AWS CloudFront CDN Setup Turnkey

When launching a site on AWS, global users often face slow loading. TTFB above 500 ms, LCP spikes, and the server can't handle peak load. Without a CDN, this is normal. We configure AWS CloudFront so that response times drop by 2–3× and origin load falls by 90%. Our experience: 5+ years working with AWS, 50+ projects, certified engineers. We guarantee SLA and round‑the‑clock support.

How CloudFront Speeds Up Your Site

CloudFront is Amazon's CDN with 450+ edge locations worldwide. Instead of always hitting your server, it delivers cached content from the nearest node. This radically reduces TTFB (first 50 ms) and improves Core Web Vitals: LCP, CLS, INP. Additionally, CloudFront supports HTTP/2, automatic Brotli/Gzip compression, and stale-while-revalidate. Traffic savings can reach 60% thanks to compression and edge caching.

Typical cache policies for different content types:

Why Choose CloudFront for AWS Infrastructure?

CloudFront deeply integrates with AWS—S3, ALB, API Gateway, Lambda@Edge. You can:

• Attach an SSL certificate via ACM for free.
• Use Origin Shield for an additional cache layer between edge and origin.
• Run custom logic on Edge Functions (CloudFront Functions or Lambda@Edge) with no latency.

Comparison with other CDNs:

CloudFront is the best fit if your infrastructure is already on AWS. It gives you full control over caching and security.

Real Problems CloudFront Solves

In one project with 100,000 unique daily visitors, we reduced TTFB from 800 ms to 40 ms after configuring CloudFront with Origin Shield and proper cache policies. Origin load dropped 50× and traffic costs decreased by 40%. Origin Shield is a second cache layer between edge and origin that aggregates requests and reduces load. Recommended for projects with thousands of requests per second.

Our Setup Process

1. Analysis: We study your site architecture, determine which resources to cache and which APIs to bypass.
2. Design: We design the distribution, cache policies, behaviors, and Origin Shield.
3. Implementation: We write Terraform configurations, set up SSL via ACM, and connect S3 for static content.
4. Testing: We verify cache headers, invalidation, and load speed in different regions.
5. Deployment: We deploy via CI/CD and document the process.

What's Included in the Work

• Documentation of the configuration and developer instructions.
• Access to CloudFront, ACM, S3 with minimal privileges.
• Training for your team: how to manage cache and create invalidations.
• One month of post‑launch support—fixing any unexpected issues.
• Monitoring via CloudWatch with alerts for errors and latencies.
• Performance report with metrics (TTFB, LCP, CLS) before and after implementation.

Example Terraform Configuration

# main.tf — creating a CloudFront distribution
resource "aws_cloudfront_distribution" "main" {
    enabled             = true
    is_ipv6_enabled     = true
    default_root_object = "index.html"
    price_class         = "PriceClass_200"

    # Main origin — Laravel on EC2/ALB
    origin {
        domain_name = aws_lb.main.dns_name
        origin_id   = "alb-origin"

        custom_origin_config {
            http_port              = 80
            https_port             = 443
            origin_protocol_policy = "https-only"
            origin_ssl_protocols   = ["TLSv1.2"]
        }

        custom_header {
            name  = "X-Origin-Verify"
            value = var.origin_verify_token
        }
    }

    # S3 origin for static files
    origin {
        domain_name            = aws_s3_bucket.assets.bucket_regional_domain_name
        origin_id              = "s3-assets"
        origin_access_control_id = aws_cloudfront_origin_access_control.main.id

        origin_shield {
            enabled              = true
            origin_shield_region = "eu-central-1"
        }
    }

    # Static assets from S3
    ordered_cache_behavior {
        path_pattern           = "/assets/*"
        target_origin_id       = "s3-assets"
        viewer_protocol_policy = "redirect-to-https"
        allowed_methods        = ["GET", "HEAD"]
        cached_methods         = ["GET", "HEAD"]
        compress               = true
        cache_policy_id        = aws_cloudfront_cache_policy.assets.id
    }

