For most Australian organisations, cloud remains a core part of their IT strategy. The value of public cloud in driving speed, innovation and access to advanced services is well understood, and it continues to play a critical role in modern application and data platforms.
What is changing is not confidence in cloud itself, but how organisations think about where different workloads should run over time. As environments mature, IT leaders are becoming more deliberate about workload placement, governance and commercial alignment. Rather than defaulting to a single platform, many are designing hybrid models that combine cloud services with on-premises infrastructure for specific reasons.
This shift is not about moving away from cloud, it’s about using cloud more intentionally and ensuring that cost, control and operational requirements remain aligned as environments grow. Azure Local exists to support this more deliberate hybrid approach.
Azure Local brings Azure services and management directly into the data centre, enabling organisations to run cloud-native workloads locally while maintaining consistency with public Azure.
Through Azure Arc, Azure Local provides a unified operational experience across cloud and on-premises environments. Teams use the same tools, policies and governance models, regardless of where workloads run. This is particularly valuable for organisations that require:
Azure Local is not a fallback for workloads that cannot go to cloud. It is a way to extend Azure where workloads make the most sense without fragmenting tooling, skills or governance.
While Azure Local delivers the cloud operating model, it still requires enterprise-grade infrastructure underneath. This is where HPE GreenLake becomes a natural complement.
GreenLake allows organisations to consume on-premises infrastructure through a cloud-like commercial model. Capacity can be deployed in small increments and scaled over time, aligning infrastructure investment with actual demand rather than fixed forecasts.
Together, Azure Local and GreenLake support a hybrid architecture where:
This combination delivers a consistent operating and commercial experience across cloud and on-premises environments, which is increasingly important for organisations running mixed workloads over long time horizons.
The most important shift reflected in this conversation is that hybrid is now perceived as an intentional end state.
Some workloads benefit from the elasticity and global reach of public cloud, while others require proximity, deterministic performance or specific compliance controls. Azure Local allows those workloads to stay local while still benefiting from Azure innovation, and GreenLake ensures the infrastructure supporting them remains flexible and commercially aligned.
This avoids two extremes that organisations are increasingly wanting to move away from:
When designed intentionally, a hybrid approach delivers flexibility, cost control, scalability, strengthened security and compliance, and the speed to innovate.
Decisions on where workloads run and how they are funded now sit firmly at the intersection of IT and finance. Platform choices affect cash flow, depreciation, operational risk and long-term flexibility, and should be viewed through a governance and planning lens that requires alignment across teams.
Data#3’s role is to help organisations structure these conversations and bring together cloud architecture, on-premises design and commercial models into a single, coherent strategy.
If your organisation is modernising its data centre or refining its cloud strategy, the question is no longer whether to use cloud or on-premises infrastructure. It is how to combine them deliberately and sustainably.
Data#3’s Data Centre Assessment helps organisations evaluate where workloads should run, how they should be funded, and how platforms like Azure Local and GreenLake fit into a long-term hybrid strategy.
For a deeper dive into data centre modernisation, be sure to explore our three-part series: start with “Rethinking infrastructure investment: how flexible financial models can unlock stalled refresh projects” to understand how to get movement back into stalled initiatives, then read “When cloud economics stop adding up: the cost curve of AI testing vs production” to see why scaling AI workloads on cloud can strain budgets, and finish with “The smarter, more cost-effective path to modern virtualisation” for practical insights on evolving your virtualisation strategy in a cost-conscious way.
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