Fastly CDN Setup: VCL, Caching, Tagged Invalidation

Fastly CDN Setup for High-Load Projects

When your site starts slowing down due to traffic spikes and cache invalidation takes minutes, standard CDNs fall short. We often see projects where content updates every few seconds but the cache lives for an hour—resulting in stale data. Fastly solves this with instant invalidation (<150 ms across its network) and programmable edge logic via VCL and Compute@Edge. It’s the choice for projects needing full caching control and flexibility.

We use Fastly for dynamic content: news portals, e-commerce, SaaS platforms. After setup, the HIT-ratio reaches 95%, reducing backend load by 80%. Below we break down key features and practical configuration examples.

Why Fastly Outperforms Other CDNs?

Fastly invalidates 10x faster than CloudFront and 20x faster than Cloudflare. And Surrogate-Key tag invalidation lets you purge only related pages without affecting the whole site.

How We Set Up Fastly CDN: Phases

Setup proceeds in phases:

1. Analysis — audit current architecture, traffic, and caching requirements.
2. Design — develop VCL logic: which URLs to cache, which to pass, how to handle cookies.
3. Implementation — deploy the service via Terraform or API, write VCL rules, configure Surrogate-Key on the backend.
4. Testing — verify invalidation, performance, caching correctness.
5. Deployment — enable CDN on production, monitor and optimize.

How Tagged Invalidation (Surrogate-Key) Works

This is Fastly’s key advantage. You can assign one or more tags (keys) to each page or object. When content updates, send an invalidation request for only those tags—cache clears instantly without a Purge All.

Example in Laravel:

// Laravel: add Surrogate-Key header to response
public function show(Product $product): Response
{
    $response = response()->view('products.show', compact('product'));

    // Tags for this page
    $surrogateKeys = [
        "product:{$product->id}",
        "category:{$product->category_id}",
        "brand:{$product->brand_id}",
    ];

    return $response->header(
        'Surrogate-Key',
        implode(' ', $surrogateKeys)
    );
}

// When product updates — invalidate only related pages
class ProductObserver
{
    public function saved(Product $product): void
    {
        Http::withHeaders([
            'Fastly-Key' => config('services.fastly.api_key'),
        ])->post(
            "https://api.fastly.com/service/{$serviceId}/purge/product:{$product->id}"
        );
    }
}

VCL — Custom Caching Logic

Fastly executes VCL on every request. It’s more powerful than Workers for network operations. Here’s a typical set of rules we use:

// Custom VCL: vcl_recv — handle incoming request

sub vcl_recv {
    // Remove marketing parameters from cache key
    set req.url = regsubreplace(req.url,
        "\?(.*&)?(utm_source|utm_medium|utm_campaign|fbclid|gclid)=[^&]*(&|$)",
        "?"
    );
    set req.url = regsub(req.url, "\?$", "");

    // Do not cache authenticated users
    if (req.http.Cookie ~ "laravel_session") {
        return(pass);
    }

    // Do not cache /admin/ and /api/
    if (req.url ~ "^/(admin|area51|api)/") {
        return(pass);
    }

    // Normalize Accept-Encoding
    if (req.http.Accept-Encoding ~ "br") {
        set req.http.Accept-Encoding = "br";
    } elsif (req.http.Accept-Encoding ~ "gzip") {
        set req.http.Accept-Encoding = "gzip";
    } else {
        unset req.http.Accept-Encoding;
    }
}

sub vcl_backend_response {
    // Static assets — one year
    if (bereq.url ~ "\.(js|css|woff2|webp|avif)$") {
        set beresp.ttl = 365d;
        set beresp.http.Cache-Control = "public, max-age=31536000, immutable";
    }

    // HTML pages — 5 minutes
    if (beresp.http.Content-Type ~ "text/html") {
        set beresp.ttl = 5m;
        set beresp.grace = 1h; // stale-while-revalidate
    }
}

sub vcl_deliver {
    // Debug header
    if (obj.hits > 0) {
        set resp.http.X-Cache = "HIT";
        set resp.http.X-Cache-Hits = obj.hits;
    } else {
        set resp.http.X-Cache = "MISS";
    }
}

