As promised, We will be providing our original “System Design Course” With Java and Spring Boot.
Curriculum would be same, students comfortable with Python/Javascript can pass on.
Module 1: Foundations of Log Processing
Week 1: Setting Up the Infrastructure
Day 1: Set up development environment (Docker, Git, VS Code) and create project repository
Output: Configured development environment with all necessary tools and initialised repository
Day 2: Implement a basic log generator that produces sample logs at configurable rates
Output: Working log generator that creates timestamped events with configurable throughput
Day 3: Create a simple log collector service that reads local log files
Output: Service that watches log files and detects new entries
Day 4: Implement log parsing functionality to extract structured data from common log formats
Output: Parser for Apache/Nginx logs that extracts timestamp, IP, status code, etc.
Day 5: Build a basic log storage mechanism using flat files with rotation policies
Output: Log storage system with configurable rotation based on size/time
Day 6: Create a simple CLI tool to query and filter collected logs
Output: Command-line utility that can search and filter logs using basic patterns
Day 7: Integrate the components into a simple local log processing pipeline
Output: End-to-end system generating, collecting, storing, and querying logs on a single machine
Week 2: Network-Based Log Collection
Day 8: Implement a TCP server to receive logs over the network
Output: Server accepting TCP connections with log data
Day 9: Create a log shipping client that forwards logs to the TCP server
Output: Client sending logs from one machine to another over TCP
Day 10: Add UDP support for high-throughput log shipping
Output: Server and client handling log transmission over UDP
Day 11: Implement batching in the log shipper to optimize network usage
Output: Client that efficiently batches logs with configurable batch size and interval
Day 12: Add compression to reduce network bandwidth usage
Output: Compressed log transmission with measurable bandwidth reduction
Day 13: Implement TLS encryption for secure log transmission
Output: Encrypted log transmission with certificate management
Day 14: Build a simple load generator and measure throughput of the system
Output: Benchmark report showing logs/second processing capability
Week 3: Data Serialization and Formats
Output: End-to-end JSON log processing with schema validation
Day 16: Implement Protocol Buffers for efficient binary serialization
Output: Log system using Protocol Buffers with measurable performance gain
Day 17: Create Avro serialization support for schema evolution
Output: Log system using Avro with schema versioning demonstration
Day 18: Implement log normalization to convert between formats
Output: Service that can transform logs between different formats (text, JSON, Protobuf, Avro)
Output: Central service for managing and validating log formats and schemas
Day 20: Build compatibility layer for common logging formats (syslog, journald)
Output: Adapters for ingesting logs from system services
Day 21: Implement a simple log enrichment pipeline adding metadata to raw logs
Output: Service that augments logs with additional context (hostname, environment, etc.)
Week 4: Distributed Log Storage
Day 22: Set up a multi-node storage cluster using simple file replication
Output: Log storage distributed across multiple nodes with basic replication
Day 23: Implement partitioning strategy for logs based on source or time
Output: Partitioned storage demonstrating improved query performance
Output: Storage nodes with even distribution of logs using consistent hashing
Output: Storage cluster with automatic leader election recovery
Day 26: Create a cluster membership and health checking system
Output: Self-healing cluster that detects and handles node failures
Day 27: Build a distributed log query system across partitions
Output: Query tool that can retrieve logs from across the cluster
Day 28: Implement read/write quorums for consistency control
Output: Configurable consistency levels with demonstration of tradeoffs
Day 29: Add anti-entropy mechanisms to repair inconsistencies
Output: Background process that detects and fixes replication inconsistencies
Output: Performance report with throughput and latency metrics
Module 2: Scalable Log Processing (Days 31-60)
Week 5: Message Queues for Log Processing
Day 31: Set up a RabbitMQ instance for log message distribution
Output: Working message queue for log distribution
Output: Log collector publishing to message queues
Output: Workers consuming and processing logs from queues
Day 34: Add consumer acknowledgments and redelivery mechanisms
Output: Reliable message processing with failure handling
Day 35: Implement different exchange types for routing patterns
Output: Topic-based routing of logs to different processing pipelines
Day 36: Add dead letter queues for handling failed processing
Output: System capturing and managing failed log processing attempts
Output: Demonstration of high-priority logs bypassing normal processing queues
Week 6: Stream Processing with Kafka
Output: Working Kafka cluster for high-throughput log streaming
