cost Optimization service identifies and eliminates this waste — with no upfront investment required. Our fees are structured as a portion of the savings we deliver, which means we have a direct commercial incentive to find every saving available in your environment. If we don’t reduce your costs, we dont get paid.
Clients typically achieve measurable cost reductions within 3 months, following a structured four-phase methodology beginning with a Discovery Workshop and progressing through agile two-week implementation sprints with savings tracked from each cycle.
Partner with us to achieve tangible cost savings and operational efficiency. You will gain:
- Full analysis of your current virtual machine footprint, CPU utilization, and overall resource reservations.
- Expert recommendations tailored to your specific environment, directly leading to significant cost reductions for your business.
- The ability to leverage the right pricing models for each of your unique workloads, ensuring you pay only for the resources your business demands.
- No upfront investment from your side – our fees are directly tied to a portion of the savings we achieve on your hyperscaler costs.
- Access to BEST practices in cloud cost optimization, gleaned from our experience across diverse industries.
We understand the urgency of optimizing your cloud spend. Our industrialized and agile implementation methodology allows us to address your business needs and deliver measurable results typically within 3 months.
The Novarto Optimization Methodology: Four Phases to Measurable Savings
Our proven methodology ensures a transparent, low-risk, and fast path to realizing significant cost savings in your hyperscaler environment. We begin with a collaborative Discovery Workshop to thoroughly understand your current setup and address key implementation questions.
Our approach is built on a Pre-built Foundation and follows a structured Methodology Track:
- Template-based and in sync with former projects: Leveraging our experience and proven frameworks for efficient execution.
- Agile execution to support transparency: Providing clear visibility and iterative progress throughout the optimization process.
- Low risk and fixed price (for the initial phases): Offering predictable costs and minimizing financial uncertainty.
- Fast time to value: Delivering tangible savings and optimizations quickly.
The Methodology in a Nutshell:
- INITIATE: We clearly explain our solution offering and the detailed methodology we will employ.
- DISCOVER: We seamlessly set up necessary monitoring agents and securely gather relevant contract and console information.
- DELIVER: We work in agile two-week sprints, implementing continuous rightsizing recommendations with savings measured two sprints post-implementation.
- CONTINUOUS RUN: We provide a smooth handover to your team or establish ongoing continuous improvement and operational support for sustained optimization.
The first step is a Discovery Call: a structured two-hour session in which we will assess your current cloud environment and begin to identify potential savings. No commitment is required beyond this stage. [Book a Discovery Call →]
FAQ Section:
1. What is hyperscaler cost optimization, and why do SAP environments overspend on cloud?
Hyperscaler cost optimization is the process of systematically analyzing and restructuring cloud infrastructure usage to eliminate unnecessary spend while maintaining or improving system performance. For SAP environments specifically, cloud overspend typically originates at the point of migration — when systems are provisioned based on peak-load estimates or on-premise hardware specifications that do not reflect actual cloud utilization patterns.
The most common sources of SAP hyperscaler overspend are over-provisioned virtual machines running at a fraction of their allocated CPU and memory capacity, storage configurations using high-performance tiers for data that is rarely accessed, SAP license arrangements that are not optimized for the cloud deployment model, and monitoring gaps that allow idle or forgotten resources to continue generating charges. A structured cost optimization engagement identifies and addresses all of these categories systematically, rather than targeting isolated savings opportunities.
2. Which hyperscaler platforms does Novarto optimize?
Novarto’s cost optimization methodology applies to SAP and enterprise workloads running on the major hyperscaler platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Novarto also works with STACKIT, a sovereign European cloud platform, for organizations with EU data residency requirements.
The optimization approach is platform-aware — each hyperscaler has different pricing models, reserved instance structures, storage tier options, and licensing arrangements, and recommendations are tailored to the specific platform and the workloads running on it. For organizations running SAP workloads across multiple cloud platforms simultaneously, Novarto can conduct a multi-platform assessment to identify savings opportunities across the entire cloud environment.
3. How quickly can we expect to see measurable cloud cost savings?
Novartos methodology is designed to deliver measurable results within 3 months of engagement start. The first phase — INITIATE and DISCOVER — typically takes two to four weeks, covering the Discovery Workshop, monitoring agent setup, and baseline analysis. The DELIVER phase then proceeds in agile two-week sprints, with savings measured two sprints after each implementation to give changes time to fully take effect in billing cycles.
The speed of savings realization depends on the size and complexity of the environment and the volume of optimization opportunities identified during the discovery phase. Environments with significant over-provisioning or large volumes of idle resources typically see the fastest initial savings. Longer-term savings from reserved instance restructuring or licensing optimization take longer to realize but often represent the largest total reduction.
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