Compare Scenarios
Side-by-side comparison with decision path analysis. Every dimension traces back to topology, risk propagation, simulation, and advisor intelligence.
Select Scenarios to Compare
Left Scenario
AI / RAG
Multi-Tenant SaaS
Analytics
Financial Ledger
Read-Heavy
Multi-Tenant SaaS
Write-Heavy
Marketplace
Event-Driven
Financial Ledger
Realtime Collab
Realtime Collab
Financial Ledger
Write-Heavy
AI / RAG
Multi-Tenant SaaS
Event-Driven
Analytics
Read-Heavy
Realtime Collab
Search-Heavy
Event-Driven
Event-Driven
Marketplace
Write-Heavy
Right Scenario
AI / RAG
Multi-Tenant SaaS
Analytics
Financial Ledger
Read-Heavy
Multi-Tenant SaaS
Write-Heavy
Marketplace
Event-Driven
Financial Ledger
Realtime Collab
Realtime Collab
Financial Ledger
Write-Heavy
AI / RAG
Multi-Tenant SaaS
Event-Driven
Analytics
Read-Heavy
Realtime Collab
Search-Heavy
Event-Driven
Event-Driven
Marketplace
Write-Heavy
Topology at a Glance
Architecture Comparison
Realtime Collaborative Editor is both simpler and lower-risk than Two-Sided Marketplace Platform
Realtime Collaborative Editor is the simpler architecture. Realtime Collaborative Editor carries lower operational risk. They share 2 component(s). Two-Sided Marketplace Platform has 5 unique risk(s); Realtime Collaborative Editor has 1. Two-Sided Marketplace Platform requires lower team maturity to operate.
19
Nodes
0
Edges
5
Risks
2
Seeds
0
Strengths
5
Adv. Risks
5
Nodes
2
Edges
1
Risks
1
Seeds
1
Strengths
1
Adv. Risks
Comparison Dimensions
Complexity
Two-Sided Marketplace Platform
expert complexity, 19 nodes, 0 edges, 5 risks, 2 simulation seeds
Realtime Collaborative Editor
expert complexity, 5 nodes, 2 edges, 1 risks, 1 simulation seeds
Realtime Collaborative Editor is simpler: expert operational complexity with 5 topology nodes vs 19 for Two-Sided Marketplace Platform.
Operational Risk
Two-Sided Marketplace Platform
5 risks (top: high), 5 high/critical, 1 confirmed by simulation
Realtime Collaborative Editor
1 risks (top: high), 1 high/critical, 1 confirmed by simulation
Realtime Collaborative Editor has lower operational risk: weighted severity score 4 vs 20 (1 vs 1 simulation-confirmed).
Scalability
Two-Sided Marketplace Platform
4 scaling thresholds, 3 migration paths, 6 advisor scaling signals
Realtime Collaborative Editor
3 scaling thresholds, 2 migration paths, 6 advisor scaling signals
Two-Sided Marketplace Platform has more defined scaling paths: 4 thresholds and 3 migration paths.
Operational Maturity
Two-Sided Marketplace Platform
Advisor assessment: Advanced; recommended team: Platform Engineering Team; 15 operational requirements
Realtime Collaborative Editor
Advisor assessment: Expert Only; recommended team: Enterprise Architecture Team; 6 operational requirements
Two-Sided Marketplace Platform requires lower team maturity (Advanced) vs Expert Only for Realtime Collaborative Editor.
Observability
Two-Sided Marketplace Platform
5 watched metrics, 7 observability recommendations, 2 simulation seeds
Realtime Collaborative Editor
4 watched metrics, 2 observability recommendations, 1 simulation seeds
Realtime Collaborative Editor has lower observability burden: 4 watched metrics vs 5.
Generator Readiness
Two-Sided Marketplace Platform
generator relevance documented; topology generation relevance noted; simulation relevance noted; 2 seeds with generator notes
Realtime Collaborative Editor
generator relevance documented; topology generation relevance noted; simulation relevance noted; 1 seeds with generator notes
Two-Sided Marketplace Platform has more documented generator readiness signals. Note: this is still preliminary.
Architecture Components
Only in Two-Sided Marketplace Platform (17)
Only in Realtime Collaborative Editor (3)
Operational Risks
Only in Two-Sided Marketplace Platform (5)
Only in Realtime Collaborative Editor (1)
Consistency Guarantees
Neither scenario has a recorded consistency-guarantee claim.