Output: Log shippers sending data to Kafka topics
Output: Consumers reading and processing logs from Kafka
Output: Parallel processing across multiple consumer instances
Output: System guaranteeing no duplicate log processing
Output: Compacted topics maintaining latest state of entities
Day 44: Create a real-time monitoring dashboard using Kafka Streams
Output: Dashboard showing live statistics of log processing
Week 7: Distributed Log Analytics
Day 45: Implement a simple MapReduce framework for batch log analysis
Output: System performing word count and pattern frequency analysis
Output: Analytics calculating statistics over time windows
Output: Real-time trend analysis with sliding windows
Output: Session analysis identifying user behavior patterns
Output: System detecting unusual patterns in logs
Output: Alerting system triggered by specific log conditions
Output: Web interface displaying key metrics and trends
Week 8: Distributed Log Search
Output: Search index enabling quick text searches across logs
Output: Partitioned search index spanning multiple machines
Output: Parser and executor for SQL-like queries on logs
Output: Search system with filtering by multiple dimensions
Output: Search system with minimal indexing latency
Output: Search system with relevance scoring
Output: RESTful API for querying log data
Week 9: High Availability and Fault Tolerance
Day 59: Implement active-passive failover for critical components
Output: Automatic failover demonstration with minimal downtime
Output: Log replication across simulated regions
Module 3: Advanced Log Processing Features (Days 61-90)
Week 9 (continued): High Availability and Fault Tolerance
Day 61: Add circuit breakers for handling component failures
Output: System maintaining availability when components fail
Day 62: Implement backpressure mechanisms for load management
Output: System gracefully handling traffic spikes
Output: Test suite that randomly introduces failures to verify resilience
Week 10: Security and Compliance
Output: Authentication and authorization system for log access
Output: Encryption system protecting PII in logs
Output: System automatically redacting sensitive information
Output: Immutable record of who accessed what log data
Output: Automated system for enforcing retention periods
Day 69: Add GDPR compliance features (right to be forgotten)
Output: System capable of selectively removing specific user data
Output: Automated report generation for compliance audits
Week 11: Performance Optimization
Day 71: Profile and optimize log ingestion pipeline
Output: Performance improvements with before/after metrics
Day 72: Implement adaptive batching based on system load
Output: Self-tuning batch sizes maximizing throughput
Day 73: Add caching layers for frequent queries
Output: Query response time improvements with caching
Day 74: Optimize storage format for read/write patterns
Output: Storage format optimized for specific workloads
Day 75: Implement bloom filters for efficient existence checking
Output: Faster membership queries with bloom filters
Day 76: Add delta encoding for log storage efficiency
Output: Reduced storage requirements with delta compression
Day 77: Implement adaptive resource allocation
Output: System that scales resources based on demand
Week 12: Advanced Analytics
Day 78: Build a machine learning pipeline for log classification
Output: ML model classifying logs by severity/category
Day 79: Implement clustering for pattern discovery
Output: System identifying common patterns in logs
Day 80: Add predictive analytics for forecasting
Output: Predictions of system behavior based on log patterns
Day 81: Implement a recommendation system for troubleshooting
Output: System suggesting fixes based on similar past incidents
Day 82: Create correlation analysis across different log sources
Output: System identifying relationships between events in different logs
Day 83: Build a root cause analysis engine
Output: System tracing issues to their origin based on logs
Day 84: Implement natural language processing for log understanding
Output: System extracting meaning from free-text log messages
Module 4: Building a Complete Distributed Log Platform (Days 91-120)
Week 13: API and Service Layer
Day 85: Design and implement a RESTful API for the log platform
Output: Complete API documentation and implementation
Day 86: Add GraphQL support for flexible queries
Output: GraphQL endpoint for complex log queries
Day 87: Implement rate limiting and quota management
Output: Protection against API abuse with configurable limits
Day 88: Create SDK libraries for common languages
Output: Client libraries for Java, Python, and JavaScript
Day 89: Build a CLI tool for platform interaction
Output: Command-line client for log system management
Day 90: Implement webhook notifications for log events
Output: Notification system pushing events to external systems
Day 91: Add batch API operations for efficiency
Output: API endpoints supporting bulk operations
Week 14: Web Interface and Dashboards
Day 92: Create a basic web UI for log viewing
Output: Web interface for browsing logs
Day 93: Implement real-time log streaming to the UI
