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Buy this course — $299.00Hands On System Design with Distributed Systems Implementation
📊 Intermediate
📚 507 Lessons
👨🏫 Course Instructor
Why This Course?
Comprehensive course covering essential topics in system design and architecture.
What You'll Learn
Real-world projects and applications that demonstrate practical skills.
Who This Course Is For
Software engineers, system architects, and technical professionals looking to enhance their skills.
Level
Intermediate
Lessons
507
in 10 modules
MODULE 1
Foundations of Log Processing
▼
📅 Setting Up the Infrastructure
🔒
Day 1:
Day 1: Set up development environment (Docker, Git, VS Code) and create project repositoryOutput: Configured development environment with all necessary tools and initialized repository
PRO
🔒
Day 2:
Day 2: Implement a basic log generator that produces sample logs at configurable ratesOutput: Working log generator that creates timestamped events with configurable throughput
PRO
🔒
Day 3:
Day 3: Create a simple log collector service that reads local log filesOutput: Service that watches log files and detects new entries
PRO
MODULE 1
Foundations of Log Processing
▼
📅 Lessons
🔒
Day 4:
Day 4: Implement log parsing functionality to extract structured data from common log formats
PRO
🔒
Day 5:
Day 5: Build a basic log storage mechanism using flat files with rotation policies
PRO
🔒
Day 6:
Day 6: Create a simple CLI tool to query and filter collected logs
PRO
🔒
Day 7:
Day 7: Integrate the components into a simple local log processing pipeline
PRO
📅 Network-Based Log Collection
🔒
Day 8:
Day 8: Implement a TCP server to receive logs over the network
PRO
🔒
Day 9:
Day 9: Create a log shipping client that forwards logs to the TCP server
PRO
🔒
Day 10:
Day 10: Add UDP support for high-throughput log shipping
PRO
🔒
Day 11:
Day 11: Implement batching in the log shipper to optimize network usage
PRO
🔒
Day 12:
Day 12: Add compression to reduce network bandwidth usage
PRO
🔒
Day 13:
Day 13: Implement TLS encryption for secure log transmission
PRO
🔒
Day 14:
Day 14: Build a simple load generator and measure throughput of the system
PRO
📅 Data Serialization and Formats
🔒
Day 15:
Day 15: Add JSON support for structured log data
PRO
🔒
Day 16:
Day 16: Implement Protocol Buffers for efficient binary serialization
PRO
🔒
Day 17:
Day 17: Create Avro serialization support for schema evolution
PRO
🔒
Day 18:
Day 18: Implement log normalization to convert between formats
PRO
🔒
Day 19:
Day 19: Add a schema registry service for format management
PRO
🔒
Day 20:
Day 20: Build compatibility layer for common logging formats (syslog, journald)
PRO
🔒
Day 21:
Day 21: Implement a simple log enrichment pipeline adding metadata to raw logs
PRO
📅 Distributed Log Storage
🔒
Day 22:
Day 22: Set up a multi-node storage cluster using simple file replication
PRO
🔒
Day 23:
Day 23: Implement partitioning strategy for logs based on source or time
PRO
🔒
Day 24:
Day 24: Add consistent hashing for balanced distribution
PRO
🔒
Day 25:
Day 25: Implement leader election for cluster management
PRO
🔒
Day 26:
Day 26: Create a cluster membership and health checking system
PRO
🔒
Day 27:
Day 27: Build a distributed log query system across partitions
PRO
🔒
Day 28:
Day 28: Implement read/write quorums for consistency control
PRO
🔒
Day 29:
Day 29: Add anti-entropy mechanisms to repair inconsistencies
PRO
🔒
Day 30:
Day 30: Measure and optimize cluster performance
PRO
MODULE 2
Scalable Log Processing
▼
📅 Message Queues for Log Processing
🔒