Neither scenario has recorded a consistency-guarantee claim; no guarantee comparison is possible from the data on record.
Tradeoff Summary
Complexity vs Risk
Two-Sided Marketplace Platform has expert complexity. Realtime Collaborative Editor has expert complexity. Simpler systems often carry different (not necessarily fewer) risks.
Two-Sided Marketplace Platform
Two-Sided Marketplace Platform: 5 risks (top: high), 5 high/critical, 1 confirmed by simulation
Realtime Collaborative Editor
Realtime Collaborative Editor: 1 risks (top: high), 1 high/critical, 1 confirmed by simulation
Scaling Path
Two-Sided Marketplace Platform offers 4 defined scaling thresholds. Realtime Collaborative Editor offers 3. More defined paths means clearer evolution steps but also more anticipated growth.
Two-Sided Marketplace Platform
4 scaling thresholds, 3 migration paths, 6 advisor scaling signals
Realtime Collaborative Editor
3 scaling thresholds, 2 migration paths, 6 advisor scaling signals
Team Maturity Requirement
Two-Sided Marketplace Platform can be operated by a less experienced team. Realtime Collaborative Editor requires deeper operational expertise.
Two-Sided Marketplace Platform
Advisor assessment: Advanced; recommended team: Platform Engineering Team; 15 operational requirements
Realtime Collaborative Editor
Advisor assessment: Expert Only; recommended team: Enterprise Architecture Team; 6 operational requirements
Event-Driven vs Synchronous Processing
Two-Sided Marketplace Platform uses event stream infrastructure (Kafka/Kinesis), enabling decoupled async processing. Realtime Collaborative Editor does not, keeping the stack simpler but less decoupled.
Two-Sided Marketplace Platform
Event stream: async decoupling, consumer lag risk, higher ops burden
Realtime Collaborative Editor
No event stream: simpler stack, synchronous dependencies
Architecture Strengths vs Risks Balance
The advisor identifies strengths and risks grounded in knowledge relationships. A higher strengths-to-risks ratio suggests better mitigation coverage in the current topology.
Two-Sided Marketplace Platform
0 strengths, 5 risks
Realtime Collaborative Editor
1 strengths, 1 risks
Migration Considerations
Migration Step 1
Two-Sided Marketplace Platform
Monolithic marketplace application with single database → Event-driven marketplace with Kafka + saga-based checkout flow
Realtime Collaborative Editor
Short-polling API with version-based conflict detection → WebSocket + Redis pub/sub live propagation
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Checkout failures from payment provider unavailability causi'. Realtime Collaborative Editor: triggered by 'User-visible edit conflicts > 5% of sessions; poll interval '.
Migration Step 2
Two-Sided Marketplace Platform
PostgreSQL full-text search for listing discovery → Elasticsearch for listing search with CDC-based indexing
Realtime Collaborative Editor
Last-write-wins conflict resolution → Operational transformation (OT) or CRDT-based conflict resolution
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Listing search p99 > 1s; faceted navigation (category + pric'. Realtime Collaborative Editor: triggered by 'Data loss complaints from users editing simultaneously; conf'.
Migration Step 3
Two-Sided Marketplace Platform
Monolithic PostgreSQL serving all domain writes → Domain-separated databases with event-based cross-domain data propagation
Realtime Collaborative Editor
No further migration step defined
Two-Sided Marketplace Platform has a defined migration; Realtime Collaborative Editor does not at this stage.
Advisor Notes
Strength: A connection pool bounds the total database connections an application can open, preventing connection storms during traffic…
A connection pool bounds the total database connections an application can open, preventing connection storms during traffic spikes and protecting the database server from exceeding its connection limit. Key trade-off: Pooler becomes a new single point of failure if not replicated. Operational note: PgBouncer transaction-mode pooling is most effective for stateless APIs. Evidence: PgBouncer reduces PostgreSQL connections by 10–100x in typical deployments.
Risk (high): Hot Partition
One partition (a database shard, a Kafka topic partition, a Redis hash slot) receives traffic so far above its peers that it saturates while the others sit idle. Aggregate capacity looks healthy, but the hot partition throttles or lags, and everything routed to it degrades. The cause is skew in how keys map to partitions, and the fix depends on whether the skew is spread across many keys or concentrated in one.
Risk (high): Connection Pool Exhaustion
All database connections in the pool are in use; new requests queue and then time out, causing cascading latency and errors across all dependent services.
