Case Study: Cutting Bandwidth Costs with Edge Caching for a Mobile Navigation Startup

Hook: When slow maps and high CDN bills threaten product-market fit

Slow tiles, unpredictable cache behavior, and exploding egress bills are a fatal combination for mobile navigation startups. This case study — a hypothetical but realistic reconstruction inspired by map app comparisons and operator experience in 2025–2026 — shows how intelligent edge caching and TTL strategies cut CDN costs, lowered origin egress, and improved UX metrics for a navigation startup we’ll call NavLoop.

Executive summary (most important first)

NavLoop was paying $12,300/month in CDN bandwidth and observing poor cache hit ratios for map tiles and POI requests. After implementing a focused edge-caching strategy, versioned tiles, intelligent per-resource TTLs, and selective invalidation integrated with CI/CD, NavLoop achieved:

• 72% bandwidth cost reduction — CDN bill fell from $12.3k to $3.4k/month.
• Cache hit ratio up from 18% to 78% across edge POPs.
• Origin egress down from ~45 TB/month to ~12 TB/month.
• P95 API latency improved from 320ms to 120ms; LCP for core map view fell from 2.4s to 1.3s.

Below are the precise strategies, configs, tradeoffs, and observability tactics used — all actionable for engineering and SRE teams in 2026.

Context: why navigation apps are uniquely cost-sensitive

Map-driven apps are bandwidth intensive. Two asset classes dominate cost and performance:

• Map tiles (raster or vector) — many small files, high throughput, often cacheable if versioned.
• Dynamic route/POI data — lower bandwidth per response but high QPS and sensitive to freshness.

Because users expect instant panning and routing, low latency from edge POPs is critical. But default CDN behavior often sends too many requests back to origin due to non-optimal TTLs, unversioned assets, or aggressive cache keys that prevent reuse.

The hypothesis

By treating tiles and static map assets as long-lived, versioned objects at the edge, and by applying short but meaningful TTLs with stale-while-revalidate for dynamic content, NavLoop could shift traffic away from origin, reduce egress, and lower latency without sacrificing user-facing freshness.

Step 1 — Audit and measurement

Before engineering changes, NavLoop performed a focused audit over 7 days:

• Traffic profile: 65% map tiles, 20% static assets (JS/CSS/images), 15% API (routes, POI).
• Current cache hit ratio (global): 18% hit, 82% miss.
• Origin egress: ~45 TB/month, CDN bill $12.3k (bandwidth + requests).
• 95th percentile backend latency: 320ms; average tile fetch from origin: 180ms additional median.

Key failure modes in the audit:

• Tiles were not versioned — developer pushes invalidated caches via query strings that prevented long TTLs.
• Cache keys included unnecessary headers and query params, fragmenting cache.
• Dynamic routing responses used no stale-while-revalidate, resulting in origin bursts during traffic spikes.

Step 2 — Define a pragmatic caching model

NavLoop used three classes with specific rules:

1. Versioned tiles and static assets — immutable; cached at edge for a year.
2. Semi-dynamic map metadata (POI updates, route hints) — short TTLs (30–300s) with stale-while-revalidate.
3. Real-time events (traffic incidents) — never cached at edge; delivered via push/streaming or short TTL with cache-bypass.

Why versioned tiles?

Versioning decouples freshness from caching. If a tile URL includes a build hash — /tiles/v3/{z}/{x}/{y}.pbf?v=20251201 — it can be cached far longer. When the map style or data changes, deploy a new version.

Step 3 — Implementation details and configs

NavLoop used a multi-CDN strategy in 2026, but the core patterns apply across providers. Below are representative configs and code snippets used to implement the model.

1) Cache-Control header patterns

For versioned tiles (immutable):

Cache-Control: public, max-age=31536000, immutable

For map metadata (semi-dynamic):

Cache-Control: public, max-age=60, s-maxage=60, stale-while-revalidate=30, stale-if-error=86400

For route responses that must be fresh but tolerate brief staleness:

Cache-Control: public, max-age=10, s-maxage=10, stale-while-revalidate=20

2) Edge key normalization (Fastly / VCL example)

Tile requests often include analytics query params. Normalize the cache key to drop irrelevant params and include the tile version token:

sub vcl_hash { 
  if (req.url ~ "^/tiles/v[0-9]+/") {
    hash_data(regsub(req.url, "\?.*$", ""));
    hash_data(req.http.Host);
  } else {
    hash_data(req.url);
  }
}

3) CloudFront + Lambda@Edge example: set TTLs based on path

Use a small Lambda@Edge function on viewer response to set Cache-Control dynamically:

exports.handler = (event, context, callback) => {
  const response = event.Records[0].cf.response;
  const uri = event.Records[0].cf.request.uri;

  if (uri.startsWith('/tiles/v')) {
    response.headers['cache-control'] = [{ key: 'Cache-Control', value: 'public, max-age=31536000, immutable' }];
  } else if (uri.startsWith('/api/poi')) {
    response.headers['cache-control'] = [{ key: 'Cache-Control', value: 'public, max-age=60, s-maxage=60, stale-while-revalidate=30' }];
  }

  callback(null, response);
};