Day 31:
Day 31: Set up a RabbitMQ instance for log message distribution
PRO
🔒
Day 32:
Day 32: Create producers to send logs to message queues
PRO
🔒
Day 33:
Day 33: Implement consumers to process logs from queues
PRO
🔒
Day 34:
Day 34: Add consumer acknowledgments and redelivery mechanisms
PRO
🔒
Day 35:
Day 35: Implement different exchange types for routing patterns
PRO
🔒
Day 36:
Day 36: Add dead letter queues for handling failed processing
PRO
🔒
Day 37:
Day 37: Implement priority queues for critical log messages
PRO
📅 Stream Processing with Kafka
🔒
Day 38:
Day 38: Set up a Kafka cluster for log streaming
PRO
🔒
Day 39:
Day 39: Create Kafka producers for log ingestion
PRO
🔒
Day 40:
Day 40: Implement Kafka consumers for log processing
PRO
🔒
Day 41:
Day 41: Set up partitioning and consumer groups
PRO
🔒
Day 42:
Day 42: Add exactly-once processing semantics
PRO
🔒
Day 43:
Day 43: Implement log compaction for state management
PRO
🔒
Day 44:
Day 44: Create a real-time monitoring dashboard using Kafka Streams
PRO
📅 Distributed Log Analytics
🔒
Day 45:
Day 45: Implement a simple MapReduce framework for batch log analysis
PRO
🔒
Day 46:
Day 46: Add time-based windowing for aggregation
PRO
🔒
Day 47:
Day 47: Implement sliding windows for moving averages
PRO
🔒
Day 48:
Day 48: Add sessionization for tracking user activity
PRO
🔒
Day 49:
Day 49: Implement anomaly detection algorithms
PRO
🔒
Day 50:
Day 50: Create alert generation based on log patterns
PRO
🔒
Day 51:
Day 51: Build dashboards for visualizing analytics results
PRO
📅 Distributed Log Search
🔒
Day 52:
Day 52: Implement a simple inverted index for log searching
PRO
🔒
Day 53:
Day 53: Add distributed indexing across multiple nodes
PRO
🔒
Day 54:
Day 54: Implement a query language for complex searches
PRO
🔒
Day 55:
Day 55: Add faceted search capabilities
PRO
🔒
Day 56:
Day 56: Implement real-time indexing of incoming logs
PRO
🔒
Day 57:
Day 57: Add full-text search capabilities with ranking
PRO
🔒
Day 58:
Day 58: Build a search API for programmatic access
PRO
📅 High Availability and Fault Tolerance
MODULE 3
Advanced Log Processing Features
▼
📅 High Availability and Fault Tolerance
📅 Security and Compliance
🔒
Day 64:
Day 64: Implement role-based access control for log data
PRO
🔒
Day 65:
Day 65: Add field-level encryption for sensitive log data
PRO
🔒
Day 66:
Day 66: Implement log redaction for compliance
PRO
🔒
Day 67:
Day 67: Create audit trails for log access
PRO
🔒
Day 68:
Day 68: Implement data retention policies
PRO
🔒
Day 69:
Day 69: Add GDPR compliance features (right to be forgotten)
PRO
🔒
Day 70:
Day 70: Create compliance reports and export capabilities
PRO
📅 Performance Optimization
🔒
Day 71:
Day 71: Profile and optimize log ingestion pipeline
PRO
🔒
Day 72:
Day 72: Implement adaptive batching based on system load
PRO
🔒
Day 73:
Day 73: Add caching layers for frequent queries
PRO
🔒
Day 74:
Day 74: Optimize storage format for read/write patterns
PRO
🔒
Day 75:
Day 75: Implement bloom filters for efficient existence checking
PRO
🔒
Day 76:
Day 76: Add delta encoding for log storage efficiency
PRO
🔒
Day 77:
Day 77: Implement adaptive resource allocation
PRO
📅 Advanced Analytics
🔒
Day 78:
Day 78: Build a machine learning pipeline for log classification
PRO
🔒
Day 79:
Day 79: Implement clustering for pattern discovery
PRO
🔒
Day 80:
Day 80: Add predictive analytics for forecasting
PRO
🔒
Day 81:
Day 81: Implement a recommendation system for troubleshooting
PRO
🔒
Day 82:
Day 82: Create correlation analysis across different log sources
PRO
🔒
Day 83:
