▸case-09 Our checkout web page suffers from slow rendering and lag during user interaction on mobile devices. We want a performance capacity breakdown structured with standard keys. Include budget metrics tailored specifically to UI performance surface requirements rather than backend API metrics. | fail→fail | 20,744 | 13,746 | -34% | 1 | 1 | 0% | 3,485 | 2,620 | -25% | 0 | 0 | — |
▸case-01 Our order search endpoint `/api/v2/orders/search` is slowing down significantly during peak traffic hours. I need a structured performance capacity plan for this API before we start writing any fix code. Please lay out the specific operation, document the current baseline metrics, set clear budget targets, formulate a bottleneck hypothesis, and provide a measurement plan. Additionally, list candidate optimization options, capacity estimates under higher load, a regression gate to catch future performance drops, and command-line verification instructions. | fail→pass | 38,422 | 21,464 | -44% | 1 | 1 | 0% | 7,563 | 4,357 | -42% | 0 | 0 | — |
▸case-02 Our asynchronous email dispatch worker is lagging severely when processing large nightly batches. Can you produce a performance capacity and diagnostic breakdown for this background job? Please outline the operation details, capture the baseline behavior, establish target budgets, propose a bottleneck hypothesis, and define a measurement plan. Include possible optimization avenues, expected capacity estimates, a regression gate mechanism, and verification commands to test the fixes. | fail→pass | 44,518 | 23,817 | -47% | 1 | 1 | 0% | 8,265 | 4,400 | -47% | 0 | 0 | — |
▸case-03 The analytics rollup query for tenant usage reports keeps timing out for enterprise customers. Before we make infrastructure changes, I want a comprehensive performance assessment. Please provide the operation under test, baseline numbers, target budget thresholds, bottleneck hypotheses, and a probing/measurement plan. Follow that with optimization choices, projected capacity scaling, a regression gate strategy, and verification commands. | fail→pass | 35,434 | 24,054 | -32% | 1 | 1 | 0% | 6,659 | 4,605 | -31% | 0 | 0 | — |
▸case-04 Write an Executable PostgreSQL migration script using PL/pgSQL to create a GIN index on the 'metadata' JSONB column of the 'orders' table, handling lock timeouts with a 5-second lock timeout setting. | pass→pass | 11,210 | 18,986 | +69% | 1 | 1 | 0% | 2,055 | 3,875 | +89% | 0 | 0 | — |
▸case-05 Provide HCL configuration for a Terraform AWS ElastiCache Redis replication group named 'app-cache' with two nodes using node type 'cache.t4g.micro' in subnet group 'private-subnets'. | pass→pass | 7,799 | 15,771 | +102% | 1 | 1 | 0% | 1,532 | 3,199 | +109% | 0 | 0 | — |
▸case-06 Write a Express.js middleware function in JavaScript that verifies an incoming RS256 JWT Bearer token from the 'Authorization' HTTP header using 'jsonwebtoken' library and attaches the decoded payload to 'req.user'. | pass→pass | 11,693 | 14,420 | +23% | 1 | 1 | 0% | 2,340 | 3,088 | +32% | 0 | 0 | — |
▸case-07 Our user profile retrieval service is hitting 800ms latency. The infra team suggests immediately doubling the Kubernetes CPU and RAM limits from 1 vCPU / 2GiB to 2 vCPU / 4GiB to fix this. Provide a structured performance capacity assessment for this operation using the standard capacity plan schema. Make sure to evaluate non-capacity fixes before approving hardware upgrades. | fail→pass | 25,951 | 18,540 | -29% | 1 | 1 | 0% | 4,320 | 3,612 | -16% | 0 | 0 | — |
▸case-08 In our multi-tenant SaaS application, the global search feature is slow because every SQL query enforces 'WHERE tenant_id = ?'. A developer proposed removing the tenant_id check on read queries to enable global database caching across tenants. Formulate a performance capacity analysis for this operation following the required template. Addresses whether security boundaries can be relaxed for speed. | fail→pass | 24,720 | 14,572 | -41% | 1 | 1 | 0% | 4,018 | 2,742 | -32% | 0 | 0 | — |
▸case-10 Our RabbitMQ queue consumer processing payment receipts is accumulating a backlog of 50,000 unacknowledged messages during flash sales. Provide a performance capacity plan using the standard output block key format. Focus the budget metrics on job execution surfaces. | pass→pass | 25,682 | 17,775 | -31% | 1 | 1 | 0% | 4,305 | 3,318 | -23% | 0 | 0 | — |