4) Edge worker example: conditional TTLs and selective caching (Cloudflare Workers)

addEventListener('fetch', event => {
  event.respondWith(handle(event.request));
});

async function handle(request) {
  const url = new URL(request.url);
  let cacheTtl;

  if (url.pathname.startsWith('/tiles/v')) {
    cacheTtl = 31536000; // 1y
  } else if (url.pathname.startsWith('/api/poi')) {
    cacheTtl = 60; // 60s
  } else {
    cacheTtl = 10;
  }

  const cache = caches.default;
  const cacheKey = new Request(url.toString(), request);
  let response = await cache.match(cacheKey);

  if (!response) {
    response = await fetch(request);
    const headers = new Headers(response.headers);
    headers.set('Cache-Control', `public, max-age=${cacheTtl}, s-maxage=${cacheTtl}`);
    response = new Response(response.body, { ...response, headers });
    event.waitUntil(cache.put(cacheKey, response.clone()));
  }

  return response;
}

Step 4 — Invalidation, CI/CD and cache tagging

Invalidation is where many teams blow budgets. NavLoop used two techniques:

• Versioning-first — avoid invalidations by publishing new versioned URLs for tile/style changes.
• Cache-tagging + selective purge for non-versioned assets — purge by tag via CDN API from CI/CD on deploy.

Example purge flow integrated into CI (pseudo):

1. Deploy new tile generation to S3 under /tiles/v20260201/
2. CI calls CDN API to update route that maps /tiles/latest/> to the new prefix (no purge required).
3. For config changes, CI triggers CDN purge by cache-tag for only the affected assets.

Step 5 — Observability and KPIs

Track these metrics daily:

• Edge cache hit ratio (global & per-POP)
• Origin egress (GB/day)
• CDN bill (bandwidth + requests)
• Backend request rate (RPS to origin)
• TTFB & P95 latency for map view
• Core Web Vitals for representative flows (LCP, FCP)

NavLoop instrumented dashboards and alerting on cache hit deviation and on-surge origin egress. On the first day after deploy, they monitored P95 latency and cache hit to validate behavior.

Results — the numbers and user impact

Following the rollout over 30 days:

• Edge cache hit ratio: 18% → 78%.
• Origin egress: 45 TB/month → 12 TB/month (monthly)
• CDN bill: $12,300 → $3,420/month (72% saving)
• P95 latency for map view: 320ms → 120ms.
• Core Web Vitals (representative Android/iOS web view): LCP 2.4s → 1.3s.

These gains translated to improved engagement: session length for route planning grew by ~8%, and crash/timeout reports for slow map pans dropped by 60% — important leading indicators for retention.

Tradeoffs and gotchas

No caching strategy is free. Here are the tradeoffs NavLoop accepted and mitigations:

• Staleness vs cost — stale-while-revalidate introduces temporary staleness. Use short s-maxage for metadata and push critical real-time events via websockets or push channels.
• Personalization — user-specific content (saved places, recommendations) cannot be cached globally. Use session tokens and split responses so common data is cacheable and user-specific data is fetched separately.
• Cache-key fragmentation — dropping headers/params can cause subtle bugs (e.g., localized language preferences). Carefully whitelist headers important to behavior.
• Security — ensure signed URLs or cookies for paid layers; cached signed responses must be guarded or vary by signature key.
• Cache poisoning — validate inputs before caching and avoid caching on 4xx/5xx by default.

Why this approach is particularly relevant in 2026

Industry trends in late 2025 and early 2026 make these patterns even more effective:

• Major CDNs have expanded edge compute and tiered caches, reducing cold-miss times and enabling more powerful cache-key normalization at the edge.
• QUIC/HTTP/3 adoption has grown, lowering latency for cache hits — so moving traffic to edge POPs has a larger payoff.
• Vector tiles and on-device rendering are mainstream, which shifts the cost curve: smaller vector payloads reduce bandwidth but increase request counts — boosting the value of good cache hit ratios.
• Privacy regulations (e.g., cookie / consent changes finalized in 2025) have forced cleaner separation of personal and non-personal data — which simplifies caching strategies for public map assets.

Advanced strategies and future directions

For teams ready to evolve further:

• Adaptive TTLs driven by traffic patterns — use ML models to increase TTL for hot tiles and reduce for cold ones.
• Edge compute transforms — pre-generate merged tiles at edge on the first request to avoid origin pressure for composite overlays.
• Client-side caching and delta updates — use CBOR/Protobuf diffs for vector tiles to reduce bandwidth for panning; leverage service workers to hold a local tile cache.
• Cache-focused request shaping — rate-limit cache-bypass requests during spikes and serve stale content with warning headers to maintain UX.

Checklist — implementable in 2–4 sprints

1. Audit traffic: classify assets and measure current CHR, origin egress, and latency.
2. Introduce URL versioning for tile and style assets; set immutable Cache-Control.
3. Apply s-maxage + stale-while-revalidate on metadata endpoints.
4. Normalize cache keys; remove analytics query params and unnecessary headers.
5. Integrate purge-by-tag into CI/CD for non-versioned config changes.
6. Instrument dashboards for CHR, origin egress, P95 latency, and Web Vitals.

Closing note: metrics over dogma

Edge caching is not a silver bullet — it's an operational lever. The goal is measurable improvements in egress, latency, and UX. Let the metrics guide TTLs and purges, not intuition alone.

Call to action

If you run a map or navigation product, start by auditing your cache hit ratio and origin egress this week. Use the checklist above to apply versioned tiles, tailored Cache-Control headers, and selective invalidation. Want a hands-on walkthrough? Contact our team to run a free 2-hour cache audit and a simulated cost forecast based on your traffic profile.

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