Back-End and Architecture: Efficiency by Design
Cache at every layer—edge, application, and database—so repeated work is avoided. Batch background tasks, debounce triggers, and use idempotent designs to prevent duplicate processing. A charity platform moved heavy aggregations to scheduled jobs, slashing peak CPU usage while keeping dashboards fresh and boosting reliability during fundraising spikes.
Back-End and Architecture: Efficiency by Design
Avoid overprovisioning. Use autoscaling, spot instances where appropriate, and right-size instance types to your workload. Track utilization targets to keep servers in the efficient range. A SaaS team reduced their fleet by 25% after uncovering idle nodes, cutting spend and emissions without sacrificing latency or developer velocity.
Back-End and Architecture: Efficiency by Design
Select cloud regions with cleaner grids and publish your rationale. For batch processing, schedule jobs when the grid is greener, guided by forecasts from tools like ElectricityMap or similar services. Even partial shifting yields measurable reductions without compromising user experience, especially for non-urgent, compute-intensive workloads.
Back-End and Architecture: Efficiency by Design
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