Project Log: The Evolution of CloudSentry AI Fleet
Phase 1: Concept & Problem Identification Modern cloud infrastructure monitoring creates massive log noise during active incidents. Standard incident response pipelines frequently expose raw telemetry, API keys, and JWT tokens across internal monitoring channels. CloudSentry AI Fleet was conceived as a zero-trust, multi-agent control plane designed to intercept, sanitize, analyze, and remediate infrastructure threats in real time without leaking credentials.
Phase 2: Multi-Agent Topology & Model Armor We designed a four-agent orchestration mesh powered by Gemini 3.5 Flash and the Google Agent Development Kit (ADK):
Ingress Guard Agent: Parses incoming log streams and APM traces.
Model Armor Agent: Intercepts raw payloads using regex and guardrails to strip sensitive PII, DB passwords, and authorization headers before sending context to LLMs.
Zero-Trust Policy Agent: Leverages Gemini 3.5 Flash for rapid Root Cause Analysis (RCA) and dynamic severity scoring.
Remediation Sandbox: Auto-generates execution-ready code patches.
Terraform
Auto-Generated Remediation Patch (Terraform HCL)
resource "google_compute_firewall" "isolate_compromised_workload" { name = "deny-sql-injection-vector" network = "default"
deny { protocol = "tcp" ports = ["80", "443"] }
source_ranges = ["192.0.2.0/24"] target_tags = ["quarantine"] } Phase 3: Interactive Control Plane & Real-Time Analytics We constructed the Streamlit dashboard to provide full visibility across the incident lifecycle:
Timeline Stream: Live status dropdowns tracking agent execution steps.
Real-Time Analytics: Visualizing threat vector distribution, resolution latency, and cumulative neutralizations.
Generated Code Patch: Real-time Terraform HCL firewall rules and gcloud CLI commands.
Raw Audit JSON: Complete structured logs for compliance post-mortems.
Phase 4: Cloud Run Deployment & Benchmark Milestone
Deployed containerized microservices directly to Google Cloud Run with Google Secret Manager for key management.
Achieved an average Mean Time To Resolve (MTTR) of 1.2 seconds per telemetry incident.
Completed full submission packaging for the Google Cloud #AllThingsAgentic Hackathon!
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