    # API — no cache
    ordered_cache_behavior {
        path_pattern           = "/api/*"
        target_origin_id       = "alb-origin"
        viewer_protocol_policy = "https-only"
        allowed_methods        = ["DELETE", "GET", "HEAD", "OPTIONS", "PATCH", "POST", "PUT"]
        cached_methods         = ["GET", "HEAD"]
        cache_policy_id        = data.aws_cloudfront_cache_policy.caching_disabled.id
        origin_request_policy_id = data.aws_cloudfront_origin_request_policy.all_viewer.id
    }

    # Main pages — short cache
    default_cache_behavior {
        target_origin_id       = "alb-origin"
        viewer_protocol_policy = "redirect-to-https"
        allowed_methods        = ["DELETE", "GET", "HEAD", "OPTIONS", "PATCH", "POST", "PUT"]
        cached_methods         = ["GET", "HEAD"]
        compress               = true
        cache_policy_id        = aws_cloudfront_cache_policy.pages.id
    }

    restrictions {
        geo_restriction { restriction_type = "none" }
    }

    viewer_certificate {
        acm_certificate_arn = aws_acm_certificate.main.arn
        ssl_support_method  = "sni-only"
        minimum_protocol_version = "TLSv1.2_2021"
    }
}

# Cache Policy for static assets
resource "aws_cloudfront_cache_policy" "assets" {
    name    = "assets-immutable"
    min_ttl = 31536000
    max_ttl = 31536000
    default_ttl = 31536000

    parameters_in_cache_key_and_forwarded_to_origin {
        cookies_config { cookie_behavior = "none" }
        headers_config  { header_behavior = "none" }
        query_strings_config { query_string_behavior = "none" }
        enable_accept_encoding_brotli = true
        enable_accept_encoding_gzip   = true
    }
}

Cache Invalidation During Deployment

# AWS CLI: invalidate everything
aws cloudfront create-invalidation \
    --distribution-id $DISTRIBUTION_ID \
    --paths "/*"

# Only HTML pages (after content publishing)
aws cloudfront create-invalidation \
    --distribution-id $DISTRIBUTION_ID \
    --paths "/blog/*" "/products/*" "/"

// Laravel: invalidation when an article is published
use Aws\CloudFront\CloudFrontClient;

class ArticlePublished
{
    public function handle(Article $article): void
    {
        $client = new CloudFrontClient([
            'version' => 'latest',
            'region'  => 'us-east-1',
        ]);

        $client->createInvalidation([
            'DistributionId' => config('services.cloudfront.distribution_id'),
            'InvalidationBatch' => [
                'Paths'     => ['Quantity' => 1, 'Items' => ["/blog/{$article->slug}"]],
                'CallerReference' => (string) now()->timestamp,
            ],
        ]);
    }
}

CloudFront Functions — Edge Security

// function.js — adds security headers (< 1 ms)
function handler(event) {
    var response = event.response;
    var headers = response.headers;

    headers['strict-transport-security'] = { value: 'max-age=63072000; includeSubDomains; preload' };
    headers['x-content-type-options'] = { value: 'nosniff' };
    headers['x-frame-options'] = { value: 'SAMEORIGIN' };
    headers['referrer-policy'] = { value: 'strict-origin-when-cross-origin' };

    return response;
}

resource "aws_cloudfront_function" "security_headers" {
    name    = "security-headers"
    runtime = "cloudfront-js-2.0"
    code    = file("function.js")
    publish = true
}

Origin Shield

An additional intermediate cache between edge nodes and the origin server. Reduces origin load by 10–50× for popular content. Enabled in the example above.

Timelines and Cost

Basic setup takes 1–2 days. Complex scenarios with Lambda@Edge and Origin Shield up to 5 days. We calculate the exact cost after analyzing your infrastructure. We'll evaluate your project in one day—contact us to get a proposal. Get a consultation on CloudFront setup today.

For more information: CloudFront Documentation, CDN

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.