Step 1: Use Cases, Constraints, Assumptions, Back-of-Envelope

Use cases

We'll scope to handle only the core flows that expose the bottlenecks; everything else is deferred.

• User searches — GET /search?q=..., cache lookup by normalized query hash, hit returns in self.cap: tail=self.tail; self._remove(tail); del self.map[tail.key] def _add_front(self,n): ... def _move_front(self,n): ... def _remove(self,n): ...

Shard routing

def cache_node_for(query: str, ring) -> str: h=hashlib.md5(query.lower().strip().encode()).hexdigest() return ring.get_node(h)

Single-flight miss

inflight={} def search_with_cache(q: str): key=hashlib.sha256(q.lower().encode()).hexdigest()[:32] val=r.get(key) if val: return json.loads(val) # single-flight if key in inflight: inflight[key].wait(); return json.loads(r.get(key)) ev=t