Cloud provides extensive opportunities to optimise costs so businesses can dedicate scarce resources to innovation and digital transformation. Here are ten strategies businesses can employ to control costs. \nBusinesses today must adapt to a global reality of disrupted supply chains, economic and political volatility, and populations whose expectations of work and shopping are considerably different to those they had pre-pandemic. These circumstances are placing technology and finance leaders under more pressure than ever to minimise waste and maximise the value of every dollar dedicated to IT.\u00a0\nThis means investing in digital transformation and cloud strategy, rather than \u2018keeping the lights on\u2019 by spending on infrastructure. However, help is at hand for technology leaders: cloud infrastructure provides the flexibility to control costs that legacy on-premise equipment does not.\nUnlocking competitive advantage from cloud infrastructure can be as easy as analysing workloads and right-sizing resources. However, the opportunities to optimise cloud spend run considerably deeper. At Google Cloud, we aim to help customers maximise the value of their investments in our products and services.\u00a0\nFor example, James Gwee, Chief Technology Officer and Co-founder of enterprise event application Micepad, says "Google Cloud helped us find ways to save money. This was counterintuitive because the assumption is that vendors want to bill as much as possible. Instead, Google Cloud comes in and shows us how to pay them less. It really gives us the feeling that Google Cloud cares about startups."\nHere are 10 techniques businesses can use to free up resources to focus on delivering value:\n1. Employ AI to provide cost optimisation around the clock\nArtificial intelligence and machine learning tools can operate over cloud workloads, learning over time the resources needed and making adjustments to ensure businesses pay only for what they need.\n2. Look for committed\u00a0use discounts\nOptimising cloud means selecting the best pricing model for a business. Technology leaders may ask cloud providers about flexibility in pricing for long-term committed workloads, where the technology team understands the workloads well and knows only minimal resources are needed on an ongoing basis.\u00a0\nCloud providers may offer discounts in these circumstances, and at the other end of the dial \u2013\u00a0 where a team needs only to spin up a resource for a few hours.\n3. Identify non-time-critical workloads\nIf a business has large workloads that do not have to run in real-time, preemptible virtual machines present an opportunity to manage costs. A business can load a virtual machine into a cloud provider\u2019s platform to run when a cloud provider has available resources. As long as a workload can tolerate stop-start operation, this can be cost effective.\n4. Make use of autoscaling\nIf a business has highly variable workloads \u2013 for example an e-commerce website that hosts sales events that spike demand \u2013 and runs in the cloud, autoscaling can activate new virtual machine instances or containerised application instances to meet demand. It then shuts down\u00a0 resources when demand drops.\n5. Keep your storage only as active as it needs to be\nMany businesses are generating large data volumes - but only a small proportion needs to be hosted on high performance storage. Cloud providers can provide tiered data storage ranging from high performance platforms down to \u2018nearline\u2019 and \u2018coldline\u2019 storage, with each tier priced accordingly.\u00a0\nHowever, a key difference between providers is whether they can autotier data based on policy and AI. This can deliver efficiencies, with infrequently-accessed data moved to lower cost and more appropriate storage tiers.\n6. Make sure you have full visibility\nWhen evaluating cost monitoring tools, businesses should look for role-based, granular visibility. Business units, individual teams and developers should all be able to track costs. The tool should also forecast likely workload costs, while raw data should also be available to a company\u2019s existing business insights tools.\n7. Take the free advice from your cloud vendor\u2019s presales team\nCloud providers\u2019 consulting and presales teams are\u00a0 accustomed to helping customers identify the most cost-effective cloud configuration. Businesses can make the most of free advice to optimise deployment, and take advantage of\u00a0 planning tools and methodologies.\n8. Consider engaging professional services partners\nCloud cost optimisation can require detailed planning, observation and tuning of resources. Professional services experts can help deliver significant cost reductions, starting with full-scale assessments of existing workloads ( legacy and cloud-migrated) and detailed cost optimisation strategies.\n9. Write once, run anywhere\nThe containerisation of applications and associated frameworks revolutionises scalability - rather than running heavily resourced virtual machines running full operating systems to accommodate applications, businesses can spin up thousands of instances of an application almost instantly.\nBusinesses should look for cloud vendors that support \u2018write once, run anywhere\u2019 technology, and can orchestrate the deployment and management of those applications across multiple different cloud platforms.\n10. Build a multicloud strategy to balance cloud economics\nOpenness and contestability delivered through a multi-cloud strategy can help optimise costs. Technologies like Kubernetes can deliver ease of management across cloud services and inform decisions about workload placement.\nLearn more here about how to optimise cloud costs with Google Cloud.\u00a0\n Supplied by Google\nAbout Matthew Zwolenski:\u00a0\nMatt leads the Technology and Architecture team for Google Cloud across Australia and New Zealand. His team is responsible for the cloud transformation journeys of many of the largest organisations in the region, as well as accelerating and scaling digital native organisations. Matt's team consists of AI and machine learning specialists, cloud architects and application and infrastructure modernisation specialists who help customers on their digital journeys.