| Category | Item | Description / Details | Mandatory |
| 1. Objective Definition | Test Objective | Define what you are testing: performance, scalability, stability, or regression. | Yes |
| Success Criteria | Define SLAs or benchmarks for response time, error rate, and throughput. | Yes | |
| Expected Traffic Pattern | Choose traffic shape: steady, spike, ramp-up, soak, or burst load. | Yes | |
| 2. API Specifications | List of Endpoints | List of API URLs and HTTP methods (GET, POST, PUT, etc.) to be tested. | Yes |
| Request/Response Schema | Sample request bodies and expected response formats for each API. | Yes | |
| API Documentation | OpenAPI/Swagger spec or Postman collection to understand APIs clearly. | Yes | |
| Dependency Map | Note any downstream systems or services each endpoint interacts with. | Conditional | |
| 3. Authentication | Auth Mechanism | Identify if the API uses Basic Auth, API keys, JWT, or OAuth2. | Yes |
| Token Generation | Understand how to generate or acquire tokens (e.g., login, service call). | Yes | |
| Token Expiry Handling | Account for token expiry and renewal if tests run long. | Conditional | |
| Role/Access Levels | Determine whether different endpoints require different user roles. | Conditional | |
| 4. Test Data | Valid Data Samples | Collect payloads, query parameters, and path variables required by APIs. | Yes |
| Parameterization Strategy | Plan for dynamic test data (e.g., user IDs, timestamps, random values). | Yes | |
| Number of Unique Users | Estimate how many distinct users are needed to simulate concurrency. | Conditional | |
| Preloaded Entities | Ensure any related objects (products, orders) are created before the test. | Conditional | |
| Data Cleanup Plan | Plan for test data cleanup, especially for write-heavy operations. | Conditional | |
| 5. Load Design | Concurrent Users | Set the number of virtual users to simulate parallel requests. | Yes |
| Requests per Second (RPS) | Define the target throughput or request volume over time. | Yes | |
| Ramp-up Time | Specify how quickly the test load will increase to simulate real usage patterns. | Yes | |
| Think Time / Pacing | Set user delay between steps to mimic real user behavior. | Conditional | |
| Test Duration | Decide how long the load will be applied (short bursts or endurance). | Yes | |
| 6. Environment | Target Environment | Ensure you know the base URL or hostname of the API environment to test. | Yes |
| Production Parity | Confirm how closely the test environment matches production in infra and config. | Conditional | |
| Isolation | Prevent other tests or deployments from running during your test. | Yes | |
| Monitoring Access | Ensure visibility into system metrics during test execution. | Yes | |
| 7. Tooling | Load Testing Tool | Decide which tool will be used (e.g., JMeter, k6, Gatling, Locust). | Yes |
| Tool Installation and Setup | Verify installation and configuration of the tool and supporting dependencies. | Yes | |
| Script Parameterization | Incorporate dynamic values (e.g., CSV, feeders) in test scripts. | Yes | |
| Response Validation | Include logic to check HTTP status codes and content correctness. | Yes | |
| Script Dry Run | Run the script with minimal load to ensure correctness before applying full load. | Yes | |
| 8. Monitoring | Application Metrics | Setup dashboards for response time, error count, latency, and request distribution. | Yes |
| System Metrics | Track CPU, memory, disk I/O, and network activity. | Yes | |
| Database Metrics | Monitor query time, connection pool size, and slow query logs. | Conditional | |
| Logging System | Enable access to logs for application, exceptions, and infrastructure. | Yes | |
| Dashboards | Ensure dashboards (e.g., Grafana, CloudWatch) are active to observe live trends. | Conditional | |
| 9. Governance | Rate Limits or API Quotas | Be aware of any platform-level or gateway-level limits (e.g., 1000 RPS). | Conditional |
| Throttling and Retry Logic | Know how the system handles overload, retries, or 429/503 errors. | Conditional | |
| Notification to Stakeholders | Inform DevOps, Infra, and QA teams about test timing to avoid conflicts. | Conditional | |
| Rollback Plan in Case of Side Effects | Plan how to undo test changes (e.g., mass test user creation or transactions). |
| Category | Item | Description / Details | Mandatory |
| 1. Objective Definition | Test Objective | Define whether you are testing performance, UX under load, or frontend/backend interaction latency. | Yes |
