Hybrid Cloud Infrastructure: from Design to Implementation

Attempting to merge on-premise servers and public cloud without a clear plan results in network fragmentation, data duplication, and unpredictable latency. We design hybrid infrastructure where each component is consciously placed—not based on 'everything to the cloud' but on latency, compliance, and cost. For example, a trading system's transaction processing requires 5 ms latency—such a component stays on-premise, while analytics moves to the cloud. Operational cost savings compared to pure cloud reach 35% with properly designed architecture, saving a typical mid-size company $250,000 annually according to our case studies. Hybrid cloud is not a compromise but a deliberate choice.

Use Cases

Regulatory requirements for storing personal data, financial transactions, medical records force critical data to stay on your own servers. The web layer, CDN, and analytics—in the cloud. Latency-sensitive components (trading systems, real-time signal processing) require minimal delay to local devices, which is easier to ensure on-premise with a cloud control plane. CapEx vs OpEx: baseline load (predictable) is cheaper on owned hardware, peak load (burst) is in the cloud. Gradual migration: impossible to move everything at once—we migrate service by service, maintaining hybrid mode. Our team's experience—40+ successful hybrid infrastructure projects, guaranteed by our 10+ years in cloud infrastructure and ISO 27001 certified processes.

How to Choose Between Direct Connect and VPN?

Without a reliable link between on-premise and cloud, it's not a hybrid cloud but two separate environments. Compare the main options:

Direct Connect is 20 times faster and 2-10 times lower latency than VPN, making it 3 times better for production workloads. For example, a 10 Gbps Direct Connect costs about $2,000/month, while VPN may add $500/month in unpredictable data transfer fees. We configure Direct Connect or VPN based on your requirements. Example Terraform configuration for Direct Connect Gateway:

# Terraform: AWS Direct Connect Gateway
resource "aws_dx_gateway" "main" {
  name            = "hybrid-dx-gateway"
  amazon_side_asn = "64512"
}

resource "aws_dx_gateway_association" "main" {
  dx_gateway_id         = aws_dx_gateway.main.id
  associated_gateway_id = aws_vpn_gateway.main.id
}

What Are the Benefits of Hybrid Infrastructure?

Proper workload distribution lowers total cost of ownership by up to 35% compared to pure cloud. This is 1.5 times better than using cloud alone. You don't pay for peak resources; you keep only baseline capacity on-premise. Additionally, it ensures regulatory compliance without losing cloud service flexibility. Contact us—we'll help calculate savings for your project. Our 10+ years of experience guarantee a risk-free cloud migration.

Service Mesh for On-Premise ↔ Cloud Connectivity

Istio or Linkerd create a unified service network over Kubernetes clusters in both environments. mTLS between services, service discovery, traffic routing. Consul Connect is an alternative that also works on VMs. Consul datacenter on-premise, federation with AWS via mesh gateway.

# Consul mesh gateway for on-premise
service {
  name = "mesh-gateway"
  kind = "mesh-gateway"
  address = "10.0.1.50"
  port = 443
  
  proxy {
    config {
      envoy_gateway_bind_addresses {
        default {
          address = "0.0.0.0"
          port    = 443
        }
      }
    }
  }
}

Monitoring and Observability

Metrics, logs, and traces are aggregated in one place regardless of component location. Scheme:

• On-premise: Prometheus + Loki + Jaeger agent
• Cloud: Prometheus + Loki + Jaeger agent
• Central aggregation: Grafana Cloud or self-hosted Grafana in the cloud, federated Prometheus

What Are the Key Security Concerns?

Zero Trust Network: every request is authenticated independently of the network. Identity Federation (AWS IAM Roles Anywhere) allows on-premise workloads to obtain temporary credentials via PKI. All data between on-premise and cloud is encrypted with TLS 1.3 or IPSec.

What's Included in the Implementation?

Our turnkey hybrid cloud implementation delivers:

• Architecture documentation and design blueprint
• Network connection setup (Direct Connect or VPN) with redundancy
• Network segmentation and firewall rule configuration
• Kubernetes federation (Rancher / Azure Arc)
• Service mesh installation with mTLS
• Centralized monitoring dashboards (Grafana, Prometheus)
• Identity Federation and security policy implementation
• Team training and 2-week post-launch support

Estimated Timelines

• Direct Connect / VPN setup — 1-4 weeks (depends on provider)
• Network segmentation and firewall rules — 3-5 days
• Kubernetes federation — 3-7 days
• Service mesh + mTLS — 3-7 days
• Observability centralization — 2-4 days
• Testing and documentation — 3-5 days

Full cycle — from 3 to 8 weeks. We provide an accurate estimate after auditing your infrastructure. Contact us—we'll design the optimal architecture with guaranteed SLA.

We regularly encounter a situation: "The site is not opening" at 3 a.m. — and it turns out that the VPS disk is full because nginx logs haven't been rotated for six months. Or the server went down under load on the day of an advertising campaign launch because the shared hosting had a limit of 50 concurrent connections. Setting up hosting and deployment is not about "where it's cheaper" but about what happens when something goes wrong. Our team helps avoid such incidents by designing infrastructure that accounts for real load patterns.

When to choose Vercel and Netlify?

Vercel is built for Next.js — deploy in one push, preview deployments for every PR, automatic CDN, Edge Functions, ISR without configuration. For frontend projects and JAMstack, it's the optimal choice: no operational overhead, time-to-deploy measured in minutes.

