What actually qualifies as "edge computing" versus just using a CDN?

A traditional CDN caches static content near users. Edge computing goes further — running actual compute (functions, logic, sometimes small databases) at those same edge locations, so dynamic requests can be handled without a round-trip to a central region. We help you figure out which one your workload actually needs.

Is edge computing worth it for our application?

It depends entirely on your latency sensitivity and user geography. If your users are concentrated in one region and your current latency is already acceptable, edge computing adds complexity without benefit. We benchmark first and only recommend it where the latency improvement is measurable and matters to the user experience.

How do you handle IoT devices with unreliable connectivity?

Edge gateways aggregate and process sensor data locally, using store-and-forward patterns so data isn't lost during connectivity gaps — it syncs to the cloud once the connection is restored, rather than requiring constant connectivity to function.

Does edge computing complicate our data residency/compliance requirements?

It can, if not planned for — data processed at edge locations in different jurisdictions raises real compliance questions. We map data residency requirements before choosing which edge locations and providers to use, not after.

Can edge deployments integrate with our existing Kubernetes or microservices setup?

Yes. Edge functions typically front your central services rather than replace them — handling caching, auth checks, and request routing at the edge while your Kubernetes-hosted microservices handle the core logic centrally.

Home›Solutions›Edge Computing

LATENCY-OPTIMISED DEPLOYMENT

Edge Computing
Solutions

CDN and edge compute deployment, IoT edge gateways, and latency-sensitive workload placement — moved closer to your users, benchmarked, not assumed.

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What's Included

Complete Edge Computing Coverage

From CDN caching to IoT edge gateways — every layer of edge deployment, placed where it actually helps.

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Edge Compute Deployment

Run workloads at the network edge — closer to users — instead of a single distant region.

✓ Cloudflare Workers / Workers KV deployment
✓ AWS Lambda@Edge & CloudFront Functions
✓ Azure Edge Zones evaluation
✓ Regional workload placement strategy
✓ Cold-start & latency benchmarking

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CDN & Content Delivery

Static and dynamic content served from the point of presence nearest your users.

✓ CDN architecture & cache strategy
✓ Cache invalidation & purge automation
✓ Origin shielding & failover design
✓ Image/asset optimisation at the edge
✓ Multi-CDN failover strategy

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IoT Edge Gateways

Process sensor and device data locally before it ever reaches the cloud.

✓ Edge gateway hardware & software selection
✓ Local data aggregation & filtering
✓ Store-and-forward for intermittent connectivity
✓ Device fleet management
✓ Edge-to-cloud sync design

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Latency-Sensitive Workload Placement

Decide, workload by workload, what actually needs to run at the edge versus centrally.

✓ Workload latency requirement analysis
✓ Edge vs regional vs central placement
✓ Data residency & compliance mapping
✓ Edge caching for API responses
✓ A/B testing edge vs origin performance

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Edge Security

The edge is still your infrastructure — it gets the same security discipline.

✓ WAF at the edge (Cloudflare, AWS)
✓ Bot mitigation & rate limiting
✓ TLS termination at edge nodes
✓ DDoS protection at the perimeter
✓ Edge access logging & audit

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Edge-to-Cloud Data Sync

Keep edge and central systems consistent without constant round-trips.

✓ Event-driven sync (Kafka at the core)
✓ Conflict resolution strategy
✓ Bandwidth-aware sync scheduling
✓ Offline-first design patterns
✓ Sync monitoring & failure alerting

Placement Decision

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Measure

Benchmark current latency by region

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Decide

Edge, regional, or central per workload

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Deploy

Functions, CDN rules, or IoT gateways

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Secure

WAF and DDoS protection at the perimeter

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Verify

Before/after latency confirmed, not assumed

Our Approach

Edge Where It Helps, Central Where It Doesn't

Edge computing adds real complexity. We only recommend it where the latency or resilience benefit is measurable.

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Benchmarked, Not Assumed

We measure current latency by user region before proposing an edge strategy, and we measure again after deployment to confirm it actually helped.

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Workload-by-Workload Placement

Not every request needs to run at the edge. We decide placement per workload — some at the edge, some regional, some central — rather than an all-or-nothing move.

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Compliance Mapped First

Processing data at edge locations in different jurisdictions has real data residency implications. We map this before choosing edge providers and regions, not after deployment.

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