| Success Criteria | Target page load times, acceptable UX delays, error thresholds, or component rendering completion. | Yes | |
| Load Profile | Number of simulated users, load duration, and flow repetition frequency. | Yes | |
| 2. Scenario Planning | User Journeys / Click Paths | Define key flows to simulate (e.g., login → dashboard → search → edit profile). | Yes |
| Pages or Screens Under Test | Identify which screens will be opened and interacted with during the test. | Yes | |
| Think Time / User Delay | Define wait times between user actions to simulate real behavior. | Yes | |
| Data Variation | Plan dynamic user data (e.g., usernames, product IDs) for different sessions. | Conditional | |
| 3. Authentication | Auth Mechanism | How users log in (form-based, SSO, token injection), and how it’s scripted in the tool. | Yes |
| Session Management | Handle cookies, session expiry, and CSRF tokens between steps. | Yes | |
| User Pool | Pool of test user accounts to be used in parallel (unique or shared users). | Yes | |
| 4. Element Handling | DOM Element Locators | Accurate selectors for buttons, input fields, and links (IDs, class names, XPath, etc.). | Yes |
| Dynamic Element Readiness | Use appropriate waits for JS-loaded content (explicit waits, condition checks). | Yes | |
| Page Load Synchronization | Define when a page is considered "fully loaded" (DOM ready, AJAX complete, etc.). | Yes | |
| 5. Tooling | Testing Tool | Tool choice (e.g., Selenium Grid, Playwright, Cypress with parallelization plugins). | Yes |
| Execution Mode | Choose headless vs. headed browsers based on test scope and infra limitations. | Yes | |
| Scripting Language | Confirm scripting language used (Java, Python, JS, etc.) and framework readiness. | Yes | |
| Parallel Execution Setup | Ability to run multiple browser instances or distribute across nodes. | Yes | |
| Load Injection Controller | Use a controller to schedule and manage browser sessions and user flows. | Conditional | |
| 6. Test Data | Input Data for Forms/Actions | Prepare email IDs, names, addresses, or any form inputs needed. | Yes |
| Visual Assets (if needed) | Images, files, or attachments to simulate file uploads or form completions. | Conditional | |
| State Preparation | Ensure required backend state (e.g., existing orders, empty carts) is setup before test. | Conditional | |
| 7. Infrastructure Setup | Execution Nodes | Sufficient and scalable VMs/containers to run browser instances in parallel. | Yes |
| Browser Drivers / Dependencies | Install and configure browser drivers (e.g., ChromeDriver, GeckoDriver). | Yes | |
| Tool Agent Setup | Tools like Selenium Grid or Playwright Test Runner must be ready and registered with nodes. | Yes | |
| 8. Environment Readiness | Test Environment URL | Provide base URL of the UI environment to be tested (e.g., staging, UAT). | Yes |
| Env Isolation / Stability | No deployments or parallel load on the environment during testing. | Yes | |
| Responsive / Device Target | Define if testing desktop only or also mobile/tablet via viewport resizing. | Conditional | |
| 9. Monitoring | Page Load Time Tracking | Use browser timers or frontend logs to capture load/render times. | Yes |
| JavaScript Error Logging | Collect any frontend errors/exceptions that occur during test. | Yes | |
| Backend/API Metrics | Complement UI test with backend metrics to correlate slowdowns. | Conditional | |
| Video or Screenshot Capture | Capture videos or screenshots for failed flows or checkpoints. | Conditional | |
| 10. Governance | Test Duration Limits | Ensure browser tests don’t run excessively long to avoid memory leaks or browser crashes. | Yes |
| License Limits (if using commercial tool) | Be aware of any license or concurrency caps. | Conditional | |
| Stakeholder Notification | Notify QA, Dev, and Infra teams of the test schedule and expectations. | Conditional | |
| Result Reporting | Plan to generate readable reports (HTML, dashboards, CI uploads) post test. |
| Category | Item | Description / Details | Mandatory |
| 1. Objective Definition | Test Objective | Define the purpose: throughput testing, latency measurement, queue depth handling, or failure resilience. | Yes |
| Success Criteria | Define SLAs for processing time, message loss, retries, dead-letter thresholds, etc. | Yes | |
| Load Pattern | Constant, ramp-up, burst, or soak — define load profile over time. | Yes | |