Day 83: Build a root cause analysis engine
PRO
🔒
Day 84:
Day 84: Implement natural language processing for log understanding
PRO
MODULE 4
Building a Complete Distributed Log Platform
▼
📅 API and Service Layer
🔒
Day 85:
Day 85: Design and implement a RESTful API for the log platform
PRO
🔒
Day 86:
Day 86: Add GraphQL support for flexible queries
PRO
🔒
Day 87:
Day 87: Implement rate limiting and quota management
PRO
🔒
Day 88:
Day 88: Create SDK libraries for common languages
PRO
🔒
Day 89:
Day 89: Build a CLI tool for platform interaction
PRO
🔒
Day 90:
Day 90: Implement webhook notifications for log events
PRO
🔒
Day 91:
Day 91: Add batch API operations for efficiency
PRO
📅 Web Interface and Dashboards
🔒
Day 92:
Day 92: Create a basic web UI for log viewing
PRO
🔒
Day 93:
Day 93: Implement real-time log streaming to the UI
PRO
🔒
Day 94:
Day 94: Add advanced search interface with filters
PRO
🔒
Day 95:
Day 95: Create customizable dashboards
PRO
🔒
Day 96:
Day 96: Implement data visualization components
PRO
🔒
Day 97:
Day 97: Add saved searches and alerts in the UI
PRO
🔒
Day 98:
Day 98: Implement user preferences and settings
PRO
📅 Advanced Operational Features
🔒
Day 99:
Day 99: Create a health monitoring system for the platform
PRO
🔒
Day 100:
Day 100: Implement automated scaling policies
PRO
🔒
Day 101:
Day 101: Add blue/green deployment capabilities
PRO
🔒
Day 102:
Day 102: Implement A/B testing framework for features
PRO
🔒
Day 103:
Day 103: Create comprehensive metrics collection
PRO
🔒
Day 104:
Day 104: Build cost allocation and usage reporting
PRO
🔒
Day 105:
Day 105: Implement automated backup and recovery
PRO
📅 Multi-tenancy and Enterprise Features
🔒
Day 106:
Day 106: Design and implement multi-tenant architecture
PRO
🔒
Day 107:
Day 107: Add tenant isolation and resource quotas
PRO
🔒
Day 108:
Day 108: Implement tenant-specific configurations
PRO
🔒
Day 109:
Day 109: Create tenant onboarding/offboarding processes
PRO
🔒
Day 110:
Day 110: Add tenant usage reporting and billing
PRO
🔒
Day 111:
Day 111: Implement single sign-on integration
PRO
🔒
Day 112:
Day 112: Create enterprise integration features (LDAP, Active Directory)
PRO
📅 Storage and Retention Management
🔒
Day 113:
Day 113: Implement tiered storage for log data
PRO
🔒
Day 114:
Day 114: Add data lifecycle policies
PRO
🔒
Day 115:
Day 115: Create historical data archiving
PRO
🔒
Day 116:
Day 116: Implement data restoration from archives
PRO
🔒
Day 117:
Day 117: Add storage optimization for cost reduction
PRO
🔒
Day 118:
Day 118: Create storage usage forecasting
PRO
🔒
Day 119:
Day 119: Implement cross-region data replication
PRO
🔒
Day 120:
Day 120: Add data sovereignty compliance features
PRO
MODULE 5
Integration and Ecosystem
▼
📅 Log Source Integration
🔒
Day 121:
Day 121: Create collectors for Linux system logs
PRO
🔒
Day 122:
Day 122: Add Windows event log collection
PRO
🔒
Day 123:
Day 123: Implement cloud service log collection (AWS CloudWatch)
PRO
🔒
Day 124:
Day 124: Add Azure monitoring integration
PRO
🔒
Day 125:
Day 125: Create Google Cloud logging integration
PRO
🔒
Day 126:
Day 126: Implement container log collection (Docker, Kubernetes)
PRO
🔒
Day 127:
Day 127: Add database audit log collection
PRO
📅 Application Integration
🔒
Day 128:
Day 128: Create logging libraries for major languages
PRO
🔒
Day 129:
Day 129: Implement structured logging helpers
PRO
🔒
Day 130:
Day 130: Add application performance monitoring integration
PRO
🔒
Day 131:
Day 131: Create distributed tracing integration
PRO
🔒
Day 132:
Day 132: Implement error tracking features
PRO