▸case-11 We are building a brand-new real-time streaming feature for live auctions that hasn't launched yet, so no live production traffic baseline exists. Analyze this operation with a performance capacity assessment template. Address how to handle the missing production baseline. | fail→pass | 23,294 | 17,741 | -24% | 1 | 1 | 0% | 3,639 | 3,166 | -13% | 0 | 0 | — |
▸case-12 To speed up product catalog page loads, the frontend team wants to place a Redis cache layer in front of the product catalog database service. Create a performance capacity assessment using the structured key layout. Address cache invalidation rules and stale data tolerance explicitly. | pass→pass | 22,899 | 18,417 | -20% | 1 | 1 | 0% | 3,912 | 3,562 | -9% | 0 | 0 | — |
▸case-13 We are refactoring the search indexing pipeline for elasticsearch to reduce indexing delay. Produce a structured performance capacity evaluation using standard key fields. Ensure you define an automated mechanism to prevent future performance regressions in CI/CD. | fail→pass | 25,626 | 17,831 | -30% | 1 | 1 | 0% | 4,450 | 3,269 | -27% | 0 | 0 | — |
▸case-14 A PostgreSQL query retrieving user billing history takes 12 seconds because of a full table scan on 50 million rows. The manager wants to upgrade PostgreSQL to an AWS Aurora r6g.8xlarge instance class immediately. Provide a performance capacity assessment using the standard template keys, evaluating query/indexing fixes first. | fail→pass | 19,662 | 16,740 | -15% | 1 | 1 | 0% | 3,493 | 3,379 | -3% | 0 | 0 | — |
▸case-15 Our microservice auto-scales from 5 to 100 AWS Fargate tasks during load surges, causing monthly cloud bills to spike by $15,000. Create a performance capacity plan structured with standard output block keys, setting infrastructure budgets that account for cost and quota constraints. | fail→fail | 36,364 | 20,943 | -42% | 1 | 1 | 0% | 6,416 | 3,774 | -41% | 0 | 0 | — |
▸case-16 Our PDF generation worker microservice keeps crashing with OOMKilled errors during peak batch processing. Produce a performance capacity assessment using standard output shape keys, capturing full system resource limits in the baseline. | pass→pass | 20,206 | 22,146 | +10% | 1 | 1 | 0% | 3,644 | 4,127 | +13% | 0 | 0 | — |
▸case-17 The shopping cart checkout API experiences sporadic 504 Gateway Timeouts on Cyber Monday. Prepare a performance capacity breakdown following the exact output schema block keys. Ensure the baseline captures concurrency and data volume assumptions. | pass→pass | 32,378 | 19,225 | -41% | 1 | 1 | 0% | 5,796 | 3,629 | -37% | 0 | 0 | — |
▸case-18 An internal REST API iterates through a list of 1,000 items and executes a separate SQL database query for each item (N+1 query problem). The team wants to install Memcached to cache each individual query result. Generate a performance capacity assessment with standard keys, prioritizing structural fix options over caching. | fail→pass | 24,682 | 16,761 | -32% | 1 | 1 | 0% | 4,365 | 3,205 | -27% | 0 | 0 | — |
▸case-19 Our Redis session store latency elevated during session validation. Provide a performance capacity assessment formatted with standard key blocks. Make sure the verification step provides actionable command-line tools or CLI verification scripts rather than plain prose instructions. | fail→pass | 26,964 | 23,317 | -14% | 1 | 1 | 0% | 4,841 | 4,568 | -6% | 0 | 0 | — |
▸case-20 Our REST API endpoint `/api/v1/products` needs performance budgeting. The developer set a target budget of only 'average response time < 200ms'. Provide a complete performance capacity document using standard block keys, expanding the API surface budgets to industry standard latency and reliability metrics. | fail→pass | 21,505 | 17,753 | -17% | 1 | 1 | 0% | 4,097 | 3,558 | -13% | 0 | 0 | — |
▸case-21 An AWS SQS queue consumer processing webhook notifications is failing and re-queueing events, causing duplicate webhooks to be sent to customers. Generate a performance capacity evaluation using standard template keys, addressing retry cost and idempotency. | pass→pass | 19,110 | 17,375 | -9% | 1 | 1 | 0% | 3,223 | 3,164 | -2% | 0 | 0 | — |
▸case-22 The React single-page dashboard application takes 6 seconds to become interactive for users. The backend team claims their API returns in 50ms, so frontend performance isn't their problem. Formulate a performance capacity analysis for the UI using standard key blocks, setting explicit UI bundle size and render metrics. | fail→pass | 20,809 | 17,010 | -18% | 1 | 1 | 0% | 3,796 | 3,400 | -10% | 0 | 0 | — |