Solution
Cloud architecture, performance and cost
Analysis of CPU, memory, network and storage workloads to size cloud platforms. Configuration optimisation based on measured response times, processing throughput and costs.
Architecture and implementation
Service architecture
Compute, storage and data environment design for applications.
Performance and capacity
Workload measurement, resource sizing and configuration optimisation.
Cost analysis
Tools for analysing costs and resource consumption by service and environment.
Design decisions
Analysis of CPU, memory, storage and network metrics alongside cloud resource costs. Sizing compares job execution time, API latency and transfer volume to identify configurations suited to the measured workload.
Illustrative implementation
For a periodic workload, the comparison can cover a permanent server and on-demand execution, including startup time, computation, storage and data transfers under explicit workload assumptions.
Engineering outputsWorkload profile, option comparison, optimised configuration and before/after measurements
Development and integration
- Azure and Google Cloud architecture
- Capacity planning and performance analysis
- Consumption and cost monitoring
- Configuration automation
Systems involved
- Cloud services and data platforms
- Containers, databases and applications
- Logs, metrics and billing data
Service lineAzure and Google Cloud →
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