🔒
Day 133:
Day 133: Add deployment and release tracking
PRO
🔒
Day 134:
Day 134: Create feature flag status logging
PRO
📅 External System Integration
🔒
Day 135:
Day 135: Implement Slack notification integration
PRO
🔒
Day 136:
Day 136: Add email alerting and reporting
PRO
🔒
Day 137:
Day 137: Create PagerDuty/OpsGenie integration
PRO
🔒
Day 138:
Day 138: Implement JIRA/ServiceNow ticket creation
PRO
🔒
Day 139:
Day 139: Add Webhook support for custom integrations
PRO
🔒
Day 140:
Day 140: Create data export to S3/blob storage
PRO
🔒
Day 141:
Day 141: Implement metrics export to monitoring systems
PRO
📅 Advanced Processing Integrations
🔒
Day 142:
Day 142: Create Elasticsearch integration for advanced search
PRO
🔒
Day 143:
Day 143: Add Apache Spark integration for big data processing
PRO
🔒
Day 144:
Day 144: Implement machine learning pipeline with TensorFlow
PRO
🔒
Day 145:
Day 145: Create real-time stream processing with Flink
PRO
🔒
Day 146:
Day 146: Add time series database integration
PRO
🔒
Day 147:
Day 147: Implement business intelligence tool integration
PRO
🔒
Day 148:
Day 148: Create natural language queries with NLP
PRO
MODULE 6
Specialized Log Processing Use Cases
▼
📅 Deployment and Operations
🔒
Day 151:
Day 151: Implement GitOps workflow for the platform
PRO
🔒
Day 152:
Day 152: Create operator pattern for Kubernetes management
PRO
🔒
Day 153:
Day 153: Add infrastructure monitoring integration
PRO
🔒
Day 154:
Day 154: Implement disaster recovery procedures
PRO
🔒
Day 155:
Day 155: Create capacity planning tools
PRO
📅 Security Log Processing
🔒
Day 156:
Day 156: Implement SIEM (Security Information Event Management) features
PRO
🔒
Day 157:
Day 157: Add threat detection rules
PRO
🔒
Day 158:
Day 158: Create user behavior analytics
PRO
🔒
Day 159:
Day 159: Implement IOC (Indicators of Compromise) scanning
PRO
🔒
Day 160:
Day 160: Add automated incident response
PRO
🔒
Day 161:
Day 161: Create security compliance reporting
PRO
🔒
Day 162:
Day 162: Implement log-based network traffic analysis
PRO
📅 IT Operations Use Cases
🔒
Day 163:
Day 163: Build service dependency mapping
PRO
🔒
Day 164:
Day 164: Create change impact analysis
PRO
🔒
Day 165:
Day 165: Implement SLA monitoring and reporting
PRO
🔒
Day 166:
Day 166: Add capacity management features
PRO
🔒
Day 167:
Day 167: Create automated root cause analysis
PRO
🔒
Day 168:
Day 168: Implement IT asset tracking with logs
PRO
🔒
Day 169:
Day 169: Build configuration management database integration
PRO
📅 Business Analytics Use Cases
🔒
Day 170:
Day 170: Implement user journey tracking
PRO
🔒
Day 171:
Day 171: Create conversion funnel analysis
PRO
🔒
Day 172:
Day 172: Add revenue impact analysis
PRO
🔒
Day 173:
Day 173: Implement feature usage analytics
PRO
🔒
Day 174:
Day 174: Create A/B test analysis framework
PRO
🔒
Day 175:
Day 175: Add customer experience monitoring
PRO
🔒
Day 176:
Day 176: Build executive dashboards for business metrics
PRO
MODULE 7
Advanced Distributed Systems Concepts
▼
📅 Consensus and Coordination
🔒
Day 181:
Day 181: Implement Raft consensus algorithm
PRO
🔒
Day 182:
Day 182: Create a distributed lock service
PRO
🔒
Day 183:
Day 183: Add distributed semaphores
PRO
🔒
Day 184:
Day 184: Implement lease-based resource management
PRO
🔒
Day 185:
Day 185: Create a service discovery mechanism
PRO
🔒
Day 186:
Day 186: Add version vectors for conflict resolution
PRO
🔒
Day 187:
Day 187: Implement a gossip protocol for state dissemination
PRO
📅 Advanced Consistency Models
🔒
Day 188:
Day 188: Implement linearizable consistency
PRO
🔒
Day 189:
