This title slide introduces "E2E Synthetic Testing for Backend (Orchestrator-Based API)", focusing on continuous monitoring and orchestration validation for backend APIs. It is a title slide with no additional subtitle content.

Continuous monitoring and orchestration validation for backend APIs

Source: Akshay Khandelwal

E2E Synthetic Tests involve simulated user journeys that validate APIs end-to-end, ensuring orchestration reliability across backend services in both staging and production environments. Key benefits include proactive issue detection, 24/7 monitoring, and early warnings, as illustrated by a 3D diagram of dual-environment coverage.

Overview of E2E Synthetic Tests

• Synthetic testing: Simulated user journeys validating APIs end-to-end.
• Purpose: Ensures orchestration reliability across backend services.
• Key benefits: Proactive issue detection, 24/7 monitoring, early warnings.
• Test coverage: Comprehensive across staging and production environments.
• 3D diagram illustrates dual-environment monitoring scope.

Source: E2E Synthetic Testing for Backend (Orchestrator-Based API)

The slide outlines a four-step test architecture workflow, starting with GitHub Actions triggering a self-hosted runner for pipeline and environment setup, followed by Karate Framework for API test execution. It then proceeds to Orchestrator API for lifecycle management and ends with a Validation Layer for success/failure checkpoints.

Test Architecture & Setup

Source: Architecture flow: GitHub Actions → Self-hosted Runner → Karate → Orchestrator API → Validation. 3D diagram: Orchestration lifecycle with validation checkpoints.

The slide outlines the Execution Flow and GitHub Actions Pipeline across five phases: Trigger (via Webhook/API/Cron), Build (code checkout and Karate framework setup with env tokens), Test (Karate execution with API calls and validation), Report (Allure dashboard and Excel summaries), and Alert (threshold checks with SquadCast/Slack notifications). It details triggers, actions, environments (Staging vs. Prod), and reporting outputs for each phase, emphasizing dynamic configs and prod-only alerting.

Execution Flow & GitHub Actions Pipeline

Source: 3D sequential flow: Trigger → Build → Test → Report → Alert. Staging vs production workflows. Environment tokens, cron schedules, Allure reporting.

The workflow outlines a notification mechanism starting with Karate Test failure detection, which immediately triggers an alert payload sent to SquadCast for generation (<1s), followed by posting a formatted message with details and @mentions to a Slack Channel (2-5s). It then proceeds to incident management in the SquadCast Dashboard, where an incident is created, responders are assigned, and resolution is tracked ongoing.

Notification and Alerting Mechanism

Source: SquadCast + Slack integration for failure handling

The slide outlines the Environment Strategy with two columns: the Staging Environment uses dedicated config files with test tokens, staging URLs like api-staging.papayaglobal.com, mock data for safe testing, and frequent cron runs to detect regressions early. The Production Environment employs live configs with production tokens and URLs like api.papayaglobal.com for real data validation, 24/7 monitoring, and a shared configuration layer to maintain consistent orchestration logic across both environments.

Environment Strategy

Source: E2E Synthetic Testing for Backend

The slide outlines known issues in a testing or monitoring system, including flaky tests due to network timeouts, false positives from config drift, slow reporting, limited coverage, and alert fatigue from noisy thresholds. For each, it lists causes and mitigations like retry logic, shared configs, async exports, expanded suites, and trend filters.

Known Issues, Limitations & Reporting

Source: E2E Synthetic Testing for Backend

The slide outlines a timeline of next steps for improving the testing pipeline: Phase 1 in Q4 2024 stabilizes the core pipeline with GitHub Actions optimization and reliable executions; Phase 2 in Q1 2025 adds smart retries and alerting; and Phase 3 in Q2 2025 expands test coverage across APIs, performance, and backend. It concludes with ongoing key takeaways on proactive monitoring benefits and contact info for Akshay Khandelwal.

Next Steps & Q&A

Q4 2024: Phase 1: Stabilize Core Pipeline Optimize GitHub Actions, enhance Allure reporting, and ensure reliable daily executions. Q1 2025: Phase 2: Smart Retries & Alerting Implement intelligent retry logic and advanced SquadCast/Slack alerting mechanisms. Q2 2025: Phase 3: Expand Test Coverage Increase API endpoints, add performance metrics, and achieve full backend orchestration coverage. Ongoing: Key Takeaways & Contact Proactive monitoring benefits. Contact: Akshay Khandelwal, akshay.khandelwal@papayaglobal.com.

Source: E2E Synthetic Testing for Backend