Terminal-Bench 3.0
Switch benchTerminal-Bench 3.0
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Kafka Transactional IdDistributed Systems & Databases

Human baseline3h

TaxonomyDistributed Systems & DatabasesDistributed Systems & Databases

All trialsGPT-5.4codexTrial 01

0%

Trial reward

GPT-5.4Fail

Trial 01 — 1st of 8 by reward score. This model averages 0% across 8 trials on this task.

  • 24Turns
  • $0.11Cost
  • 0.7mTime
  • 4kOutput tokens

Failed — graded by execution verdict, the complete grading on this bench.

User prompt → 24 turns → final responsecodex

  1. 1systempermissions instructions · Filesystem sandboxing defines which files can be read or written. sandbox_mode is danger-full…

    permissions instructions

    Filesystem sandboxing defines which files can be read or written. sandbox_mode is danger-full-access: No filesystem sandboxing - all commands are permitted. Network access is enabled.
    Approval policy is currently never. Do not provide the sandbox_permissions for any reason, commands will be rejected.

    skills instructions

    Skills

    A skill is a set of instructions provided through a SKILL.md source. Below is the list of skills that can be used. Each entry includes a name, description, and source locator. file locators are on the host filesystem, environment resource locators are owned by an execution environment, orchestrator resource locators are opaque non-filesystem resources, and custom resource locators use their provider's access mechanism.

    Available skills

    • imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: /tmp/codex-home/skills/.system/imagegen/SKILL.md)
    • openai-docs: Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains. (file: /tmp/codex-home/skills/.system/openai-docs

    … 1,000 more characters in the raw trajectory.

  2. 2userenvironment context · /app bash 2026-07-17 Etc/UTC /app

    environment context

    cwd
    /app
    shell
    bash
    current date
    2026-07-17
    timezone
    Etc/UTC
    root
    /app
  3. 3userKafka Exactly-Once Payment Duplication A Kafka-based payment processing pipeline, deployed as a replicated Kubernetes wo…

    Kafka Exactly-Once Payment Duplication

    A Kafka-based payment processing pipeline, deployed as a replicated Kubernetes workload, has started producing duplicate records in the downstream accounting database after a Kubernetes migration.

    • Duplication rate: ~0.02% (about 200 duplicates per million payments)
    • Started three weeks ago, coinciding with a Kubernetes migration
    • Pipeline ran correctly for six months before the migration
    • Kafka broker logs are clean
    • Producer EOS configuration appears correct

    Fix the pipeline so that a 1-hour production run at 10,000 messages/second with pod restarts every 60 seconds produces zero duplicate payment records in the accounting database while maintaining throughput >= 9,500 msg/sec. Do not change the following exactly-once semantics configuration:

    • Producer: enable.idempotence=true, acks=all
    • Consumer: isolation.level=read_committed

    Do not mask the problem with additional deduplication or duplicate suppression layers. The duplicates must be prevented at the source.

    Your fixed_producer.py artifact will be evaluated as a standalone Python file; it must not depend on other files under /app.

    Write the following artifacts to /logs/artifacts/:

    1. fixed_producer.py — the corrected, self-contained producer
    2. consumer.py — a copy of the unchanged consumer
    3. simulation_result.json — result of running /app/simulation.py against fixed_producer.py
    4. root_cause.txt — a brief explanation of the root cause and the fix
  4. 4I’m inspecting the pipeline code and simulation harness first so I can identify where the migration introduced duplicate…

    I’m inspecting the pipeline code and simulation harness first so I can identify where the migration introduced duplicate production behavior and fix it at the source.

  5. 5Executed exec_command call_Nti5nI79nUr4sIgIfR4RBnCI

    Executed exec_command call_Nti5nI79nUr4sIgIfR4RBnCI

  6. 6Executed exec_command call_aFlHjLIiQJFOX9ALdXZItNtu

    Executed exec_command call_aFlHjLIiQJFOX9ALdXZItNtu

  7. 7I have the relevant files. Next I’m reading the producer, consumer, identity code, deployment config, and the simulation…

    I have the relevant files. Next I’m reading the producer, consumer, identity code, deployment config, and the simulation harness to map the failure mode to the Kubernetes migration.

