DNS and Traffic Routing in the Cloud: From Resolver to Anycast
Before any request reaches a server, DNS decides where it goes. We trace a full resolution from stub resolver to authoritative name server, then show how cloud providers layer on top: anycast for CDN entry, geo and latency routing policies, weighted records, and the handoff from DNS to the load balancer's instance pool. We examine how TTLs determine failover speed, why caching hides your changes, and what health-check-driven record removal actually costs. The video closes with a realistic global deployment — edge cache, origin, multi-region fallback — and shows how each layer decides where the next request lands.
Topics covered:
- The resolution path: resolver to authoritative
- Anycast, geo routing, and weighted records
- TTLs, caching, and failover timing
- Load balancer handoff and health-check mechanics
Related articles
Multi-Region Deployments and Latency
Speed-of-light RTT floors, active-passive versus active-active architectures, DNS-based routing, and replication lag — the real tradeoffs of running in multiple regions.
Containers Aren't Lightweight VMs
Namespaces, cgroups, seccomp, and the real isolation boundaries — what containers actually isolate and what they don't.
Vendor Lock-In Is a Cost Model
Egress fees, control-plane APIs, and data gravity — how cloud providers price switching costs, and how to compute the real cost of a migration.
More in Cloud & Infrastructure
Edge Computing Explained: Where Compute Actually Sits
What edge computing actually is — the compute tiers from device to far edge to cloud, latency and bandwidth budgets, and which workloads genuinely benefit.
DetailsContainer Orchestration Basics: API Server, Controllers, and Scheduler
Container orchestration from first principles — what the API server, controller manager, and scheduler actually do, with Kubernetes as the working example.
DetailsThe Cost of Distributed Systems: Coordination, Consistency, and Failure
What distributed systems actually cost — coordination, consistency, and failure taxes — quantified with quorum math, tail latency, and retry-storm dynamics.
DetailsMulti-Region Architecture: Active-Active, Failover, and Replication
The real mechanics of multi-region deployments — where writes land, how replication propagates, what failover flips, and the latency math that constrains every design.
DetailsObject Storage Under the Hood: PUT, GET, and Erasure Coding
What happens inside an object store — the PUT and GET paths, metadata partitions, erasure coding, and why object storage is eventually consistent.
DetailsAutoscaling Explained: The Controller Loop Behind Horizontal Scaling
How autoscaling actually works — the metrics window, desired-replica calculation, stabilization, and why naive CPU-based scaling oscillates under real load.
DetailsServerless Cold Starts, Measured: Where the Latency Actually Goes
Measured cold-start latency across Lambda, Cloud Functions, and container runtimes — what actually takes time and which optimizations genuinely reduce it.
DetailsKubernetes Scheduling Visualized: The Filter-Score Pipeline
What the Kubernetes scheduler actually does — how pending Pods become assigned to Nodes, the filter-then-score pipeline, and how taints and affinity shape placement.
DetailsContainer Images Explained: Layers, Manifests, and Digests
How container images are actually built and run — layers, manifests, content digests, and what the runtime does at pull and run time.
DetailsDepth, delivered weekly
One technical dispatch a week — articles and episode notes before they go public.
One technical dispatch per week. No noise.