Billing and usage analysis
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Improve cloud cost visibility and optimise AWS resource usage with workload analysis, resource rightsizing and cost management strategies. Datanet Hosting helps businesses align cloud spending with their infrastructure requirements.
Request a Cost Optimisation Consultation
Cost optimisation can include usage analysis, resource right-sizing, idle resource identification, storage lifecycle review and purchasing option evaluation.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
A cost review should distinguish avoidable waste from required capacity and consider utilisation, commitments, storage tiers, data transfer and operational trade-offs.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Review bills, usage reports, account allocation and cost trends by service and workload.
Evaluate rightsizing, idle resources, storage tiers, data transfer and commitment options.
Prioritise approved changes and measure cost, utilisation and performance after implementation.
AWS cost optimisation is an ongoing process of understanding cloud spend, matching resources to demand and improving cost efficiency without compromising required performance.
A cost review should distinguish avoidable waste from required capacity and consider utilisation, commitments, storage tiers, data transfer and operational trade-offs.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Cost optimisation recommendations are based on actual usage, workload constraints and pricing commitments. Savings are not guaranteed and depend on implementation and ongoing demand.
Share your AWS billing concerns and discuss a practical cost review with our cloud optimisation team.
Improve AWS cost visibility and align resource consumption with actual workload demand.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
Recommendations are prioritised by potential impact, implementation effort, risk and performance requirements.
| Service feature | Starter | Business | Managed |
|---|---|---|---|
| Billing, usage and cost allocation review | ✓ | ✓ | ✓ |
| Idle resource and rightsizing analysis | ✓ | ✓ | ✓ |
| Budgets, anomaly alerts and reporting | — | ✓ | ✓ |
| Savings Plans and Reserved Instance evaluation | — | ✓ | ✓ |
| Recurring FinOps and trend reporting | — | — | ✓ |
Cost optimisation recommendations are based on actual usage, workload constraints and pricing commitments. Savings are not guaranteed and depend on implementation and ongoing demand.
AWS pricing varies by region, service, usage and purchasing option. Compare regional costs alongside latency, data residency and service availability.
Cost optimisation is useful for unexpected bill increases, growing environments, idle resources, budget governance and recurring cloud spend reviews.
Cost optimisation is useful for unexpected bill increases, growing environments, idle resources, budget governance and recurring cloud spend reviews.
Cost optimisation is useful for unexpected bill increases, growing environments, idle resources, budget governance and recurring cloud spend reviews.
Cost optimisation is useful for unexpected bill increases, growing environments, idle resources, budget governance and recurring cloud spend reviews.
| Project area | Datanet Hosting | Self-managed |
|---|---|---|
| Billing and usage analysis | ✓ | Customer-led |
| Rightsizing and idle resource recommendations | ✓ | Self-reviewed |
| Budgets and cost alert configuration | ✓ | Self-configured |
| Recurring cost trend and commitment review | ✓ | Customer-managed |
A cost assessment can identify potential savings through rightsizing, idle resource cleanup, storage lifecycle changes and purchasing options. Actual savings depend on usage and implementation.
Rightsizing matches resource types and sizes to observed workload utilisation and performance requirements.
Savings Plans can reduce eligible compute costs in exchange for a usage commitment. The commitment should be evaluated against stable and forecast usage.
Yes. Reporting can cover spend trends, service allocation, budget variance, anomalies and optimisation actions according to the agreed review cadence.
A cost review should distinguish avoidable waste from required capacity and consider utilisation, commitments, storage tiers, data transfer and operational trade-offs.
Compare CPU, memory, throughput and demand patterns before changing resource sizes.
Identify unattached volumes, unused addresses, stopped instances and unnecessary resources.
Review lifecycle tiers, retention, retrieval and data-transfer paths.
Evaluate Savings Plans and Reserved Instances against predictable baseline demand.
Improve AWS cost visibility and align resource consumption with actual workload demand.