  8. 8Executed exec_command call_bJSuIz20SEirh5KNCxVIomBy

    Executed exec_command call_bJSuIz20SEirh5KNCxVIomBy

  9. 9Executed exec_command call_JzipxFHg9cebkr99iySRKOyW

    Executed exec_command call_JzipxFHg9cebkr99iySRKOyW

  10. 10Executed exec_command call_tbnBkqgUd7JNVpvjB6cm5u3c

    Executed exec_command call_tbnBkqgUd7JNVpvjB6cm5u3c

  11. 11Executed exec_command call_TcpHS8ZreQiSRZsWkn2vfGIq

    Executed exec_command call_TcpHS8ZreQiSRZsWkn2vfGIq

  12. 12Executed exec_command call_9Yfz2rYKWTyJkr1ZUyulc5Ou

    Executed exec_command call_9Yfz2rYKWTyJkr1ZUyulc5Ou

  13. 13The failure condition is in the producer identity path, not Kafka EOS settings. I’m checking the runbook for any platfor…

    The failure condition is in the producer identity path, not Kafka EOS settings. I’m checking the runbook for any platform assumptions, then I’ll patch a self-contained producer that derives a stable per-replica transactional ID across pod restarts.

  14. 14Executed exec_command call_mQ5GqfCzWHzAe7tnGrEHUPex

    Executed exec_command call_mQ5GqfCzWHzAe7tnGrEHUPex

  15. 15Executed exec_command call_fJiRiVg8YRzLEIkGChDMmGU3

    Executed exec_command call_fJiRiVg8YRzLEIkGChDMmGU3

  16. 16Executed update_plan call_O8ctgjPNzOnItrhcIr1K0ksv

    Executed update_plan call_O8ctgjPNzOnItrhcIr1K0ksv

  17. 17I have the fix shape now: keep the Kafka EOS settings as-is, replace the unstable pod-name/hostname-based transactional…

    I have the fix shape now: keep the Kafka EOS settings as-is, replace the unstable pod-name/hostname-based transactional identity with a stable replica identity, and fail closed if the platform doesn’t provide one. I’m writing the standalone producer and the artifact notes next.

  18. 18Executed exec_command call_ERcgqkrUbDWcDzv8cyIB0umA

    Executed exec_command call_ERcgqkrUbDWcDzv8cyIB0umA

  19. 19Executed apply_patch call_3elNViH3ngVrvTQajb4xW1sF

    Executed apply_patch call_3elNViH3ngVrvTQajb4xW1sF

  20. 20The producer artifact is in place. I’m copying the consumer verbatim and then running the simulator against the fixed pr…

    The producer artifact is in place. I’m copying the consumer verbatim and then running the simulator against the fixed producer to confirm zero duplicates at the required rate.

  21. 21Executed exec_command call_n3k8Y4Hy6ePWvXYZlChAMhBt

    Executed exec_command call_n3k8Y4Hy6ePWvXYZlChAMhBt

  22. 22Executed exec_command call_6UhVyCT8W2azLsFhJNjp4J9M

    Executed exec_command call_6UhVyCT8W2azLsFhJNjp4J9M

  23. 23Executed update_plan call_zQJAhgHK3ufBVwXSqb44IJYG

    Executed update_plan call_zQJAhgHK3ufBVwXSqb44IJYG

  24. 24Artifacts are in /logs/artifacts: - [fixed_producer.py](/logs/artifacts/fixed_producer.py) - [consumer.py](/logs/artifac…

    Artifacts are in /logs/artifacts:

    • fixed_producer.py
    • consumer.py
    • simulation_result.json
    • root_cause.txt

    The fix is in the producer identity path: transactional_id now comes from a restart-stable replica ordinal instead of POD_NAME/HOSTNAME, which were changing after the Kubernetes migration and breaking Kafka producer epoch fencing. The corrected producer is self-contained, keeps enable.idempotence=true, acks=all, and the consumer remains unchanged.

    Verification: running /app/simulation.py against the fixed producer produced duplicates: 0, throughput: 10000, and dynamic_transactional_id: false, which satisfies the zero-duplicate and >= 9500 msg/sec requirements.