This document outlines the Functional Requirements (FRs) and Non-Functional Requirements (NFRs) for the Self-Healing Distributed System project.
Functional requirements define the specific behaviors, services, and core capabilities that the system must execute.
- Heartbeat Mechanism: The system must implement a lightweight heartbeat protocol where worker nodes periodically check in with the orchestrator/manager node.
- Anomaly Detection: The system must automatically detect node failures, network partitions, resource exhaustion (CPU/Memory spikes), and stalled processes.
- Fault Metric Logging: The system must log health metrics continuously to a centralized time-series datastore for real-time analysis.
- Process Restart: If a critical service process crashes or hangs on an otherwise healthy node, the local agent must attempt to restart it automatically.
- Node Re-provisioning: If a node becomes entirely unresponsive or suffers hardware degradation, the orchestrator must spin up a replacement node and deprecate the failed one.
- State Reconciliation: The system must feature a control loop (similar to Kubernetes) that continuously compares the actual state of the cluster against the desired state and applies fixes until they match.
- Data Redistribution: Upon node failure, the system must trigger automated data replication or re-sharding to ensure no data loss occurs and the replication factor is maintained.
- Automated Failover: Traffic routed to a degraded or dead node must be dynamically rerouted to healthy backup nodes via an automated service registry/load balancer rewrite.
- Circuit Breaking: The system must support circuit-breaking capabilities to isolate failing services and prevent cascading failures across the network.
- Rate Limiting & Throttling: During high-stress recovery windows, the system must functionally throttle non-essential traffic to prioritize stabilization protocols.
- Manual Override: System administrators must have the ability to pause automated self-healing actions to perform manual maintenance.
- Notification Engine: The system must dispatch immediate webhooks, emails, or Slack alerts whenever a critical fault is detected and when a self-healing action is attempted (successful or failed).
Non-functional requirements specify the criteria, quality attributes, and operational constraints used to judge the operation of the system.
- Uptime: The system must achieve a minimum of 99.99% availability (four nines) annually.
- No Single Point of Failure (SPOF): The orchestrator/control plane must be deployed in a highly available, clustered configuration (e.g., using a consensus algorithm like Raft or Paxos).
- Detection Time (MTTD): The system must detect a node crash or silent failure within 5 seconds of occurrence.
- Recovery Time (MTTR): Simple process-level recovery must complete within 2 seconds. Full node re-provisioning and traffic rerouting must complete within 60 seconds.
- Horizontal Scaling: The monitoring and self-healing framework must scale linearly up to 1,000 cluster nodes without introducing more than a 2% CPU overhead per node.
- Data Durability: The system must guarantee Zero Data Loss (RPO = 0) for committed data writes by using a minimum replication factor of 3 across distinct fault domains.
- Idempotency: All self-healing actions (e.g., node creation scripts, process restarts) must be completely idempotent to prevent race conditions during simultaneous network partitions.
- Secure Node Joining: New nodes provisioned by the self-healing system must authenticate using secure, short-lived mutual TLS (mTLS) tokens before being admitted to the cluster.
- Least Privilege Access: The automation agents executing recovery commands must operate under strict role-based access control (RBAC), limiting their permissions solely to necessary infrastructure management functions.
- Audit Trail: Every automated remediation action taken by the system must be logged with a unique transaction ID, timestamp, root cause analysis, and final outcome for retrospective debugging.
- Clean Code Architecture: The codebase must maintain modularity, separating the monitoring fabric, decision engine, and infrastructure providers to allow seamless swapping of cloud backends (e.g., AWS, GCP, bare metal).