Error: expect(received).toContain(expected) // indexOf

Expected substring: "Admin was here"
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Concurrent modifications are detected and merged by specialized functions in the coordination layer. The protocol\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Circuit breakers protect downstream services from cascading failures during periods of degradation. The system processes data through multiple layers of abstraction ensuring consistency across all nodes. Reliability is maintained by distributed components that handle requests efficiently within the network. Each architecture layer guarantees strict ordering for operations that modify shared state. Synchronization protocols use vector clocks to track causal dependencies between updates. Optimistic replication propagates changes using conflict resolution based on deterministic rules. Concurrent modifications are detected and merged by specialized functions in the coordination layer. The protocol maintains eventual consistency while minimizing latency for participating clients. State transitions are\",\"dropCap\":false},\"innerBlocks\":[]}]},{\"name\":\"core/heading\",\"attributes\":{\"content\":\"Future Work\",\"level\":3},\"innerBlocks\":[]},{\"name\":\"core/list\",\"attributes\":{\"ordered\":false,\"values\":\"\"},\"innerBlocks\":[{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"The system processes data through multiple layers of abstraction ensuring consistency across all nodes. Reliability is maintained by distributed components that handle requests efficiently within\"},\"innerBlocks\":[]},{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"Reliability is maintained by distributed components that handle requests efficiently within the network. Each architecture layer guarantees strict ordering for operations that modify shared state.\"},\"innerBlocks\":[]},{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"Each architecture layer guarantees strict ordering for operations that modify shared state. Synchronization protocols use vector clocks to track causal dependencies between updates. Optimistic replication\"},\"innerBlocks\":[]},{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"Synchronization protocols use vector clocks to track causal dependencies between updates. Optimistic replication propagates changes using conflict resolution based on deterministic rules. Concurrent modifications are\"},\"innerBlocks\":[]},{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"Optimistic replication propagates changes using conflict resolution based on deterministic rules. Concurrent modifications are detected and merged by specialized functions in the coordination layer. The\"},\"innerBlocks\":[]},{\"name\":\"core/list-item\",\"attributes\":{\"content\":\"Concurrent modifications are detected and merged by specialized functions in the coordination layer. The protocol maintains eventual consistency while minimizing latency for participating clients. State\"},\"innerBlocks\":[]}]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"The protocol maintains eventual consistency while minimizing latency for participating clients. State transitions are validated against invariants before being committed to the distributed log. Recovery mechanisms restore consistency after partial failures using checkpointed snapshots. Performance monitoring tracks throughput and latency metrics across all participating services. The coordination layer batches updates to reduce network overhead during peak traffic periods. Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"State transitions are validated against invariants before being committed to the distributed log. Recovery mechanisms restore consistency after partial failures using checkpointed snapshots. Performance monitoring tracks throughput and latency metrics across all participating services. The coordination layer batches updates to reduce network overhead during peak traffic periods. Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Recovery mechanisms restore consistency after partial failures using checkpointed snapshots. Performance monitoring tracks throughput and latency metrics across all participating services. The coordination layer batches updates to reduce network overhead during peak traffic periods. Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures all changes as immutable facts appended to a persistent ordered log. Materialized views\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/heading\",\"attributes\":{\"content\":\"Conclusion\",\"level\":2},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Admin typed this paragraph in Phase 2.\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Performance monitoring tracks throughput and latency metrics across all participating services. The coordination layer batches updates to reduce network overhead during peak traffic periods. Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures all changes as immutable facts appended to a persistent ordered log. Materialized views are rebuilt from the event log to provide optimized read\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"The coordination layer batches updates to reduce network overhead during peak traffic periods. Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures all changes as immutable facts appended to a persistent ordered log. Materialized views are rebuilt from the event log to provide optimized read access patterns. Schema evolution is managed through compatible transformations that preserve\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Load balancing distributes requests across available replicas based on current capacity estimates. Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures all changes as immutable facts appended to a persistent ordered log. Materialized views are rebuilt from the event log to provide optimized read access patterns. Schema evolution is managed through compatible transformations that preserve backward compatibility. Rate limiting prevents individual clients from consuming disproportionate amounts of shared\",\"dropCap\":false},\"innerBlocks\":[]},{\"name\":\"core/quote\",\"attributes\":{\"value\":\"\",\"citation\":\"Project Lead\"},\"innerBlocks\":[{\"name\":\"core/paragraph\",\"attributes\":{\"content\":\"Data partitioning strategies ensure that related records are co-located for efficient queries. The consensus algorithm tolerates up to one third of nodes failing without losing availability. Background compaction processes reclaim storage space from obsolete versions of modified records. Event sourcing captures all changes as immutable facts appended to a persistent ordered log. Materialized views are rebuilt from the event log to provide optimized read access patterns. Schema evolution is managed through compatible transformations that preserve backward compatibility. Rate limiting prevents\",\"dropCap\":false},\"innerBlocks\":[]}]}]"

Call Log:
- Timeout 10000ms exceeded while waiting on the predicate
    at /home/runner/work/gutenberg/gutenberg/test/e2e/specs/editor/collaboration/collaboration-stress.spec.ts:456:8