Output: Live log tail feature in the web interface
Day 94: Add advanced search interface with filters
Output: Rich search UI with multiple filtering options
Day 95: Create customizable dashboards
Output: User-configurable dashboards for monitoring
Day 96: Implement data visualization components
Output: Charts and graphs showing log patterns and trends
Day 97: Add saved searches and alerts in the UI
Output: Feature for saving searches and configuring alerts
Day 98: Implement user preferences and settings
Output: Personalized user experience with saved preferences
Week 15: Advanced Operational Features
Day 99: Create a health monitoring system for the platform
Output: Internal monitoring tracking all component health
Day 100: Implement automated scaling policies
Output: Self-scaling system adjusting to load changes
Day 101: Add blue/green deployment capabilities
Output: Zero-downtime upgrade process
Day 102: Implement A/B testing framework for features
Output: System for gradually rolling out new features
Day 103: Create comprehensive metrics collection
Output: Detailed performance metrics for all components
Day 104: Build cost allocation and usage reporting
Output: Reports showing resource usage by tenant/user
Day 105: Implement automated backup and recovery
Output: Scheduled backups with verified restore capability
Week 16: Multi-tenancy and Enterprise Features
Day 106: Design and implement multi-tenant architecture
Output: System supporting multiple isolated tenants
Day 107: Add tenant isolation and resource quotas
Output: Resource limits enforced by tenant
Day 108: Implement tenant-specific configurations
Output: Per-tenant customization capabilities
Day 109: Create tenant onboarding/offboarding processes
Output: Automated tenant provisioning and cleanup
Day 110: Add tenant usage reporting and billing
Output: Usage-based billing system with detailed reports
Day 111: Implement single sign-on integration
Output: SSO support for popular providers (Google, Okta)
Day 112: Create enterprise integration features (LDAP, Active Directory)
Output: Enterprise authentication integration
Week 17: Storage and Retention Management
Day 113: Implement tiered storage for log data
Output: Automatic movement of logs between storage tiers
Day 114: Add data lifecycle policies
Output: Policy-based data management across its lifecycle
Day 115: Create historical data archiving
Output: Archiving system for long-term storage
Day 116: Implement data restoration from archives
Output: Process for retrieving archived logs when needed
Day 117: Add storage optimization for cost reduction
Output: Automated storage optimization with cost metrics
Day 118: Create storage usage forecasting
Output: Predictions of future storage requirements
Day 119: Implement cross-region data replication
Output: Geographic redundancy for disaster recovery
Day 120: Add data sovereignty compliance features
Output: Controls ensuring data stays in designated regions
Module 5: Integration and Ecosystem (Days 121-150)
Week 18: Log Source Integration
Day 121: Create collectors for Linux system logs
Output: Linux agent collecting system and service logs
Day 122: Add Windows event log collection
Output: Windows agent for event log integration
Day 123: Implement cloud service log collection (AWS CloudWatch)
Output: Integration pulling logs from AWS services
Day 124: Add Azure monitoring integration
Output: Connection to Azure Monitor log sources
Day 125: Create Google Cloud logging integration
Output: Integration with Google Cloud Logging
Day 126: Implement container log collection (Docker, Kubernetes)
Output: Container-aware log collection system
Day 127: Add database audit log collection
Output: Collectors for major database audit logs
Week 19: Application Integration
Day 128: Create logging libraries for major languages
Output: Client libraries for Java, Python, Node.js, and .NET
Day 129: Implement structured logging helpers
Output: Tools helping developers create structured logs
Day 130: Add application performance monitoring integration
Output: Combined logs and metrics for application monitoring
Day 131: Create distributed tracing integration
Output: Trace context propagation in logs
Day 132: Implement error tracking features
Output: Automatic grouping and tracking of similar errors
Day 133: Add deployment and release tracking
Output: System correlating logs with software releases
Day 134: Create feature flag status logging
Output: Automatic logging of feature flag state
Week 20: External System Integration
Day 135: Implement Slack notification integration
Output: Alerts and notifications delivered to Slack
Day 136: Add email alerting and reporting
Output: Scheduled and triggered email reports
Day 137: Create PagerDuty/OpsGenie integration
Output: Critical alerts routed to on-call systems
Day 138: Implement JIRA/ServiceNow ticket creation
Output: Automatic ticket creation from log events
Day 139: Add Webhook support for custom integrations
Output: Generic webhook system for third-party services
Day 140: Create data export to S3/blob storage
Output: Automated exports to cloud storage
Day 141: Implement metrics export to monitoring systems
Output: Integration with Prometheus, Datadog, etc.
