event-exporter-v2: shared-nothing HA re-architecture

[erain]

Summary

Re-architecture of the event-exporter as a new standalone module (event-exporter-v2/) for horizontal scalability and high availability. The original event-exporter/ is untouched.

• Shared-nothing consistent hashing — each pod watches all events, only sends events it "owns" via xxhash(namespace/name) % N
• Peer discovery via headless Service Endpoints informer — no leader election, no gRPC, no external dependencies
• Deterministic InsertId for Cloud Logging deduplication during scaling transitions
• Tuned sink defaults — buffer 500 (was 100), concurrency 25 (was 10), flush 2s (was 5s)
• Exponential backoff with jitter replacing fixed 10s retry in Cloud Logging writer
• HPA-compatible Deployment with readiness probe, PDB, and custom metrics
• Fully backward compatible — same binary runs in single-pod mode when --headless-service-name is empty

Design

Architecture

  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐
  │   Pod 0     │  │   Pod 1     │  │   Pod 2     │
  │             │  │             │  │             │
  │ ┌─────────┐ │  │ ┌─────────┐ │  │ ┌─────────┐ │
  │ │ Watcher │ │  │ │ Watcher │ │  │ │ Watcher │ │
  │ │(all evts)│ │  │ │(all evts)│ │  │ │(all evts)│ │
  │ └────┬────┘ │  │ └────┬────┘ │  │ └────┬────┘ │
  │      │      │  │      │      │  │      │      │
  │ hash%3==0?  │  │ hash%3==1?  │  │ hash%3==2?  │
  │   ┌──┴──┐   │  │   ┌──┴──┐   │  │   ┌──┴──┐   │
  │   │Sink │   │  │   │Sink │   │  │   │Sink │   │
  │   │~1/3 │   │  │   │~1/3 │   │  │   │~1/3 │   │
  │   └──┬──┘   │  │   └──┬──┘   │  │   └──┬──┘   │
  └──────┼──────┘  └──────┼──────┘  └──────┼──────┘
         │                │                │
         └────────────────┼────────────────┘
                          ▼
                 GCP Cloud Logging

How consistent hashing works

1. Each pod discovers peers via a headless Service's Endpoints informer
2. Peer IPs are sorted lexicographically — all pods produce the same ordering
3. Each pod identifies itself by POD_IP (Downward API) and finds its index in the sorted list
4. For each event: owner = xxhash(namespace/name) % len(peers) — if owner == myIndex, process it
5. Grace period: if a pod isn't in Endpoints yet, it processes ALL events (prevents gaps)
6. Deduplication: deterministic InsertId = namespace/name/resourceVersion handles brief overlaps during scaling

Why shared-nothing over leader-worker

Dimension	Shared-Nothing (chosen)	Leader-Worker
Complexity	Low — no gRPC, no leader election	High — gRPC service, election, role transitions
SPOF	None — all pods are equal	Leader is a bottleneck
HPA	Natural — add more pods	Requires separate scaling for leader vs workers
API server impact	N watchers (negligible for N<10)	1 watcher (minimal)
Memory per pod	Full event cache per pod	Only leader needs caches

Scaling behavior

• Scale up (2→3): new pod appears in Endpoints, all pods recompute N=3. Brief overlap window (<1s) produces duplicates deduplicated by InsertId
• Scale down (3→2): departing pod drains buffers on SIGTERM. Remaining pods absorb orphaned partition
• Pod crash: remaining pods see updated Endpoints, absorb crashed pod's partition. Resync (1min) recovers any in-flight events
• Throughput: ~200-500 events/sec per pod. N pods = N × throughput

New files (vs original event-exporter)

File	Purpose
peerdiscovery/discovery.go	Endpoints informer, sorted peer list, IsOwner() hash check
peerdiscovery/discovery_test.go	Tests: determinism, distribution, grace period, rebalancing
peerdiscovery/metrics.go	event_exporter_peer_count, event_exporter_peer_updates_total
example/event-exporter-ha.yaml	HA deployment: headless Service, HPA, PDB, readiness probe

Modified files (vs original event-exporter)

File	Change
main.go	--headless-service-name flag, PeerDiscovery init, /readyz endpoint
event_exporter.go	PeerDiscovery as third concurrent goroutine
sinks/stackdriver/sink.go	Hash filtering in OnAdd/OnUpdate (before serialization), queue depth reporting
sinks/stackdriver/sink_factory.go	Exported type, CreateNewWithOwnerChecker method
sinks/stackdriver/sink_config.go	Tuned defaults: buffer 500, concurrency 25, flush 2s
sinks/stackdriver/writer.go	Exponential backoff (1s→60s, 2x, 20% jitter)
sinks/stackdriver/log_entry_factory.go	Deterministic InsertId
sinks/stackdriver/metrics.go	events_dropped_by_hash_total, events_owned_total, queue_depth

New Prometheus metrics

Metric	Type	Purpose
event_exporter_peer_count	Gauge	Current number of peer pods
event_exporter_peer_updates_total	Counter	Peer list update events
event_exporter_events_dropped_by_hash_total	Counter	Events skipped (owned by another pod)
event_exporter_events_owned_total	Counter	Events this pod processes
event_exporter_queue_depth	Gauge	Log entry channel depth (HPA metric)

Status

This is an initial working implementation. Known TODOs:

• End-to-end tests with multi-pod deployment
• Load testing at scale (>1000 events/sec)
• Validate Cloud Logging InsertId deduplication behavior under rebalancing
• Tune HPA thresholds based on real-world metrics
• Update Makefile/Dockerfile for v2 build paths
• Consider EndpointSlice API as future replacement for Endpoints

Test plan

• Unit tests pass: go test ./... (peerdiscovery, sinks, watchers, podlabels)
• go vet ./... clean
• go build ./... succeeds
• Original event-exporter/ untouched and builds/tests independently
• Deploy in test GKE cluster with 3 replicas
• Verify all events appear in Cloud Logging with no gaps
• Scale up/down and verify no event loss
• Kill a pod and verify partition recovery

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