Ten years ago, Microsoft Azure launched in Australia. Since then, Azure has evolved from a relatively small set of services to over 300 types of services, now joined by a range of cutting-edge AI services. Azure is now central to how many modern organisations build, scale, and innovate.
Initially, most organisations took a “lift and shift” approach, migrating legacy VMs into Azure data centres. While this was a logical first step, cloud environments have since evolved far beyond basic compute.
As a large-scale Azure Expert Managed Service Provider and Azure licensing provider, Data#3 have visibility to a large amount of Azure environments in Australia. Only a few years ago, VMs, and backups accounted for nearly half of all Azure consumption. Today, that figure has decreased significantly, providing clear evidence that the shift towards Platform as a Service (PaaS) and containerised workloads is well underway.
Today, Azure is rich with capabilities, from advanced data and analytics services, AI services, market leading security, and global-scale networking.
To different organisations and teams within them, Azure can mean different things: for some it is a key business critical application, for others their data and analytics platform, their security platform, their AI platform, or increasingly all of these.
To realise the full potential of AI, data analytics and modern applications, organisations may need to re-evaluate their foundations. By looking at Azure holistically, significant value can be gained by leveraging all the different capabilities of Azure to support these applications.
Legacy environments often stem from organic growth, designed around a single application, with limited foresight to how networking, access, security, and management would eventually scale. These environments can become obstacles to innovation – hindering the efficient deployment of AI workloads or modern applications.
The real challenge now isn’t adopting Azure – it’s optimising, to ensure you are gaining maximum value from it.
Using AI readiness as a strategic lens can help organisations effectively assess and optimise their Azure environments. The key questions to ask when assessing your environment include:
Is your Azure environment manageable, compliant and cost-optimised?
These are not abstract questions. They directly affect your ability to safely and cost-effectively scale new initiatives, particularly AI and data-intensive workloads.
A robust Azure landing zone forms the foundation for any modern deployment. Microsoft offers extensive guidance through its Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF), while Data#3 brings these best practices to life through its own solution accelerator – a set of proven infrastructure as code (IaC) templates used in real customer environments.
A good landing zone:
Strategic planning for scalability is critical. Architecting with future growth in mind ensures long-term agility, optimised performance, and alignment with evolving business needs.
AI is only as useful as the data it can access. That’s why Azure modernisation must also include a clear data strategy.
Many organisations struggle with siloed, inaccessible, or poorly governed data. A strategy to address this issue is to unify data into a centralised data estate where you can leverage common services for warehousing, integration, business intelligence, and governance, as well as providing access to AI and modernised applications. Whilst Azure has many data and analytics services to support this, traditionally this required significant effort and advanced skills to deploy and configure the various services.
A more recent addition to Azure, Microsoft Fabric, provides a unified analytics platform that integrates storage, analytics, integration, and visualisation, and is designed to address the above issue. Built on OneLake, a logical data lake for the entire enterprise, it aims to simplify deployment and management of centralised data services, providing a centralised platform where teams can collaborate and work. It also provides centralised security and governance services so that you can ensure that your data is secured and well-governed.
The aim is to make data accessible when and where it’s required, without sacrificing compliance or control. Fabric is proving to be a streamlined and cost-effective solution for many organisations aiming to create a future-ready analytics environment.
Azure’s global backbone and advanced networking capabilities make it an ideal core for enterprise environments.
However, getting the network architecture right is essential for ensuring secure, efficient, and cost-effective traffic flow – particularly when integrating with on-premises systems or Software-Defined Wide Area Network (SD-WAN) solutions.
The following elements are important to address within the environment:
Increasingly we are seeing a number of trends that are worth considering as part of your network architecture:
Removal of on-premises data centres, making Azure the ‘core’ of the organisations network.
Security remains a top concern, and rightly so. Microsoft’s leadership in areas such as access management, endpoint protection, and security operations is now widely recognised, and Azure provides native support for Zero Trust principles – which includes integrated services for just-in-time access, conditional access, encryption, policy enforcement, network filtering and segmentation, threat protection, and more.
Organisations are encouraged to fully utilise Azure’s built-in security tools (Entra ID, Sentinel, Defender for Cloud, and Azure Policy) with appropriate third-party tools.
With Microsoft’s ability to provide workload protection for servers, containers, databases, DevOps, and more, Defender for cloud can gather telemetry from a wide range of sources inside and outside of Azure to allow you to better identify potential threats and attacks.
For those requiring close alignment with regulatory frameworks, built-in policy sets support standards like ISO 27001, NIST, and the Australian Government’s protected status requirements. Azure Policy provides a rich set of controls to help organisations align with both regulatory frameworks and internal policies, supporting audit and enforcement of these settings.
Effective Azure management services are important for operational success. Azure natively provides a range of services for operations, automation, and cost control. These can be utilised for management of Azure hosted resources, and for organisations operating in hybrid or multi-cloud environments. Azure Arc extends Azure’s management capabilities across on-premises and multi-cloud environments, enabling consistent governance, policy enforcement, and cost optimisation at scale.
It is also important to think about ongoing governance of the environment, assessing potential risks and defining policies for acceptable cloud usage. Once you have defined these, Azure Policy can be helpful to audit or enforce these policies.
Cost remains a key consideration for all cloud strategies. With the right tools and processes, cost blow-outs can be effectively controlled. Microsoft Azure offers robust cost management capabilities – including budgeting and alerting, tagging to support identification of resources and cost allocation, budgeting, right-sizing insights, and pricing reductions through reservations. These controls empower organisations to drive greater transparency, accountability, and efficiency across their environments.
To maximise value, cost governance should be embedded into regular operations, with reviews conducted monthly rather than annually. Integrating cost estimation into the early design phases of projects is particularly important for AI workloads, which can introduce new and complex pricing models.
With foundational infrastructure in place, Azure has become known as the premier platform for developing and deploying AI solutions. At the heart of this innovation is what Microsoft Azure offers in AI services and tooling – a comprehensive, enterprise-grade ecosystem built for scale, speed, and security. AI Foundry brings together more than 1,800 models, DevOps integration, built-in safety assessments, and collaborative tools – all within a unified environment designed to accelerate responsible AI innovation.
A real-world example within Data#3 highlights the impact. A formerly manual process of updating the Azure Periodic Table, once taking up to three weeks, is now automated using Azure AI and Logic Apps, completing the task within a matter of minutes, including the update of products, descriptions, links to Microsoft content, and audio description. This level of operational efficiency demonstrates the transformative potential of AI when integrated into everyday workflows.
Whether you need to:
Data#3 can help at every stage.
To learn more about our Azure strategy, design and management services, visit Azure Solutions Page
or speak with one of our Azure specialists to start your journey towards a more agile, secure and AI-ready environment.
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