Week 21: Advanced Processing Integrations
Day 142: Create Elasticsearch integration for advanced search
Output: Log forwarding and querying with Elasticsearch
Day 143: Add Apache Spark integration for big data processing
Output: Spark jobs analyzing log data at scale
Day 144: Implement machine learning pipeline with TensorFlow
Output: ML models trained on log data for prediction
Day 145: Create real-time stream processing with Flink
Output: Complex event processing on log streams
Day 146: Add time series database integration
Output: Metrics extraction and storage in InfluxDB/TimescaleDB
Day 147: Implement business intelligence tool integration
Output: Connections to Tableau, PowerBI, etc.
Day 148: Create natural language queries with NLP
Output: System answering questions asked in plain English
Week 22: Deployment and Operations
Day 149: Build Kubernetes deployment definitions
Output: Complete K8s deployment files for the platform
Day 150: Create cloud-specific deployment templates
Output: Terraform/CloudFormation for AWS, Azure, GCP
Module 6: Specialized Log Processing Use Cases (Days 151-180)
Week 22 (continued): Deployment and Operations
Day 151: Implement GitOps workflow for the platform
Output: CI/CD pipeline with GitOps deployment
Day 152: Create operator pattern for Kubernetes management
Output: Custom K8s operator for the log platform
Day 153: Add infrastructure monitoring integration
Output: Combined infrastructure and log monitoring
Day 154: Implement disaster recovery procedures
Output: Tested DR plan with RTO/RPO measurements
Day 155: Create capacity planning tools
Output: Resource forecasting based on log volume trends
Week 23: Security Log Processing
Day 156: Implement SIEM (Security Information Event Management) features
Output: Security-focused log analysis capabilities
Day 157: Add threat detection rules
Output: Rule engine detecting security threats in logs
Day 158: Create user behavior analytics
Output: System detecting anomalous user behavior
Day 159: Implement IOC (Indicators of Compromise) scanning
Output: Log scanning for known threat indicators
Day 160: Add automated incident response
Output: Playbooks responding to security events
Day 161: Create security compliance reporting
Output: Automated reports for security frameworks (PCI, SOC2)
Day 162: Implement log-based network traffic analysis
Output: Network security monitoring using log data
Week 24: IT Operations Use Cases
Day 163: Build service dependency mapping
Output: Automatic discovery of system dependencies
Day 164: Create change impact analysis
Output: System predicting impacts of changes
Day 165: Implement SLA monitoring and reporting
Output: Real-time SLA tracking with alerting
Day 166: Add capacity management features
Output: Resource usage analysis and forecasting
Day 167: Create automated root cause analysis
Output: System identifying causes of incidents
Day 168: Implement IT asset tracking with logs
Output: Asset inventory derived from log data
Day 169: Build configuration management database integration
Output: CMDB populated with data from logs
Week 25: Business Analytics Use Cases
Day 170: Implement user journey tracking
Output: User flow analysis from application logs
Day 171: Create conversion funnel analysis
Output: Visualization of user conversion steps
Day 172: Add revenue impact analysis
Output: Correlation between system issues and revenue
Day 173: Implement feature usage analytics
Output: Reports showing feature adoption rates
Day 174: Create A/B test analysis framework
Output: Statistical analysis of experiment results
Day 175: Add customer experience monitoring
Output: Metrics for user experience derived from logs
Day 176: Build executive dashboards for business metrics
Output: C-level views of system performance
Week 26: IoT and Edge Log Processing
Day 177: Implement edge log collection for limited connectivity
Output: Log collector working in intermittent network conditions
Day 178: Create bandwidth-efficient log transport
Output: Log shipping optimized for constrained networks
Day 179: Add device state tracking and management
Output: System managing IoT device state from logs
Day 180: Implement geospatial log analysis
