You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
SentraCore is a **Local System Behavior Intelligence Platform** for Windows. It continuously analyzes system telemetry to understand performance behavior, detect statistical anomalies, explain the root cause of slowdowns, and forecast resource exhaustion before it occurs.
3
+
SentraCore is a local system behavior intelligence platform for Windows that continuously analyzes system telemetry to understand performance behavior, detect statistical anomalies, explain performance degradation, and estimate future resource exhaustion before it impacts usability.
4
4
5
-
Unlike traditional monitoring tools that display raw snapshots, SentraCore interprets system behavior over time — answering not just *what* is happening, but *why* it is happening and *when* it will become critical.
5
+
Unlike traditional monitoring tools that focus on raw real-time snapshots, SentraCore interprets system behavior over time — helping users understand not only what is happening, but also why it is happening, how severe it is, and how it may affect system responsiveness.
6
+
7
+
---
8
+
9
+
## Overview
10
+
11
+
SentraCore combines:
12
+
13
+
- Real-time telemetry collection
14
+
- Adaptive baseline learning
15
+
- Statistical anomaly detection
16
+
- Correlation-based root cause analysis
17
+
- Predictive resource forecasting
18
+
- Historical system behavior tracking
19
+
- User-impact focused diagnostics
20
+
21
+
The platform is designed as a lightweight local intelligence layer running continuously in the background with minimal overhead.
6
22
7
23
---
8
24
9
25
## Current Status
10
26
11
-
**All six phases are complete and production-ready.**
27
+
SentraCore is actively developed and currently includes a production-ready monitoring engine, behavioral intelligence system, predictive analysis pipeline, and Windows desktop dashboard.
|Phase 3 |Correlation & Root Cause Engine|Complete|
18
-
|Phase 4 | Prediction & Risk Engine |Complete|
19
-
|Phase 5 |Flutter Dashboard System | Complete|
20
-
|Phase 6 | Productization Layer | Complete|
29
+
|Layer| Status |
30
+
|---|---|
31
+
| Core Telemetry Engine |Stable|
32
+
| Behavioral Intelligence Layer |Stable|
33
+
| Correlation & Root Cause Analysis|Stable|
34
+
|Predictive Risk Engine |Stable|
35
+
| Flutter Desktop Dashboard | Stable|
36
+
|Windows Packaging & Installer | Stable|
21
37
22
38
---
23
39
24
-
## What SentraCore Does
40
+
## Core Capabilities
25
41
26
42
### System Stability Index
27
-
The primary dashboard metric is the **System Stability Index (1–100)**. Unlike a raw CPU percentage, this score synthesises instantaneous resource pressure, statistical anomaly deviation, and forward-looking predictive risk into a single, actionable number. A score of 100 is perfect health.
43
+
44
+
SentraCore generates a unified **System Stability Index (1–100)** representing overall system health.
45
+
46
+
The score combines:
47
+
- Resource pressure
48
+
- Behavioral deviation
49
+
- Sustained stress trends
50
+
- Predictive degradation risk
51
+
52
+
Rather than exposing isolated metrics, the Stability Index provides a high-level understanding of system condition and responsiveness.
53
+
54
+
---
55
+
56
+
### Behavioral Intelligence
57
+
58
+
The platform continuously models normal system behavior using adaptive baselines.
59
+
60
+
SentraCore learns:
61
+
- Typical CPU activity
62
+
- Memory consumption patterns
63
+
- Disk activity behavior
64
+
- Time-of-day workload trends
65
+
66
+
This allows the system to distinguish between expected workload spikes and abnormal behavior.
67
+
68
+
---
69
+
70
+
### Statistical Anomaly Detection
71
+
72
+
SentraCore uses statistical deviation analysis to identify abnormal system states.
73
+
74
+
Detection includes:
75
+
- Sustained deviation from baseline
76
+
- Resource volatility spikes
77
+
- Abnormal trend acceleration
78
+
- Multi-resource pressure correlation
79
+
80
+
Anomaly sensitivity can be configured by the user.
81
+
82
+
---
28
83
29
84
### Root Cause Analysis
30
-
When the system enters a high-stress state and an alert fires, SentraCore's Correlation Engine automatically generates a **Root Cause Analysis** — identifying the primary bottleneck (CPU, Memory, or Disk), the most likely offending process, and the system event that triggered the degradation.
85
+
86
+
When degradation events occur, the Correlation Engine analyzes:
87
+
88
+
- Process activity
89
+
- Resource contention
90
+
- System event timing
91
+
- Trend alignment
92
+
93
+
The engine then generates a ranked explanation of likely contributing factors.
94
+
95
+
Example:
96
+
97
+
- Elevated memory pressure from browser processes
98
+
- Increased disk activity from indexing services
99
+
- Sustained CPU saturation from background workloads
100
+
101
+
---
31
102
32
103
### Predictive Forecasting
33
-
The Prediction Engine uses Exponential Moving Averages on trend slopes to generate **Time-to-Exhaustion (ETA)** countdowns. If memory is growing at a sustained rate, SentraCore will warn you that saturation is expected in X seconds, not just that usage is high.
34
104
35
-
### Adaptive Baseline Learning
36
-
SentraCore does not use static thresholds. It learns what is *normal* for the specific machine it runs on, segmented by time-of-day. A CPU spike at 2 AM during a known backup job is treated differently from the same spike at 2 PM.
105
+
SentraCore estimates future resource exhaustion using trend-based forecasting models.
106
+
107
+
Capabilities include:
108
+
- Memory saturation estimation
109
+
- CPU trend projection
110
+
- Disk pressure forecasting
111
+
- Time-to-exhaustion estimation (ETA)
112
+
113
+
This enables proactive alerts before severe degradation occurs.
37
114
38
115
---
39
116
40
-
##Architecture
117
+
### Historical Monitoring (Logbook)
41
118
42
-
SentraCore is structured as two decoupled layers communicating over a local WebSocket and REST API:
119
+
The dashboard automatically records and visualizes historical system behavior over time.
43
120
44
-
```
121
+
Supported views include:
122
+
- CPU pressure history
123
+
- Memory pressure history
124
+
- Disk pressure history
125
+
- Interactive time filtering
126
+
- Date-range analysis
127
+
128
+
History is stored locally on the machine.
129
+
130
+
---
131
+
132
+
### Process Intelligence
133
+
134
+
Processes are evaluated using sustained impact analysis rather than instantaneous usage alone.
135
+
136
+
Features include:
137
+
- Process grouping by executable
138
+
- Sustained resource contribution tracking
139
+
- Ranked impact analysis
140
+
- Process lifecycle cleanup for stale PIDs
141
+
- Expandable per-process details
142
+
143
+
---
144
+
145
+
### Alerting & Diagnostics
146
+
147
+
SentraCore includes a real-time alerting and diagnostics system.
148
+
149
+
Features:
150
+
- Alert history tracking
151
+
- Root cause summaries
152
+
- WebSocket-powered live alerts
153
+
- Windows desktop notifications
154
+
- Diagnostics timeline integration
155
+
156
+
---
157
+
158
+
### Safeguard System (Optional)
159
+
160
+
An optional safeguard layer can automatically terminate selected user-approved processes during severe degradation scenarios.
161
+
162
+
Features:
163
+
- Live process selection
164
+
- Flexible executable matching
165
+
- User-controlled targeting
166
+
- Logged termination outcomes
167
+
- Safety-focused restrictions
168
+
169
+
---
170
+
171
+
## System Architecture
172
+
173
+
SentraCore is structured as two decoupled layers communicating over local APIs and WebSockets.
0 commit comments