How intelligent observability and FinOps fuel cloud cost optimisation

As costs to run cloud services continue to escalate amid a push to modernise and adopt AI-driven workloads, organisations need to prioritise getting on top of the expenses as a key priority. Gartner expects Australian organisations to spend nearly A$26.6 billion on public cloud services in 2025, an increase of 18.9% from 2024.

With 90% of Australian organisations using multiple public clouds, businesses must navigate the complexities of managing diverse cloud platforms, security frameworks, and billing models. 

Organisations shifting their focus to measure outcomes of engineering decisions must enhance cloud cost forecasting, make informed investment decisions based on data and align cloud spending with strategic business objectives.

Gain insight into cloud spend 

Getting visibility into cloud costs is key to establishing effective cost controls. Setting up a FinOps practice allows organisations to optimise the business benefits of cloud by fostering financial accountability and collaboration. 

Intelligent observability platforms empower FinOps teams to collect, analyse, and act on cloud cost data in real time. Built around FinOps best practices, these platforms promote collaboration across teams, enhance cost visibility, and drive financial accountability, all of which promote strategic cloud investment decisions.

Organisations that adopt intelligent observability effectively shift from reactive cost-cutting to proactive optimisation, enabling accurate forecasting and efficient cloud spending.

AI-driven FinOps

The future of FinOps will be heavily influenced by advancements in AI and intelligent automation. Integrated platforms will increasingly optimise cloud resource allocation by adapting in real time to shifting usage patterns and evolving business demands. AI will enhance forecasting and decision-making through predictive analytics and conversational interfaces, uncovering more accurate cost projections and savings opportunities.

Powered by AI, FinOps will give engineering teams the clarity to weigh the value of services against their cost, leading to smarter decisions around tooling, optimisation, and consolidation. Ultimately, intelligence-led cloud cost management paves the way for balancing performance with spend, enabling tighter financial control over cloud infrastructure without sacrificing efficiency.

As cloud cost environments become increasingly complex to manage, real-time data and intelligence are a game-changer for technical and FinOps teams to optimise resources, reduce unnecessary spend, and maintain strong performance. Paired with continuous monitoring and fine-tuning, intelligent observability not only improves application performance and reliability but also leads to streamlined and cost-effective cloud infrastructure.

Improve visibility to get ahead of costs

Many organisations struggle with real-time visibility into their cloud usage. Distributed teams often work in isolation, provisioning resources as needed without a shared understanding of the financial impact. The constantly shifting nature of the cloud makes it even more challenging to control sprawl, pinpoint cost drivers, and spot anomalies.

The lack of visibility across IT ecosystems and data pipelines leads to overspending or spending in the wrong areas, waste, and a lack of predictability in future costs. Without observability, cloud spending decisions are reactive, with the organisation exceeding its budget, receiving a bill, and then scrambling to find quick wins to reduce cloud spend.

To help identify inefficiencies and drive down cloud spend, companies should empower engineers to identify and address performance issues earlier in the process by using modern, AI-strengthened observability tools to estimate cost impacts of different services. By applying intelligent observability data from applications and infrastructure in production, organisations can take a more fine-grained approach to optimising spend while monitoring for performance impacts. It also enables organisations to effectively shift from reactive to proactive value-driven decision-making. 

While cost-cutting remains a priority, engineering teams often grapple with the challenge of maximising the value of delivered services. Observability addresses this by aligning service delivery KPIs, costs, and business value so teams maintain focus on optimising performance.