Output: Location-based analysis of log events
Module 7: Advanced Distributed Systems Concepts (Days 181-210)
Week 27: Consensus and Coordination
Day 181: Implement Raft consensus algorithm
Output: Working Raft implementation for cluster coordination
Day 182: Create a distributed lock service
Output: Lock service preventing concurrent operations
Day 183: Add distributed semaphores
Output: Resource limiting across distributed components
Day 184: Implement lease-based resource management
Output: Time-bounded ownership of resources
Day 185: Create a service discovery mechanism
Output: Dynamic discovery of system components
Day 186: Add version vectors for conflict resolution
Output: System handling concurrent updates with version vectors
Day 187: Implement a gossip protocol for state dissemination
Output: Efficient information spreading across the cluster
Week 28: Advanced Consistency Models
Day 188: Implement linearizable consistency
Output: Storage system with linearizable guarantees
Day 189: Create causal consistency mechanisms
Output: System preserving causal relationships
Day 190: Add eventual consistency with conflict resolution
Output: System converging despite concurrent updates
Day 191: Implement CRDT (Conflict-free Replicated Data Types)
Output: Data types that automatically resolve conflicts
Day 192: Create tunable consistency levels
Output: API with selectable consistency guarantees
Day 193: Add transaction support across partitions
Output: Cross-partition atomic operations
Day 194: Implement read/write quorums with sloppy quorum
Output: System maintaining consistency during partitions
Week 29: Advanced Fault Tolerance
Day 195: Create a phi-accrual failure detector
Output: Adaptive failure detection system
Day 196: Implement Byzantine fault tolerance
Output: System tolerating malicious nodes
Day 197: Add automatic leader election with prioritization
Output: Leader election preserving important properties
Day 198: Create a consensus-based configuration management
Output: Distributed configuration with atomic updates
Day 199: Implement partition-aware request routing
Output: System maintaining availability during network splits
Day 200: Add multi-region consensus groups
Output: Consensus spanning geographical regions
Day 201: Create a split-brain resolver
Output: System recovering from network partitions
Week 30: Advanced Scalability Patterns
Day 202: Implement intelligent request routing
Output: Request router directing traffic optimally
Day 203: Create adaptive load shedding
Output: System dropping less important work under load
Day 204: Add predictive resource scaling
Output: Scaling before resource exhaustion occurs
Day 205: Implement data rebalancing for even distribution
Output: System redistributing data as cluster changes
Day 206: Create workload-aware partitioning
Output: Partitioning scheme adapted to access patterns
Day 207: Add multi-dimensional sharding
Output: Data sharded by multiple attributes simultaneously
Day 208: Implement locality-aware data placement
Output: Data placement optimizing for access locality
Week 31: Real-time Processing Optimizations
Day 209: Create time-series optimized storage
Output: Storage format specialized for time-series data
Day 210: Implement real-time aggregation with decay functions
Output: Aggregates giving more weight to recent data
Module 8: System Observability and Testing (Days 211-240)
Week 31 (continued): Real-time Processing Optimizations
Day 211: Add approximate query processing for speed
Output: Fast approximate answers for large-scale queries
Day 212: Create pre-computed aggregates and materialized views
Output: Accelerated queries using pre-computed results
Day 213: Implement streaming window joins
Output: Real-time joining of different event streams
Week 32: Advanced Monitoring
Day 214: Build a metrics collection framework
Output: System collecting metrics from all components
Day 215: Create service-level objective tracking
Output: SLO/SLI monitoring with alerting
Day 216: Add distributed tracing for request flows
Output: End-to-end request tracing across components
Day 217: Implement advanced log correlation
