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.