| 2. Entry Point & Triggers | Type of Backend Component | Identify whether it’s an event listener, scheduled batch job, queue consumer, webhook handler, etc. | Yes |
| Trigger Mechanism | How is the process triggered? (e.g., Kafka topic, JMS queue, cron, webhook, internal poller) | Yes | |
| Trigger Source Simulation | Simulate or mock producers/publishers to generate the load. | Yes | |
| Queue/Topic Name | Exact name of the queue/topic/endpoint to which load will be published. | Yes | |
| Message Protocol and Format | Know the protocol (e.g., AMQP, JMS, Kafka) and message format (JSON, XML, binary). | Yes | |
| 3. Message Content | Message Payload Sample | Prepare valid, realistic payloads to simulate production behavior. | Yes |
| Field Variation Strategy | Parameterize fields like IDs, timestamps, values for randomness. | Yes | |
| Message Size Estimation | Understand average vs max payload size to test serialization, bandwidth, and memory use. | Yes | |
| Message Rate | Define messages per second (MPS), total messages, batch size, or scheduling interval. | Yes | |
| 4. Queue/System Behavior | Consumer Configuration | Confirm consumer app settings: concurrency, batch size, thread pool, ack strategy. | Yes |
| Retry and Error Handling | Understand retry policy, delay, and handling logic in case of failures. | Yes | |
| Dead-Letter Queue Behavior | Know where failed messages go, and how they’re processed or alerted. | Conditional | |
| Ordering & Deduplication Strategy | If ordering matters, confirm how it is handled (e.g., Kafka partitions, idempotency keys). | Conditional | |
| 5. Test Data & Dependencies | Data Initialization | Required setup data in DB or external services for the processing logic to function. | Conditional |
| External Calls | Any dependent APIs or systems the backend connects to — check availability or stub them. | Yes | |
| Test Isolation | Ensure no cross-contamination of production queues or shared infrastructure. | Yes | |
| 6. Infrastructure Setup | Queue Broker Setup | Kafka, RabbitMQ, ActiveMQ, etc. — ensure correct version, cluster size, and topic/queue configuration. | Yes |
| Monitoring Integration | Hook into metrics (e.g., consumer lag, queue depth, processing latency, error count). | Yes | |
| Resource Scaling & Limits | Ensure backend service, DB, and broker nodes have proper CPU, memory, and disk allocation. | Yes | |
| 7. Tooling | Load Publisher Tool | Choose tools like Kafka CLI, custom Java/Python publisher, JMeter with JMS plugin, or Testcontainers. | Yes |
| Automation Script | Scripted mechanism to generate load in volume — through CLI, CI job, or test harness. | Yes | |
| Replay of Historical Messages | Optional: ability to replay previously captured messages for realistic test. | Conditional | |
| Metrics Collection Setup | Ensure metrics from consumer, broker, and infra are captured in tools like Prometheus, Grafana, or ELK. | Yes | |
| 8. Observability & Alerts | Consumer Lag Metrics | Monitor time or count lag between publish and consume (esp. for Kafka). | Yes |
| Error Logs & Exception Tracing | Ensure logs are tailing correctly for runtime issues or deserialization failures. | Yes | |
| Broker Health | Monitor queue/topic depth, partition lag, dropped messages, and delivery latency. | Yes | |
| Alert Suppression or Notification | Disable or mute alerts if test volume will trigger false positives. | Conditional | |
| 9. Cleanup Plan | Post-Test Message Purge | Strategy to clean up test messages from queues, logs, or DB. | Yes |
| Test Data Reset | Rollback or truncate any changes to maintain clean state. | Conditional | |
| Resource Teardown | Shut down any temporary services or test infrastructure after testing completes. | Conditional | |
| 10. Stakeholder Coordination | Test Schedule Announcement | Inform stakeholders (DevOps, QA, Infra, Observability) of timing and scope. | Conditional |
| SLA Violation Notification | Know who to contact in case load test reveals service breakdowns. | Conditional | |
| Result Reporting Strategy | Define how test results will be published, shared, and reviewed. | Yes |
| Category | Item | Description / Details | Mandatory |
| 1. Objective Definition | Test Objective | Define goal: max throughput, query latency, concurrent connections, connection pool testing, write capacity, etc. | Yes |
| Success Criteria | Set benchmarks for query response times, TPS, CPU usage, IOPS, replication delay, etc. | Yes | |
| Load Profile | Define traffic pattern: steady, burst, ramp-up, long-duration (soak), etc. | Yes | |
