Understanding AutomationEdge Architecture
Platform Components
AutomationEdge consists of multiple core components:
- AE Server (Orchestration engine)
- Agents (for job execution)
- Bot Runner (RPA execution layer)
- Plugins and connectors for external systems (e.g., ServiceNow, SAP)
Jobs are scheduled or triggered via AE Server, queued, and delegated to agents or bot runners for execution based on resource availability and configuration.
Execution Pipeline
Workflow execution proceeds in stages:
- Request submission via UI or API
- Routing to appropriate agent
- Execution of workflow steps (Python/Java scripts, HTTP calls, SQL queries)
- Status and logs returned to AE server
Root Causes of Execution Failures
1. Agent Connectivity and Timeout Issues
AutomationEdge agents can lose connectivity due to network partitions, high CPU usage, or Java heap exhaustion. This leads to job retries or indefinite hanging. Errors often appear as:
ERROR: Agent unreachable FATAL: Execution timeout after 600 seconds
2. Plugin Version Mismatch
Workflow steps using outdated or incompatible plugins can fail silently or with unclear errors. This is common after platform upgrades where plugin APIs change but job definitions remain static.
3. RPA Bot Failures
RPA workflows depend on bot runners that emulate UI interactions. Failures occur due to:
- Bot environment misconfiguration
- Resolution or UI element mismatch
- Security patches interfering with automation
Diagnostics and Logging
Workflow Execution Logs
All workflows generate logs stored in the AE Server. Access these via:
AutomationEdge Portal → History → Job Execution Details
Check for common exception types:
- NullPointerException
- SocketTimeoutException
- Plugin step failed: No response from agent
Agent and Bot Runner Logs
Inspect logs located in:
/AutomationEdge/agent/logs/ /AutomationEdge/botRunner/logs/
Look for JVM GC pauses, out-of-memory errors, or failed API responses.
Job Queue Monitoring
From the AE Dashboard, monitor job queue size and stuck executions. A growing queue often indicates agent saturation or deadlocks.
Step-by-Step Fixes
1. Restart Faulty Agents
On the affected host, restart the agent service and monitor reconnection:
sudo systemctl restart ae-agent.service
Ensure the host has stable memory and network connectivity.
2. Revalidate Plugin Versions
Compare plugin versions used in workflows with installed packages. Update and reimport any outdated steps:
AutomationEdge Portal → Admin → Plugins → Update from Marketplace
3. Bot Environment Validation
Use the Bot Verifier tool to ensure display resolution, permissions, and UI bindings are correct. Avoid running bots over RDP sessions with mismatched resolutions.
4. Implement Timeouts and Retries in Workflows
Use timeout steps and error handlers in workflows to gracefully handle transient failures, rather than allowing indefinite hangs.
Architectural Best Practices
Load-Balanced Agent Pools
Distribute agents across multiple nodes and segregate by use-case (e.g., production, dev, RPA-only). Use tagging and routing logic in AE to direct jobs appropriately.
Centralized Monitoring and Alerting
Integrate AE logs with centralized platforms like ELK, Splunk, or Prometheus. Set up alerts on execution failures, agent disconnections, and queue depth.
Version Control for Workflows
Use Git or SVN to version control .aejob files. Maintain deployment pipelines that test workflows against staging AE environments before pushing to production.
Service Account Hygiene
Ensure bot and API execution accounts have non-expiring credentials, least privilege access, and correct desktop environments to avoid runtime failures.
Conclusion
While AutomationEdge offers powerful automation capabilities, production-scale stability requires proactive monitoring, plugin consistency, and resilient job design. By implementing strong diagnostics, isolating RPA failures, and maintaining environment parity, enterprise teams can minimize downtime and ensure smooth automation execution across IT and business domains.
FAQs
1. What causes jobs to remain in the 'Queued' state indefinitely?
This usually indicates that no available agent matches the job's required tag or that all agents are busy. Check agent status and job routing rules.
2. Can a single agent handle both RPA and IT workflows?
Technically yes, but best practice is to isolate RPA and IT process agents for security and stability. UI-based bots often require exclusive desktop access.
3. How do I recover a failed job automatically?
Use error-handling steps within workflows to catch failures and trigger retries or alerts. Also consider using AutomationEdge's SLA breach handler workflows.
4. What plugins are most prone to version mismatch issues?
Custom Java-based plugins and third-party connectors (e.g., SAP, JDBC) are most vulnerable. Always validate post-upgrade using test workflows.
5. Is there a CLI tool for AutomationEdge troubleshooting?
Currently, AutomationEdge relies on portal-based management, but agent logs and job files can be analyzed with external log parsers and scripts for CLI-level diagnostics.