For backend engineers & tech leads
Architecture decision reviews for backend systems.
Know what breaks before you build it.
Before your team commits to a stack like Postgres + Redis + Kafka, see the verdict, first failure path, risk evidence, and next action , a decision report you can trace, defend, and paste into a design doc.
Read-Heavy SaaS API
Fully modeled scenario
Live report excerpt
Verdict
This is a moderate rubric match with no serious readiness gaps and no simpler alternative of comparable fit; the recommended architecture is appropriately scoped.
First failure path
Replication Lag Cascade, Write burst that exceeds the replica's serial WAL apply rate; first signal: Replication Lag
Blast radius
moderate (0.429/100), 2 of 5 mitigation(s) only reduce impact after the failure starts; some residual risk remains even with all mitigations applied.
Precedent
Instagram Postgres Sharding
Key risk
Connection Exhaustion, Triggered when application concurrency exceeds database/pool capacity; blast radius is API latency, timeouts, and cascading retries.
Next action
Mitigate, Quorum synchronous replication, read from the synchronous standby (bounds staleness on that path)
Live output from the analysis engine, every line traces to structured knowledge.
6 scenarios fully modeled for decision support · 19 more as draft reference, clearly labeled and never presented as complete.
How teams use it
A concrete input to your design review
The decision report feeds into the review: specific risks and evidence for the team to work through. Here is where it fits in a normal workflow.
Pressure-test the design while it's still a choice
Get a proceed / simplify / delay verdict and the first bottleneck you'll hit, before the team commits engineering time to it.
Drop the decision into the doc
Copy the decision summary into the RFC or design doc, and use the named risks and the evidence trail (sourced precedent where it exists) to challenge “that won't happen to us.”
Turn risks into review tasks
Run the workload simulation and governance guardrail checks, and wire the telemetry signals that prove the first limit is approaching.
Auditable by default
A review you can reproduce, trace, and defend.
Every claim traces to structured knowledge or a real source, the same inputs always produce the same review, and the gaps are labeled, so you can put it in front of a design review and stand behind it.
Same input, same review
Deterministic scenario rubrics, not sampling. Re-run the review in six months and the reasoning is identical, you can diff decisions instead of re-arguing them.
Shows exactly what fired
Every line of the verdict links to the specific rubric signal, failure mode, and scaling threshold behind it. Open any of them and check the work.
Sourced precedent where it exists
Where a documented system hit the same limits (Instagram's sharding, Discord's message store) the report points at it. Where there is no sourced precedent, it says so instead of inventing one.
Won't fake certainty
Draft scenarios are labeled draft, unsupported case studies are withheld, and confidence is shown as evidence grounding, never a made-up percentage. It names what it hasn't modeled instead of guessing.
How the memo is built
From profile to review memo
Before DBRaven writes a verdict, it runs your system profile through scenario matching, topology, risk propagation, evidence checks, and recommendation logic, the same deterministic path every time.
- 1
Profile
You describe workload, constraints, team maturity, traffic, consistency, and operational tolerance.
System profile - 2
Scenario match
The profile is matched to decision-ready architecture scenarios by fixed rubric, no generation.
Matched scenario - 3
Topology
It builds the system graph: workloads, datastores, queues, caches, streams, and dependencies.
System graph - 4
Risk trace
It follows failure modes through the graph to find what breaks first and how far it spreads.
Blast radius - 5
Evidence check
It attaches sourced precedent where it exists and labels grounded relationships and draft gaps.
Grounded evidence - 6
Review memo
It produces the verdict, rationale, risks, and next actions, every line traceable.
Decision memo
Failure path analysis
See the first failure path, not just the happy path
DBRaven turns a proposed topology into a review trace: what fails first, how the load moves, what gets pulled into the blast radius, and the operational action that would make the design safer.
Read-Heavy SaaS API: Cache Failure Scenario
All systems nominal
Monitoring 6 topology paths. Cache hit rate 94%, read replica lag < 100ms.
What the report gives you
- First failure path
- Redis cache failure -> direct primary reads -> connection pressure
- Blast radius
- Read endpoints, worker fetches, replica freshness, and database pool capacity
- Next action
- Add a guarded bypass, pool limits, replica-lag alerting, and cache warm-up runbook
Honest by construction
DBRaven would rather show an evidence gap than fabricate proof.
The report only draws on knowledge it can stand behind. What it hasn’t modeled, it labels; what it can’t source, it withholds, so the confidence you see is earned.
Get a review-ready architecture memo
Describe your system and get a decision report, verdict, what breaks first, risks, and next actions, every claim traced to structured knowledge.