Output: Automatic correlation of related log events
Day 218: Create anomaly detection for system metrics
Output: Automatic detection of unusual system behavior
Day 219: Add predictive failure analysis
Output: System predicting failures before they happen
Day 220: Implement dependency-aware monitoring
Output: Monitoring system understanding service relationships
Week 33: Testing and Verification
Day 221: Create distributed system test framework
Output: Framework for testing distributed components
Day 222: Implement property-based testing
Output: Tests verifying system properties under random inputs
Day 223: Add chaos engineering capabilities
Output: Tools for injecting controlled failures
Day 224: Create partition testing tools
Output: Tests for system behavior during network partitions
Day 225: Implement clock skew testing
Output: Tests for system behavior with unsynchronized clocks
Day 226: Add load and stress testing framework
Output: System for testing performance under extreme load
Day 227: Create long-running reliability tests
Output: Tests verifying stability over extended periods
Week 34: Performance Analysis
Day 228: Build a distributed profiling system
Output: Profiler capturing performance across components
Day 229: Implement distributed request tracing
Output: Detailed latency breakdown for requests
Day 230: Add flame graph generation for bottleneck analysis
Output: Visualizations showing processing bottlenecks
Day 231: Create benchmark suite for key operations
Output: Standardized benchmarks for system capabilities
Day 232: Implement A/B performance testing
Output: Framework comparing performance of alternatives
Day 233: Add resource utilization analysis
Output: Reports identifying resource efficiency
Day 234: Create performance regression detection
Output: Automated detection of performance degradation
Week 35: Debugging and Diagnostics
Day 235: Implement distributed system snapshot capture
Output: Tool capturing global state for debugging
Day 236: Create context-aware log enrichment
Output: Logs automatically enhanced with relevant context
Day 237: Add post-mortem debugging tools
Output: Tools for analyzing system state after failures
Day 238: Implement real-time debugging capabilities
Output: Features for debugging production systems safely
Day 239: Create visualization for distributed executions
Output: Visual representation of distributed processes
Day 240: Add root cause analysis automation
Output: System suggesting likely causes of problems
Module 9: Advanced Performance and Optimization (Days 241-270)
Week 36: Memory and CPU Optimization
Day 241: Implement memory pool allocators
Output: Efficient memory management reducing GC overhead
Day 242: Create lock-free data structures
Output: High-performance concurrent data structures
Day 243: Add CPU cache-friendly algorithms
Output: Optimized algorithms maximizing CPU cache efficiency
Day 244: Implement SIMD optimizations
Output: Performance improvements using vector instructions
Day 245: Create thread affinity management
Output: Thread scheduling optimized for NUMA architectures
Day 246: Add adaptive batch sizing
Output: Self-tuning batch sizes based on system load
Day 247: Implement zero-copy processing pipelines
Output: Processing pipeline eliminating unnecessary copies
Week 37: Storage Optimization
Day 248: Create LSM-tree based storage engine
Output: Storage engine optimized for write-heavy workloads
Day 249: Implement columnar storage for analytics
Output: Column-oriented storage for analytical queries
Day 250: Add bloom filters for membership testing
Output: Efficient filtering using probabilistic data structures
Day 251: Create hierarchical storage management
Output: Automatic data movement between storage tiers
Day 252: Implement incremental compaction strategies
Output: Storage compaction minimizing performance impact
Day 253: Add compression algorithm selection based on data
Output: Adaptive compression using optimal algorithms
Day 254: Create append-only immutable data structures
I do not see 254 days of lessons yet. There are 78 lessons. Some of the later are not linked from the curriculum page. Perhaps, the others are on the way but I'm not sure.