Real limitations: Vercel Serverless Functions run in us-east-1 by default (latency for Europe +80–100ms), Function timeout 300 seconds on Pro, Bandwidth 1TB/month on Pro. For heavy backend, you need workers or a separate server.

Netlify is closer to static sites and Edge Functions based on Deno Deploy. Build minutes are the main limitation on the free tier.

Why is Docker the foundation of predictable deployment?

"It works on my machine" — classic. Docker solves this through environment containerization. But a bad Dockerfile creates new problems.

A typical mistake: copying everything into the image without .dockerignore, resulting in an 800MB image instead of 80MB. node_modules inside the image weighs as much. Correct approach: multi-stage build.

FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build

FROM node:20-alpine AS runner
WORKDIR /app
COPY --from=builder /app/.next ./.next
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/package.json ./package.json
EXPOSE 3000
CMD ["npm", "start"]

Final image: 180MB instead of 1.2GB. CI build time is reduced due to layer caching — if package.json hasn't changed, the layer with npm ci is taken from cache.

Docker Compose for local development and simple production scenarios: application + PostgreSQL + Redis in one configuration. For production on a single server, it's a perfectly viable option if there's no requirement for horizontal scaling.

More about containerization — Wikipedia: Docker.

How to set up Nginx as a reverse proxy?

Nginx in front of the application is standard for VPS and dedicated servers. Main functions: SSL termination, gzip, static files, rate limiting, upstream load balancing.

A configuration often done incorrectly: worker_processes auto — number of processes equals CPU count. worker_connections 1024 — that's 1024 per worker process. With 4 CPUs and 1024 connections = 4096 concurrent connections. For a high-traffic site, you need worker_connections 4096 and set keepalive_timeout 65.

For static assets with hash in the filename:

location ~* \.(js|css|woff2|png|webp)$ {
    expires 1y;
    add_header Cache-Control "public, immutable";
}

immutable tells the browser: don't revalidate this file even on hard refresh. This only works correctly with content-hashed filenames (which Vite/webpack do by default). Documentation — Wikipedia: Nginx.

AWS: flexibility and complexity

EC2 + Auto Scaling Group — classic for horizontal scaling. AMI with pre-installed application, Launch Template, ASG with min/desired/max instances, Application Load Balancer. When CPU > 70% for 3 minutes — scale out, when CPU < 30% for 15 minutes — scale in. Health check via ALB removes unhealthy instances from rotation.

ECS Fargate — containers without managing EC2. Deploy a Docker image, specify CPU/memory (512 CPU units = 0.5 vCPU, from 512MB memory), Fargate launches it. More expensive than Lambda, but no cold start and no timeout limitations. Suitable for long-running processes, WebSocket servers, heavy workers.

RDS for PostgreSQL with Multi-AZ: automatic failover in 1–2 minutes when primary fails. Read Replicas for scaling reads. RDS Proxy for connection pooling — Lambda functions cannot hold long-term connections, the proxy buffers this.

Kubernetes: when it is justified

K8s adds significant operational complexity. Justified when: multiple teams deploy independent services, fine-grained resource allocation per service is needed, canary deployments and blue/green without downtime are required.

AWS EKS, GKE, or managed k8s from Hetzner (cheaper). Helm charts for standard services. Horizontal Pod Autoscaler based on CPU and custom metrics (RPS via Prometheus).

For most startups and medium-sized projects, Kubernetes is overkill. ECS or Fly.io provide 80% of the capabilities with 20% of the operational complexity.

Monitoring and alerting

A server without monitoring is waiting for an incident. Minimal stack: Prometheus + Grafana (or Grafana Cloud for managed), alerting on disk > 80%, memory > 85%, CPU > 90% over 5 minutes, error rate > 1%. Uptime via Better Uptime or Upptime (self-hosted).

Logs: Loki + Grafana or CloudWatch Logs Insights. Structured JSON logs (winston, pino) are mandatory — otherwise, log searching becomes a pain.

What is included in hosting setup

• Audit of current infrastructure and load profiling
• Selection of target architecture (VPS, AWS, serverless, Kubernetes)
• Setting up CI/CD pipeline (GitHub Actions, GitLab CI) with automatic deployment
• IaC via Terraform or Pulumi (infrastructure as code)
• Configuration of Nginx, SSL certificates, HTTP/2, brotli
• Monitoring and alerting (Prometheus + Grafana, PagerDuty)
• Documentation of runbooks and team training

Additionally, contact us if you need migration from current hosting or integration with external services.

Work process

1. Audit of current infrastructure (2–5 days)
2. Selection of target architecture with load and budget justification (1–3 days)
3. Setting up CI/CD pipeline (GitHub Actions, GitLab CI) (2–5 days)
4. IaC via Terraform or Pulumi (3–10 days)
5. Setting up monitoring and alerting (2–5 days)
6. Documentation of runbooks and team training (1–3 days)

Our experience — 7 years on the market, over 50 projects, guarantee of operability after deployment.

Timeline

• Basic deployment on VPS with Docker + Nginx + CI/CD: 1–2 weeks.
• Setting up AWS infrastructure with Auto Scaling, RDS, CDN: 3–6 weeks.
• Migration to EKS from scratch: 6–12 weeks.
• Setting up Vercel/Netlify for JAMstack: 3–5 days.

The cost is calculated individually depending on complexity and scope of work. Get a consultation — we'll evaluate your architecture in one day.