Shared Operational Requirements
Both scenarios require: Cache sizing and eviction policy configuration, PostgreSQL: scenario includes high_write_throughput or write_heavy workload, Redis: scenario has read_heavy workload with high cache miss risk.
Supporting Evidence · 14 items
Coverage Warnings
- ⚠Two-Sided Marketplace Platform: fewer than 2 architectural strengths identified. the risk/complexity dimensions are present but the strength analysis is thin. Consider enriching the relationship YAMLs referenced by this scenario to improve coverage.
- ⚠Realtime Collaborative Editor: fewer than 2 architectural strengths identified. the risk/complexity dimensions are present but the strength analysis is thin. Consider enriching the relationship YAMLs referenced by this scenario to improve coverage.
- ⚠Realtime Collaborative Editor: fewer than 2 operational risks identified. the risk comparison dimension will reflect low advisor coverage, not a low-risk architecture.
Limitations
- ·Comparison grounded in YAML knowledge only. Not measured from any production system.
- ·Winner assessments are deterministic heuristics, not absolute recommendations. Context, team preferences, and workload specifics may change the conclusion.
- ·2 seed type(s) across both scenarios do not have execution previews. Risk confirmation for those types is unavailable.
- ·Neither scenario has a recorded consistency-guarantee claim. Guarantee comparison is uninformative for this pair, not silently empty.
Realtime Collaborative Editor is the recommended starting point over Two-Sided Marketplace Platform
Realtime Collaborative Editor leads on 3 weighted dimension(s): Complexity, Operational Risk, Observability. Weighted score: 4.5 vs 3.0 for Two-Sided Marketplace Platform.
Decision Intelligence
Architecture Decision Path
Structured reasoning for choosing between Two-Sided Marketplace Platform and Realtime Collaborative Editor. Every condition and trigger traces back to comparison dimensions, advisor insights, and topology evidence.
Realtime Collaborative Editor is the recommended starting point over Two-Sided Marketplace Platform
Realtime Collaborative Editor leads on 3 weighted dimension(s): Complexity, Operational Risk, Observability. Weighted score: 4.5 vs 3.0 for Two-Sided Marketplace Platform. The architectures share 2 component(s), reducing migration cost if you switch later. Realtime Collaborative Editor is the operationally simpler choice.
Where to Start
Start with Realtime Collaborative Editor
RightRealtime Collaborative Editor has lower operational complexity. Starting here reduces risk and cognitive load. Migrate to the more capable architecture only when you hit concrete scaling or feature limits.
Complexity: expert complexity, 5 nodes, 2 edges, 1 risks, 1 simulation seeds
Migrate when:
- Server memory growing with active connections; file descriptor limits approached; new WebSocket connections refused → Increase file descriptor limits (ulimit); move to dedicated WebSocket server tier; implement connection multiplexing (multiple documents per connection where safe)
- Consecutive writes to the same document causing lock contention; write latency rising; auto-save batching queue depth increasing → Move to operational transformation or CRDT-based conflict resolution; batch writes and resolve conflicts in-process before database commit; consider append-only event log for document operations
- Redis memory growing; high number of active pub/sub channels per Redis instance; SUBSCRIBE/UNSUBSCRIBE operations becoming significant overhead → Shard Redis pub/sub by document range; implement channel expiry; consider dedicated messaging tier (e.g. Ably, Pusher) for very high session counts
Decision Flow
Does your team have the operational maturity to run Realtime Collaborative Editor (expert only rating)?
If Yes
Your team can operate Realtime Collaborative Editor. Continue to Step 2 to refine based on risk tolerance and workload fit.
If No
Prefer the lower-maturity option: left scenario.
Is operational stability and minimising production risk your primary concern over feature richness or scalability ceiling?
If Yes
Prefer Realtime Collaborative Editor: it carries lower operational risk weight per the advisor's assessment.
If No
Proceed to Step 3 to evaluate based on scaling requirements.
Do you expect your load to reach: Redis cache miss spike visible in monitoring; PostgreSQL query rate spiking for listing reads despite stable write volume; p99 listing API latency > 500ms during traffic spike events ?
If Yes
Left scenario has more defined scaling evolution paths for this growth pattern.
If No
If you don't expect to hit these scaling signals soon, prefer the simpler architecture and re-evaluate when load patterns become clearer.
Does your team already operate an event streaming platform (e.g., Kafka, Kinesis, Pub/Sub) in production?