| 2. Scope Definition | Query Types | Specify which types of queries will be tested (SELECT, INSERT, UPDATE, DELETE, complex JOINs). | Yes |
| Load Entry Point | Will queries hit DB directly (e.g., via JDBC) or through backend services/APIs? | Yes | |
| Table Coverage | List which tables, collections, or partitions are involved in the test. | Yes | |
| 3. Data Strategy | Test Dataset | Prepare test data for query execution — realistic and of meaningful volume. | Yes |
| Dataset Size | Ensure dataset size reflects production-like distribution for indexes, partitions, joins, etc. | Yes | |
| Data Loading Method | Script or mechanism to pre-load DB with required data. | Yes | |
| Data Refresh Plan | Strategy to reload/reset DB before each test iteration. | Conditional | |
| Data Consistency | Ensure referential integrity and constraints are honored if applicable. | Yes | |
| 4. Query Execution Setup | Query Frequency | Define how many queries per second, per thread, or per session are to be fired. | Yes |
| Parameterization Strategy | Use variable input values for dynamic queries to avoid result caching. | Yes | |
| Transaction Control | Define if queries are inside transactions (BEGIN/COMMIT), and how isolation levels affect performance. | Conditional | |
| Query Caching Strategy | Understand and configure caching (app-side or DB-side) for realistic simulation. | Conditional | |
| 5. Connection Management | Number of Connections | Define total active connections during load test. | Yes |
| Connection Pool Size | Configure pool size in app/server (e.g., HikariCP, Tomcat JDBC). | Yes | |
| Pool Exhaustion Strategy | Define behavior when pool is full — queue, fail, grow. | Conditional | |
| Idle and Timeout Settings | Check timeout, eviction, and idle thresholds for connection reuse. | Conditional | |
| 6. Indexing & Optimization | Index Coverage | Ensure queries have indexes or deliberately test index-less cases. | Yes |
| Query Plan Review | Use EXPLAIN PLAN or profiling to verify execution paths. | Yes | |
| Partitioning/Sharding Awareness | If DB is partitioned, validate how load is distributed and whether skew occurs. | Conditional | |
| 7. Infrastructure Setup | Database Instance Size | Instance type, CPU/memory limits, IOPS provisioning must be clearly defined. | Yes |
| Disk Configuration | Disk type (SSD, network-attached), write IOPS, buffer pool size, redo/undo configuration. | Conditional | |
| Replication Setup | If replication is enabled, test replication lag or sync pressure under load. | Conditional | |
| Monitoring Agent Setup | Ensure metrics collection tools are ready — Prometheus exporters, APM agents, CloudWatch, etc. | Yes | |
| 8. Metrics & Observability | Query Latency | Capture metrics on min/avg/max response times. | Yes |
| Error Rate | Track query failures, connection errors, constraint violations, etc. | Yes | |
| Resource Metrics | Monitor CPU, memory, disk I/O, buffer pool hits, table scans. | Yes | |
| Connection Usage | Observe active/idle connections, failed handshakes, connection churn. | Yes | |
| Locking/Deadlocks | Track contention — row locks, table locks, blocking queries. | Conditional | |
| 9. Tooling | Load Test Tool | Choose load generator (e.g., JMeter JDBC plugin, custom Java app, BenchmarkSQL). | Yes |
| Script/Query Execution Framework | Implement repeatable, parameterized query execution. | Yes | |
| Data Generator Tool | Optionally use tools like dbForge, pgbench, or Flyway to prepare data. | Conditional | |
| Logging/Profiling Tool | Enable slow query logs, AWR (Oracle), pg_stat_statements (PostgreSQL), etc. | Yes | |
| 10. Governance | Access Control | Validate user roles used in test — read-only, DML, admin users. | Yes |
| Isolation from Production | Never load test production DB. Always use a replica or test-specific environment. | Yes | |
| Maintenance & Backup Window Awareness | Avoid running during DB maintenance jobs, backup windows, or migration schedules. | Yes | |
| Alert Mute Strategy | Temporarily mute alerts for CPU, locks, or slow queries during test execution. | Conditional | |
| Test Timing Approval | Coordinate with DBA and infra teams on test schedule and capacity impact. | Yes | |
| 11. Post-Test Cleanup | Data Cleanup Plan | Truncate tables or restore DB snapshot after test completion. | Yes |
| Resource Release | Shut down test instances or scale down cloud infra if scaled up temporarily. | Conditional | |
| Result Storage | Save logs, metrics, and query plans for review. | Yes |
