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Alex-CloudOps edited this page Mar 8, 2026 · 1 revision

Roadmap

Planned features, enhancements, and integrations for log-intelligence-engine.

Currently Implemented

Feature Status
Multi-file log ingestion ✅ Complete
Regex-based log parsing ✅ Complete
Severity classification ✅ Complete
Keyword-based classification ✅ Complete
Error & warning rate analysis ✅ Complete
Health status scoring ✅ Complete
Structured JSON report generation ✅ Complete
Config-driven architecture ✅ Complete

Near-Term

Real-Time Log Streaming

Replace batch file processing with real-time log tailing — monitor live log files as entries are written using Python's watchdog library.

from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler

AWS S3 Log Ingestion

Pull log files directly from AWS S3 buckets instead of requiring local file placement — enabling cloud-native log analysis workflows.

import boto3
s3 = boto3.client('s3')
s3.download_file('your-bucket', 'logs/app.log', 'logs/input/app.log')

Improved Timestamp Parsing

Enhance timestamp extraction to support a wider range of log timestamp formats using python-dateutil — enabling time-based filtering and chronological analysis.

Parse Rate Reporting

Include parse rate percentage in the intelligence report summary — making it easy to identify log sources that need regex pattern updates.

Mid-Term

Anomaly Detection

Implement time-window based anomaly detection — identify sudden spikes in error rates within a configurable time window rather than just overall file rates.

CloudWatch Logs Integration

Ship intelligence report data directly to AWS CloudWatch Logs — enabling centralized storage, querying, and alerting on log analysis results.

Pattern Frequency Analysis

Identify the most frequently occurring error and warning messages — surfacing the highest-impact issues rather than just the most recent ones.

Multi-Format Parser Support

Extend parsing to natively support additional log formats:

  • JSON structured logs
  • CSV log exports
  • Windows Event Log exports
  • Kubernetes pod logs

Long-Term

Power BI Dashboard Integration

Export intelligence report data in a format consumable by Power BI — enabling executive-level log health dashboards with trend visualization across multiple runs and log sources. Part of the broader observability-dashboard portfolio project.

REST API Endpoint

Expose a lightweight Flask API so intelligence reports can be queried programmatically by external systems:

GET /api/report/latest
GET /api/report/summary
GET /api/health/{filename}

cloud-telemetry-agent Integration

Ingest structured JSON logs produced by cloud-telemetry-agent directly — creating a closed-loop observability pipeline where telemetry agent logs are automatically analyzed for anomalies.

Unit Test Coverage

Full pytest test suite covering:

  • Parse rate accuracy across log formats
  • Classification correctness for all severity levels
  • Health status scoring logic
  • Report structure validation
  • Config parsing edge cases

Integration Roadmap

Integration Target Repo Status
Cloud Telemetry Agent cloud-telemetry-agent 🔲 Planned
Synthetic Uptime Monitor synthetic-uptime-monitor 🔲 Planned
Incident Alert Pipeline incident-alert-pipeline 🔲 Planned
Observability Dashboard observability-dashboard 🔲 Planned

This engine is one component of a larger CloudOps observability ecosystem. Each portfolio repository is designed to integrate with the others — forming a complete, production-grade monitoring platform.

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