Cloud cost optimisation
Understand the cloud bill. Change what drives it.
Find idle capacity, expensive data paths and scaling issues using workload measurements and ownership tags.
A cheaper component can create a more expensive system
The fragile approach
Optimise the biggest line item alone
A cheaper component can increase data transfer, operational effort or the cost of failures elsewhere.
The intended approach
Evaluate the full workload cost
Model the change against demand, support effort and recovery requirements before committing to it.
An implementation example
Reduce waste without hiding the tradeoff
Inspect idle capacity, data movement, storage lifecycle and expensive request paths. Agree how shared costs are allocated so teams can understand and act on the result.
Explain the bill before changing the system
Finance and engineering need to understand the AUD operating cost of shared services.
A failure to account for
Unallocated network transfer becomes a large unexplained item in the monthly review.
Illustrative scenario, not a customer case study.
Prepare the conversation
What needs attention in your system?
Select the areas you want to discuss. Download the list to share with your team.
0 areas selected
Cloud & platform engineering
Find the cost driver behind the bill.
Cost attribution
Connect workloads and shared services to owners using understandable allocation rules.
Usage analysis
Review capacity, idle resources, storage lifecycle and data transfer against workload requirements.
Change validation
Check performance and reliability after a cost change so savings do not conceal operational regressions.
Not before reviewing the workload and its constraints. Recommendations should identify a baseline, implementation effort and a way to verify the result.
Discuss cloud cost optimisation
Bring the workflow, the constraints and the questions your team needs to resolve.