If Yes
Two-Sided Marketplace Platform builds on event stream infrastructure. Your existing platform reduces the adoption risk.
If No
If you don't have an event streaming platform, the other scenario avoids adding that infrastructure dependency. Evaluate whether the async decoupling benefit justifies the new ops burden.
Is operational simplicity (fewer moving parts, easier debugging, lower ops burden) more important than maximum architectural capability?
If Yes
Realtime Collaborative Editor is the simpler choice: Realtime Collaborative Editor is simpler: expert operational complexity with 5 topology nodes vs 19 for Two-Sided Marketplace Platform.
If No
If capability and scalability ceiling matter more than simplicity, evaluate the higher-complexity scenario against your specific load model.
When to Choose Each Scenario
Two-Sided Marketplace Platform
LeftWhen you need well-defined scaling thresholds and migration paths
HighTwo-Sided Marketplace Platform has more documented scaling evolution steps (4 thresholds, 3 migration paths).
When your team has limited operational maturity
CriticalTwo-Sided Marketplace Platform is rated advanced , accessible for teams without deep platform expertise.
When your system requires decoupled async event processing
HighTwo-Sided Marketplace Platform includes event stream infrastructure (e.g., Kafka/Kinesis), enabling async decoupling between producers and consumers.
Realtime Collaborative Editor
RightWhen operational simplicity is a top priority
HighRealtime Collaborative Editor has lower operational complexity: fewer moving parts, easier to reason about and debug.
When stability and predictability matter most
CriticalRealtime Collaborative Editor carries lower overall risk weight per the advisor's assessment.
When you want to minimise monitoring setup overhead
ModerateRealtime Collaborative Editor has a lower observability burden: fewer watched metrics and monitoring targets.
When your architecture benefits from: a connection pool bounds the total database connections an application can open, preventing connection storms during traffic…
ModerateA connection pool bounds the total database connections an application can open, preventing connection storms during traffic spikes and protecting the database server from exceeding its connection limit. Key trade-off: Pooler becomes a new single point of failure if not replicated. Operational note: PgBouncer transaction-mode pooling is most effective for stateless APIs. Evidence: PgBouncer reduces PostgreSQL connections by 10–100x in typical deployments.
When to Avoid Each Scenario
Two-Sided Marketplace Platform
LeftWhen your team cannot mitigate: hot partition
HighThis architecture is significantly exposed to Hot Partition. One partition (a database shard, a Kafka topic partition, a Redis hash slot) receives traffic so far above its peers that it saturates while the others sit idle. Aggregate capacity looks healthy, but the hot partition throttles or lags, and everything routed to it degrades. The cause is skew in how keys map to partitions, and the fix depends on whether the skew is spread across many keys or concentrated in one.
When your team cannot mitigate: cascading failure
HighThis architecture is significantly exposed to Cascading Failure. A failure or degradation in one service causes increased load, held resources, or error propagation in its callers, which in turn degrade their callers, until the failure front propagates through the entire dependency graph and brings down services with no direct dependency on the original failure point.
When your team is early-stage or solo
HighTwo-Sided Marketplace Platform is rated 'advanced'. It requires experienced backend engineers or platform tooling to operate reliably at scale.
When you expect rapid growth within the next 12–18 months
ModerateThe advisor identifies 9 predicted bottlenecks for Two-Sided Marketplace Platform. Rapid growth will surface these limitations quickly.
Realtime Collaborative Editor
RightWhen your team cannot mitigate: connection pool exhaustion
HighThis architecture is significantly exposed to Connection Pool Exhaustion. All database connections in the pool are in use; new requests queue and then time out, causing cascading latency and errors across all dependent services.
When your team does not have platform engineering expertise
CriticalRealtime Collaborative Editor is rated 'expert only'. It requires deep operational expertise to run safely. Operating it without the right team leads to incidents.
When you expect rapid growth within the next 12–18 months
ModerateThe advisor identifies 3 predicted bottlenecks for Realtime Collaborative Editor. Rapid growth will surface these limitations quickly.
Team Fit
Solo developer or small startup
LeftTwo-Sided Marketplace Platform is more accessible for small teams. Fewer operational moving parts reduces on-call burden.
- ↳Validate that the simpler architecture can handle your projected load before committing.
Small product team (2–6 engineers)
LeftTwo-Sided Marketplace Platform suits small teams that need to move fast without deep platform tooling investment.
- ↳Consider Realtime Collaborative Editor only if your workload pattern specifically requires it.
