Cloud Computing Services: AWS, Azure & GCP Solutions That Scale (2026)

Cloud computing services have become the operational foundation for modern businesses, replacing data centres and dedicated hardware that characterised enterprise IT for the previous three decades. The three major cloud providers — AWS, Azure, and GCP — collectively offer thousands of services covering compute, storage, networking, databases, machine learning, analytics, security, and operational tooling. At Viprasol, our cloud solutions practice has helped clients across industries design, migrate to, and optimise cloud architectures that reduce operational overhead, improve reliability, and scale gracefully with business growth.

Getting cloud architecture right from the start prevents expensive re-architecture projects. The question in 2026 is no longer "should we use the cloud?" — it is "how do we use the cloud correctly?"

Choosing Between AWS, Azure, and GCP

The practical decision factors when choosing cloud providers: existing ecosystem alignment (Microsoft shops integrate naturally with Azure, heavy BigQuery users lean toward GCP, greenfield projects often choose AWS for service breadth), specific service requirements (GCP BigQuery for data warehousing, AWS Lambda for serverless, Azure AD for enterprise identity), support and pricing (enterprise support, committed use discounts, migration credits are actively negotiated), and talent availability.

Terraform is our infrastructure as code tool of choice for provisioning cloud resources reproducibly. Every resource is defined in version-controlled configuration files, changes are proposed through pull requests, and deployments happen through automated pipelines. Terraform modules encapsulate reusable infrastructure patterns, reducing new environment provisioning from days to minutes. For teams adopting Terraform: state management in S3/GCS with DynamoDB/Firestore locking, separate state files per environment, and policy enforcement via Sentinel or Open Policy Agent.

Kubernetes, Docker, and DevOps for Cloud-Native Applications

Kubernetes is the standard container orchestration platform for cloud-native workloads. Docker containers package application code and dependencies into immutable, portable artefacts; Kubernetes orchestrates their scheduling, scaling, networking, and lifecycle management at scale. Managed Kubernetes offerings — EKS, AKS, and GKE — handle control plane management, leaving teams to focus on workloads.

DevOps practices for Kubernetes workloads include: Helm charts for packaging applications, ArgoCD or Flux for GitOps-based continuous deployment, Istio or Linkerd for service mesh, and Prometheus plus Grafana for metrics and dashboards. CI/CD pipelines follow the GitOps pattern: code changes trigger pipeline build and test, Docker image publish to registry, Helm chart version update, and ArgoCD synchronisation of cluster state.

Serverless computing — AWS Lambda, Azure Functions, GCP Cloud Functions — is ideal for event-driven, variable-traffic workloads. Primary limitation for latency-sensitive APIs: cold start latency (100-500ms for interpreted runtimes). Many production architectures combine containers for latency-sensitive endpoints and serverless for background processing.

Cloud cost optimisation disciplines: right-sizing overprovisioned instances, reserved capacity purchases (30-60 % savings vs. on-demand), spot/preemptible instances for fault-tolerant batch workloads (70-80 % savings), auto-scaling to match actual demand, and storage tiering for infrequently-accessed data.

Explore our full cloud capabilities at /services/cloud-solutions/, browse our blog for cloud engineering articles, and review our approach.

External reference: AWS Well-Architected Framework provides comprehensive guidance on cloud architecture best practices.

Frequently Asked Questions

How much do cloud computing services cost for a typical web application?

A small-to-medium web application on AWS (ECS or EKS deployment, RDS PostgreSQL, CloudFront CDN, S3 storage) typically costs $300-$2,000 per month depending on traffic volume, database size, and data transfer. A startup serving 10,000 monthly active users typically pays $400-$800 per month. We provide detailed cost estimates as part of architecture design engagements.

How long does a cloud migration take?

Timeline depends heavily on current environment complexity and migration strategy. A lift-and-shift migration of a simple web application takes 4-8 weeks. A modernisation migration to containers and managed services takes 3-6 months for a single application. An enterprise migration of a complex application portfolio takes 12-24 months when done properly. We always recommend a phased migration starting with the least complex, highest-value workloads.

Should we go all-in on one cloud or adopt a multi-cloud strategy?

A single primary cloud with deliberate multi-cloud for specific services is our usual recommendation. All-in single-cloud maximises purchasing leverage and integration simplicity. True multi-cloud (running the same workloads on multiple clouds for redundancy) adds significant operational complexity and usually provides less benefit than a well-architected single-cloud deployment with proper availability zones and regional failover. Using GCP BigQuery for analytics while running applications on AWS, for example, is rational multi-cloud.

How do we ensure cloud security and compliance?

Cloud security starts with the principle of least privilege: every service, person, and process should have only the permissions it needs. Infrastructure as code with policy enforcement prevents insecure configurations. AWS Security Hub, Azure Defender, and GCP Security Command Center provide continuous compliance monitoring. Encryption at rest and in transit is non-negotiable. We implement security controls as code alongside application infrastructure, making security auditable and reproducible.

Why choose Viprasol for cloud computing services?

We approach cloud architecture as a long-term engineering discipline, not a one-time migration project. Our Terraform-managed infrastructure is reproducible and auditable. Our Kubernetes deployments are production-hardened with proper security, observability, and DR configurations. Our cost optimisation practice has saved clients 20-40 % on cloud bills. We are cloud-provider agnostic — our recommendations are driven by your workload requirements, not by vendor partnership incentives.