Appdynamics "Flow Map"
AppDynamics Flow Map Detection
AppDynamics visualizes application architecture through Flow Maps, showing communication between components.
Application Instrumentation
Automated agents instrument application components to collect performance data.
Language-Specific Agents
Support for Java, .NET, PHP, Node.js, and other languages.
Code-Level Monitoring
Agents collect metrics at the code level, including method executions and response times.
Data Aggregation
Metrics are aggregated for representation on the Flow Map.
Real-Time Updates
Agents report metrics in real-time to keep the Flow Map current.
Component Discovery
AppDynamics automatically identifies and maps application components.
Service Endpoints
Detection of service endpoints such as web services, databases, etc.
Backend Identification
Recognition and monitoring of backend services like databases, caches, and message queues.
Container & Cloud Services
Mapping of containers and cloud services infrastructures.
Topology Recognition
Automatic recognition of application topology, dependencies, and service interconnections.
Performance Baselines
Establishes performance benchmarks for normal operation.
Baseline Calculation
Machine learning algorithms calculate the normal performance baselines.
Anomaly Detection
Detectors flag deviations from the baseline to indicate performance issues.
Historical Analysis
Comparison between current and past performance to track trends.
Dynamic Visualization
Flow Map is dynamically created and updated in the AppDynamics Dashboard.
Real-Time Mapping
Depicts live application architecture and traffic flow.
Component Health Indicators
Visual indicators show the health of each component.
Drill-Down Capability
Ability to drill down into specific components for detailed metrics.
Customizable Views
Users can create and customize different views depending on their focus area.
Alerting & Troubleshooting
Flow Map helps identify issues and assists with root cause analysis.
Threshold-Based Alerts
Alerts generated when performance deviates from established thresholds.
Automated Root Cause Analysis
Identification and correlation of performance issues back to the specific code level.
Snapshot Capture
When a performance anomaly is detected, a snapshot of the event is taken for analysis.
Transaction Trace Review
Review trace details for individual transactions to isolate issues.
Appdynamics Error Detection
AppDynamics Error Detection
AppDynamics provides real-time monitoring and automated anomaly detection for applications and infrastructure.
Error Transactions
AppDynamics identifies transactions with errors based on predefined or customized rules.
HTTP Error Codes
Detects transactions that result in HTTP errors like 404 (Not Found) or 500 (Internal Server Error).
Slow Transactions
Identifies transactions that exceed defined response time thresholds.
Stalled Transactions
Catches transactions that do not complete within a specified time, suggesting a hang or deadlock.
Business Transaction Errors
Tracks errors within custom-defined business transactions, which could be logical errors in the application flow.
Error Logs
AppDynamics monitors log files for error messages or specific patterns.
Log Scanning
Scans log files for defined patterns that indicate errors.
Log Level Changes
Detects changes in log verbosity that might indicate increased error conditions.
Custom Error Messages
Tracks customized error messages logged by the application.
Exception Capturing
Captures and analyzes unhandled exceptions in the application code.
Stack Traces
Records stack traces of unhandled exceptions to determine the point of failure.
Exception Rates
Monitors the rate of exceptions to identify spikes which could indicate emerging issues.
Exception Types
Classifies exceptions by type and helps in identifying patterns or recurring issues.
Infrastructure Errors
Links application performance to system-level events.
Hardware Failures
Detects issues such as disk, memory, or network failures.
Resource Saturation
Monitors for signs of CPU, memory, or I/O saturation affecting application performance.
Connectivity Issues
Identifies network connectivity issues that could lead to transaction errors.
Anomaly Detection
AppDynamics uses machine learning to detect and alert on abnormal behavior.
Baseline Deviations
Compares current performance against historical baselines to find anomalies.
Error Rate Anomalies
Detects abnormal increases in error rates for transactions.
Unexpected Patterns
Identifies unusual patterns in application behavior that could suggest errors.