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Architecture field guide

Architecture Assessment Checklist for Complex .NET Systems

A practical framework for finding the risks that slow delivery, destabilize production and make every change more expensive.

15-minute review 10 assessment areas Dmitrijs Taranenko

What an architecture assessment should answer

A useful assessment is not a catalogue of technologies. It should explain where business-critical flows can fail, why delivery is slow, which constraints are real and what sequence of changes produces the most value with the least risk.

Use the questions below with code, telemetry, deployment data and production incidents. If an answer depends on tribal knowledge, treat it as unverified.

  1. 01

    Business-critical flows and service objectives

    Ask: Which user and operational flows directly affect revenue, contractual commitments or customer trust? What latency, availability and recovery targets apply?

    Collect: flow diagrams, SLOs, incident impact and business owners.

    Red flag: Every component is treated as equally critical, or success is defined only as “the system is up”.

  2. 02

    System boundaries and dependency map

    Ask: Can the team trace a critical request through applications, services, queues, databases and external providers?

    Collect: runtime topology, API contracts, event flows and infrastructure ownership.

    Red flag: The architecture diagram describes intent but no longer matches production.

  3. 03

    Coupling and change impact

    Ask: Which modules must be changed or deployed together? Where do shared libraries, databases or synchronous call chains expand the blast radius?

    Collect: repository dependencies, deployment units, change history and failed releases.

    Red flag: A small feature routinely requires coordinated changes across several teams or services.

  4. 04

    Data ownership and consistency

    Ask: Who owns each business entity? Where are transactions required, and where is eventual consistency acceptable? How are retries and duplicate messages handled?

    Collect: schemas, transaction boundaries, idempotency rules, reconciliation jobs and data incidents.

    Red flag: Multiple services write the same tables or compensate for inconsistencies manually.

  5. 05

    Performance and capacity

    Ask: Where is time spent across the full request path? Which workloads are CPU, memory, database, network or dependency bound?

    Collect: traces, query plans, load profiles, queue depth, cache behaviour and cloud cost by workload.

    Red flag: Performance work starts with code changes before a representative baseline exists.

  6. 06

    Reliability and failure modes

    Ask: What happens when a database, queue, downstream API or region becomes slow or unavailable? Are timeouts, retries and circuit breakers coordinated?

    Collect: incident timelines, retry policies, recovery procedures, RPO/RTO and dependency failure tests.

    Red flag: Retrying is the default response to failure, creating amplification during an outage.

  7. 07

    Security and operational access

    Ask: How are identities, secrets, permissions and sensitive data controlled from development through production?

    Collect: threat models, IAM roles, secret rotation, audit trails, dependency scans and data-retention rules.

    Red flag: Long-lived credentials, broad production access or security checks performed only before an audit.

  8. 08

    Delivery, rollback and test confidence

    Ask: How long does a safe production change take? Can the team deploy independently, verify behaviour and roll back without data loss?

    Collect: lead time, deployment frequency, failure rate, pipeline duration, test coverage by risk and rollback evidence.

    Red flag: Releases require long manual checklists because automated verification cannot be trusted.

  9. 09

    Observability and production ownership

    Ask: Can engineers explain a customer-visible failure using correlated logs, metrics and traces? Are alerts tied to actionable symptoms?

    Collect: dashboards, trace coverage, alert history, runbooks and on-call feedback.

    Red flag: Teams discover incidents from customers or search unstructured logs without correlation IDs.

  10. 10

    Modernization sequence and decision record

    Ask: Which constraint should be removed first? What can be improved incrementally, and which change genuinely requires replacement?

    Collect: ranked risks, expected outcomes, dependencies, decision records and measurable exit criteria.

    Red flag: “Rewrite the platform” is the roadmap, with no staged value, migration path or rollback boundary.

The useful output

Turn findings into an executable decision

The finished assessment should leave the team with a current system map, an evidence-backed risk register, a prioritized roadmap and explicit success criteria. Recommendations should separate immediate production risk, near-term delivery improvements and longer-term architecture evolution.

  • Now: contain material reliability, security or data-integrity risk.
  • Next: remove the bottlenecks that most constrain delivery or customer outcomes.
  • Later: modernize boundaries once the system is observable and change is controlled.

Need an independent assessment?

Turn the checklist into a prioritized modernization roadmap

I assess the real code, data paths, runtime evidence and delivery constraints behind complex .NET systems—then identify the smallest safe sequence of changes.

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