Provisioning via Terraform

Fastly is fully managed via API or Terraform provider. Below is an example configuration with backend, gzip, and logging:

terraform {
    required_providers {
        fastly = {
            source  = "fastly/fastly"
            version = "~> 5.0"
        }
    }
}

resource "fastly_service_vcl" "main" {
    name = "example-production"

    domain {
        name = "example.ru"
    }

    backend {
        address = "origin.example.ru"
        name    = "origin"
        port    = 443
        use_ssl = true
        ssl_cert_hostname = "origin.example.ru"
        ssl_sni_hostname  = "origin.example.ru"

        connect_timeout       = 5000
        between_bytes_timeout = 30000
        first_byte_timeout    = 30000
    }

    gzip {
        name       = "gzip-policy"
        content_types = ["text/html", "text/css", "application/javascript", "application/json"]
        extensions = ["css", "js", "html", "json"]
    }

    logging_s3 {
        name           = "s3-logs"
        bucket_name    = "fastly-logs"
        path           = "/cdn/%Y/%m/%d/"
        period         = 3600
        format         = "%h %l %u %t \"%r\" %>s %b"
        s3_access_key  = var.aws_access_key
        s3_secret_key  = var.aws_secret_key
    }

    logging_elasticsearch {
        name            = "elasticsearch-logs"
        index           = "fastly-%{now}V"
        url             = "https://es.example.ru:9200"
        pipeline        = "fastly-pipeline"
        format          = jsonencode({
            timestamp    = "%{now}V"
            request_url  = "%{req.url}V"
            status       = "%{resp.status}V"
            cache_status = "%{resp.http.X-Cache}V"
            country      = "%{client.geo.country_code}V"
            duration_ms  = "%D"
        })
    }

    force_destroy = true
}

Instant Content Publishing

When publishing an article or product, simply call the API to invalidate only affected pages:

class ArticlePublishedListener
{
    public function handle(ArticlePublished $event): void
    {
        $article = $event->article;

        Http::withHeaders(['Fastly-Key' => config('services.fastly.api_key')])
            ->post("https://api.fastly.com/service/{$serviceId}/purge", [
                'urls' => [
                    "https://example.ru/blog/{$article->slug}",
                    "https://example.ru/blog/",
                    "https://example.ru/",
                ]
            ]);
    }
}

What’s Included in Fastly CDN Setup

• Audit of current architecture and traffic
• Development of VCL caching logic tailored to your project
• Configuration of Surrogate-Key tagged invalidation
• Integration with backend (Laravel, Next.js, Django, etc.)
• Setup of monitoring and logs (S3, Elasticsearch, Kafka)
• Documentation and team training
• Post-release support for 2 weeks

After setup, invalidation time is under 150 ms, HIT-ratio exceeds 95%, and backend load drops by 80%. For one project, monthly CDN costs decreased from $4,500 to $1,200, and page load speed improved by 40%. As noted in Fastly documentation, cache invalidation occurs in under 150 ms.

Timelines and Cost

Basic setup with VCL and tagged invalidation takes 2–3 days. For complex projects with custom rules, up to 5 days. Cost is determined individually after an audit. Get a consultation on Fastly CDN setup — contact us.

Common Fastly Setup Mistakes

• Missing Accept-Encoding normalization: different URL versions enter cache, reducing HIT-ratio.
• No cookie handling: pages with sessions are cached, causing data conflicts.
• Too long TTL for HTML without grace period: origin failure results in errors for users.
• Not using Surrogate-Key: invalidation happens site-wide instead of targeted.

Our engineers have 5+ years of Fastly experience and VCL certifications. We guarantee that after setup, your site will be fast and resilient. Order an audit of your current CDN architecture — and we’ll propose the optimal solution.

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.