Experienced backend team
DependsAn experienced team can operate either architecture. Choose based on workload fit, not team capability.
- ↳Prioritise alignment with existing infrastructure and tooling.
- ↳Realtime Collaborative Editor may require additional runbook coverage and alerting investment.
Platform engineering team or SRE-equipped organisation
RightA platform team can safely operate Realtime Collaborative Editor and will benefit from its more advanced scaling characteristics.
- ↳Ensure observability and alerting are configured before launch.
Migration Triggers
Migration Step 1
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Checkout failures from payment provider unavailability causi'. Realtime Collaborative Editor: triggered by 'User-visible edit conflicts > 5% of sessions; poll interval '.
Migration Step 2
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Listing search p99 > 1s; faceted navigation (category + pric'. Realtime Collaborative Editor: triggered by 'Data loss complaints from users editing simultaneously; conf'.
Migration Step 3
Two-Sided Marketplace Platform has a defined migration; Realtime Collaborative Editor does not at this stage.
Redis cache miss spike visible in monitoring; PostgreSQL query rate spiking for listing reads despite stable write volume; p99 listing API latency > 500ms during traffic spike events
Tier 1: Viral Listing Thundering Herd: Cache TTL expiry on hot listings during peak traffic: all concurrent requests bypass cache simultaneously. Recommended evolution: Implement staggered TTL jitter on listing cache entries; use probabilistic early refresh (refresh before TTL expiry when remaining TTL < 20% and request rate is high); implement single-flight/request coalescing at the application layer to collapse concurrent cache misses into a single database read .
Saga compensation events appearing in order event log; checkout p99 > 2s; pg_locks showing contended rows on inventory_reservations table; idempotency key conflicts increasing in payment service logs
Tier 2: Checkout Saga Contention: Concurrent checkout transactions competing for the same inventory rows; saga timeout thresholds too aggressive. Recommended evolution: Increase inventory reservation table partition count; tune saga step timeout to 2x the observed p99 for each step under load; implement a per-listing checkout serialization queue to prevent N concurrent sagas competing for the same inventory .
Server memory growing with active connections; file descriptor limits approached; new WebSocket connections refused
Tier 1: WebSocket Connection Ceiling: WebSocket server process connection limit or OS file descriptor ceiling. Recommended evolution: Increase file descriptor limits (ulimit); move to dedicated WebSocket server tier; implement connection multiplexing (multiple documents per connection where safe) .
Consecutive writes to the same document causing lock contention; write latency rising; auto-save batching queue depth increasing
Tier 2: Database Write Contention: High-frequency auto-save operations conflicting at the document row level; row-level locking under concurrent user edits . Recommended evolution: Move to operational transformation or CRDT-based conflict resolution; batch writes and resolve conflicts in-process before database commit; consider append-only event log for document operations .
Readiness Requirements
Cache sizing and eviction policy configuration
BothRedis or equivalent cache requires correct maxmemory configuration, eviction policy selection (allkeys-lru is common), and cold-start warming strategy after restarts.
PostgreSQL: scenario includes high_write_throughput or write_heavy workload
BothDeploy PgBouncer in transaction-mode pooling before relying on vertical scaling
Required maturity: mid_level
Redis: scenario has read_heavy workload with high cache miss risk
BothImplement cache stampede protection (probabilistic early expiry or locking) to prevent thundering herd on cold start
Required maturity: junior
Redis: scenario relies on Redis for data that cannot be re-derived
BothRedis is not a durable store: add persistence layer or treat Redis as expendable cache only
Required maturity: junior
Runbooks and alerting for high-severity risks
Both5 high-severity risks identified. Each requires a documented runbook, alerting threshold, and on-call response procedure before running in production.
Apache Kafka: scenario has team_maturity below senior
LeftKafka operational complexity requires dedicated expertise: consider MSK or Confluent Cloud to reduce ops burden
Required maturity: senior
Apache Kafka: scenario uses Kafka for event streaming or CDC
LeftSet min.insync.replicas=2 with acks=all; monitor consumer lag as primary health signal
Required maturity: senior
Elasticsearch: scenario has full_text_search or log_analytics workload
LeftConfigure ILM policies from day one to prevent shard explosion as data grows
Required maturity: senior
Elasticsearch: scenario uses Elasticsearch as a primary datastore
LeftElasticsearch is a search index, not a source of truth: add a durable primary store and sync to ES
Required maturity: senior
Elasticsearch: scenario uses dynamic mappings on high-cardinality fields
LeftDefine explicit index mappings: dynamic mapping on high-cardinality fields causes mapping explosions and cluster instability
Required maturity: senior
Event stream operations expertise
LeftThis architecture includes event stream infrastructure (Kafka, Kinesis, or similar). Operations requires consumer group management, partition assignment, dead-letter handling, and lag monitoring.
