Cloud Infrastructure, with the whole app in view.
Cloud infrastructure optimization solves backend downtime, erratic latency spikes, and spiraling cloud hosting costs during periods of high mobile user growth. Mobile apps frequently launch on monolithic, under-provisioned servers or poorly configured cloud setups that cannot handle viral traffic surges, resulting in API timeouts, database deadlocks, and severe user dissatisfaction.
What we can take care of
- Cloud infrastructure architecture review and cost-optimization audit across AWS, Google Cloud, or Azure
- Containerized microservices orchestration utilizing Docker, Kubernetes, or serverless architectures (AWS Lambda, Cloud Functions)
- Database architecture, read/write replica scaling, and high-performance caching (Redis, DynamoDB, PostgreSQL)
- Global Content Delivery Network (CDN) and edge caching configuration for rapid static asset delivery
- Infrastructure as Code (IaC) implementation utilizing Terraform or AWS CloudFormation
- Comprehensive cloud observability, distributed tracing, and automated alert systems (Datadog, New Relic, CloudWatch)
- Disaster recovery planning, automated database backup verification, and multi-region failover design
How we approach the work
We design cloud backends to operate invisibly, securely, and cost-effectively at massive scale. We assess projected mobile API request volumes, designing decoupled, event-driven architectures that scale horizontally as traffic surges. We optimize database queries, implement multi-tier caching strategies to offload primary storage, and codify all infrastructure using Infrastructure as Code (IaC) to guarantee repeatable, secure deployments across environments.
What progress looks like
Backend uptime SLA percentage (99.99%+), average and 99th-percentile (p99) API response latency, cloud infrastructure cost per active monthly user, and recovery time objective (RTO) during simulated outages.
Before we begin
Share your app links, the challenge and the outcome you want. Your concierge will confirm inputs, deliverables, timing and costs for your scope before work begins.
How can an app reduce cloud infrastructure costs without sacrificing performance or reliability?
We typically achieve significant cost reductions by auditing underutilized resources, replacing idle provisioned servers with auto-scaling compute pools, implementing aggressive caching at the edge and application layers to minimize expensive database operations, and purchasing reserved instances or savings plans for predictable baseline workloads.