| Category | Item | Description / Details | Mandatory |
| 1. Objective Definition | Test Objective | Define what you are validating — integration resilience, API SLA adherence, fallback logic, or proxy behavior. | Yes |
| Scope of Load | Clarify if full-scale load will hit the third-party directly or only through stubs/mocks. | Yes | |
| Success Criteria | Response times, status codes, retry handling, rate limits, and fallback performance. | Yes | |
| Legal/Policy Compliance | Confirm load test is allowed under the provider’s usage policy and contract. | Yes | |
| 2. Access & Authentication | Auth Type | API key, OAuth2, JWT, HMAC signatures — know the auth mechanism and how to simulate it. | Yes |
| Token Validity | Understand token expiry, refresh logic, and how your script will handle it. | Yes | |
| Test Environment URL | Use sandbox/test environments provided by third-party APIs (never test against production). | Yes | |
| Credential Restrictions | Ensure test users have correct roles or access boundaries. | Yes | |
| 3. Test Scope Definition | Endpoint Coverage | List of endpoints to be tested (e.g., GET /user, POST /transaction). | Yes |
| Supported Methods | HTTP methods used (GET, POST, PUT, DELETE), content types (JSON, XML). | Yes | |
| Payload Preparation | Prepare realistic sample requests — valid and invalid ones. | Yes | |
| Dependency Impact | Know how third-party API affects downstream flows (e.g., OTP triggers, invoice creation). | Conditional | |
| 4. Rate Limiting & Quotas | Published Rate Limits | Understand daily/monthly quotas, burst capacity, and penalties for overuse. | Yes |
| Throttling Mechanism | Identify how rate-limiting is enforced (HTTP 429, delayed response, token bucket). | Yes | |
| Retry Strategy | Know how your client retries, what backoff is used, and how retries are tracked. | Yes | |
| Quota Management | Track usage vs. quota during testing to avoid unintentional overrun. | Yes | |
| 5. Error & Edge Case Handling | Known Error Codes | Collect all expected error responses (403, 429, 500) and how they are triggered. | Yes |
| Error Injection Scenarios | Optionally simulate network delays, timeouts, or 5xx responses to test your system's resilience. | Conditional | |
| Fallback Logic | Ensure your application has circuit breaker or fallback mechanisms enabled for failures. | Yes | |
| 6. Test Design | Load Profile | Users, requests per second, ramp-up time, total duration — define your load design. | Yes |
| Data Variation | Randomize IDs, names, payloads to avoid duplication or caching issues. | Yes | |
| Think Time | Simulate real usage with pauses between calls. | Yes | |
| Isolation Plan | Avoid running parallel tests that might interfere with quota or behavior. | Yes | |
| 7. Tooling & Execution | Load Tool Selection | Choose a tool (e.g., JMeter, Postman CLI, k6, Locust) that supports required auth and response checks. | Yes |
| Script Parameterization | Support for variable input and dynamic payloads. | Yes | |
| Logging and Debugging | Capture logs for request/response payloads and headers for validation. | Yes | |
| Sandbox Limitations | Understand what’s simulated vs. live in the test environment (e.g., fake payments, email delivery mock). | Yes | |
| 8. Observability | Response Time Monitoring | Track and log latency of each call. | Yes |
| Status Code Distribution | Monitor status codes to detect error spikes. | Yes | |
| SLA Compliance | Compare observed latency to contractual SLAs if available. | Conditional | |
| Alerting Suppression | Prevent automated alerting for expected failures during testing (both your side and theirs). | Conditional | |
| 9. Stakeholder Communication | Notify Provider (if required) | Some vendors require prior notice or approval for load testing (e.g., Stripe, Twilio). | Conditional |
| Internal Coordination | Inform internal teams (Infra, DevOps, QA, Observability) about test window. | Yes | |
| Legal / Compliance Approval | Get internal clearance if the provider or your app handles regulated data (e.g., payments, healthcare). | Conditional | |
| 10. Post-Test Activities | Result Validation | Review latency, error trends, and retry success rate after the test. | Yes |
| Quota Reset / Replenishment | Request additional quota or wait for reset if limits were hit. | Conditional | |
| Test Data Cleanup | If any real data was created (e.g., test users), ensure it is cleaned up. | Yes | |
| Documentation | Capture the entire test configuration and results for future audits or optimization. | Yes |