Required maturity: platform_engineering_team
Minimum team maturity: Platform Engineering Team
LeftThis scenario has expert operational complexity. It is recommended for Platform Engineering Team teams or higher.
Required maturity: platform_engineering_team
RabbitMQ: scenario has high_throughput_writes exceeding 50k messages/second
LeftRabbitMQ throughput ceiling may be insufficient: evaluate Kafka for sustained high-throughput event streams
Required maturity: mid_level
RabbitMQ: scenario requires event replay or consumer catch-up from historical messages
LeftRabbitMQ deletes acknowledged messages: use Kafka for replay-capable event streaming
Required maturity: mid_level
RabbitMQ: scenario uses classic mirrored queues for HA
LeftMigrate to quorum queues: classic mirrored queues have known split-brain behavior under network partition
Required maturity: mid_level
Minimum team maturity: Enterprise Architecture Team
RightThis scenario has expert operational complexity. It is recommended for Enterprise Architecture Team teams or higher.
Required maturity: enterprise_architecture_team
Generator Constraints
Two-Sided Marketplace Platform
LeftGenerator relevance documented but not yet production-ready.
For marketplace product briefs, the generator must produce the full event-driven composition: API gateway → domain services → outbox → Kafka → downstream consumers. Saga orchestration templates for the checkout flow (create_order → reserve_inventory → charge_payment → notify_seller) must be generated with explicit compensation paths. The notification subsystem (RabbitMQ + dead-letter queue) must be generated as a separate deployable unit with its own operational SLA.
Realtime Collaborative Editor
RightGenerator relevance documented but not yet production-ready.
When generating architectures for collaborative editing or presence-aware applications, the WebSocket + Redis pub/sub + PostgreSQL composition should be presented as the baseline. CRDT/OT conflict resolution should be surfaced as a required upgrade path before launch in production collaborative contexts. The knowledge base currently lacks detailed CRDT/OT pattern entries: these should be added as the knowledge base expands.
Supporting Evidence
| Type | Reference | Explanation |
|---|---|---|
| Comparison | compare_marketplace_platform_vs_realtime_collaborative_editor | Full comparison of Two-Sided Marketplace Platform vs Realtime Collaborative Editor: 6 dimensions, 2 shared components, 0 shared risks. |
| Advisor | advisor_marketplace_platform | Advisor for Two-Sided Marketplace Platform: 0 strengths, 5 risks, maturity: advanced. |
| Advisor | advisor_realtime_collaborative_editor | Advisor for Realtime Collaborative Editor: 1 strengths, 1 risks, maturity: expert_only. |
| Scenario | marketplace_platform | Scenario 'Two-Sided Marketplace Platform': 4 scaling thresholds, 3 migration paths, complexity: expert. |
| Scenario | realtime_collaborative_editor | Scenario 'Realtime Collaborative Editor': 3 scaling thresholds, 2 migration paths, complexity: expert. |
| Risk Path | prop_workload_profile_marketplace_mixed_workload_risk_hot_partition | Marketplace Mixed → Hot Partition |
| Risk Path | prop_technology_profile_redis_risk_thundering_herd | Redis → Thundering Herd (Cache Stampede) |
| Risk Path | prop_technology_profile_redis_risk_connection_exhaustion | Redis → Connection Pool Exhaustion |
| Risk Path | prop_workload_profile_marketplace_mixed_workload_risk_hot_partition | Referenced by the operational risk comparison dimension. |
| Risk Path | prop_technology_profile_redis_risk_thundering_herd | Referenced by the operational risk comparison dimension. |
Limitations
- ·Decision guidance is grounded in YAML knowledge only. Not measured from any production system.
- ·Recommendations are deterministic heuristics based on structured knowledge. Your specific workload, team profile, and business context may lead to different conclusions.
- ·Generator constraints are preliminary. No scenario should be treated as production generation-ready at this stage.
Comparison complete
Profile, topology, simulation, advisor, comparison, and decision path are ready. Your architecture decision is grounded in structured knowledge and deterministic reasoning.