Day 189: Create causal consistency mechanisms
PRO
🔒
Day 190:
Day 190: Add eventual consistency with conflict resolution
PRO
🔒
Day 191:
Day 191: Implement CRDT (Conflict-free Replicated Data Types)
PRO
🔒
Day 192:
Day 192: Create tunable consistency levels
PRO
🔒
Day 193:
Day 193: Add transaction support across partitions
PRO
🔒
Day 194:
Day 194: Implement read/write quorums with sloppy quorum
PRO
📅 Advanced Fault Tolerance
🔒
Day 195:
Day 195: Create a phi-accrual failure detector
PRO
🔒
Day 196:
Day 196: Implement Byzantine fault tolerance
PRO
🔒
Day 197:
Day 197: Add automatic leader election with prioritization
PRO
🔒
Day 198:
Day 198: Create a consensus-based configuration management
PRO
🔒
Day 199:
Day 199: Implement partition-aware request routing
PRO
🔒
Day 200:
Day 200: Add multi-region consensus groups
PRO
🔒
Day 201:
Day 201: Create a split-brain resolver
PRO
📅 Advanced Scalability Patterns
🔒
Day 202:
Day 202: Implement intelligent request routing
PRO
🔒
Day 203:
Day 203: Create adaptive load shedding
PRO
🔒
Day 204:
Day 204: Add predictive resource scaling
PRO
🔒
Day 205:
Day 205: Implement data rebalancing for even distribution
PRO
🔒
Day 206:
Day 206: Create workload-aware partitioning
PRO
🔒
Day 207:
Day 207: Add multi-dimensional sharding
PRO
🔒
Day 208:
Day 208: Implement locality-aware data placement
PRO
📅 Real-time Processing Optimizations
MODULE 8
System Observability and Testing
▼
📅 Real-time Processing Optimizations
📅 Advanced Monitoring
🔒
Day 214:
Day 214: Build a metrics collection framework
PRO
🔒
Day 215:
Day 215: Create service-level objective tracking
PRO
🔒
Day 216:
Day 216: Add distributed tracing for request flows
PRO
🔒
Day 217:
Day 217: Implement advanced log correlation
PRO
🔒
Day 218:
Day 218: Create anomaly detection for system metrics
PRO
🔒
Day 219:
Day 219: Add predictive failure analysis
PRO
🔒
Day 220:
Day 220: Implement dependency-aware monitoring
PRO
📅 Testing and Verification
🔒
Day 221:
Day 221: Create distributed system test framework
PRO
🔒
Day 222:
Day 222: Implement property-based testing
PRO
🔒
Day 223:
Day 223: Add chaos engineering capabilities
PRO
🔒
Day 224:
Day 224: Create partition testing tools
PRO
🔒
Day 225:
Day 225: Implement clock skew testing
PRO
🔒
Day 226:
Day 226: Add load and stress testing framework
PRO
🔒
Day 227:
Day 227: Create long-running reliability tests
PRO
📅 Performance Analysis
🔒
Day 228:
Day 228: Build a distributed profiling system
PRO
🔒
Day 229:
Day 229: Implement distributed request tracing
PRO
🔒
Day 230:
Day 230: Add flame graph generation for bottleneck analysis
PRO
🔒
Day 231:
Day 231: Create benchmark suite for key operations
PRO
🔒
Day 232:
Day 232: Implement A/B performance testing
PRO
🔒
Day 233:
Day 233: Add resource utilization analysis
PRO
🔒
Day 234:
Day 234: Create performance regression detection
PRO
📅 Debugging and Diagnostics
🔒
Day 235:
Day 235: Implement distributed system snapshot capture
PRO
🔒
Day 236:
Day 236: Create context-aware log enrichment
PRO
🔒
Day 237:
Day 237: Add post-mortem debugging tools
PRO
🔒
Day 238:
Day 238: Implement real-time debugging capabilities
PRO
🔒
Day 239:
Day 239: Create visualization for distributed executions
PRO
🔒
Day 240:
Day 240: Add root cause analysis automation
PRO
MODULE 9
Advanced Performance and Optimization
▼
📅 Memory and CPU Optimization
🔒
Day 241:
Day 241: Implement memory pool allocators
PRO
🔒
Day 242:
Day 242: Create lock-free data structures
PRO
🔒
Day 243:
Day 243: Add CPU cache-friendly algorithms
PRO
🔒
Day 244:
Day 244: Implement SIMD optimizations
PRO
🔒
Day 245:
Day 245: Create thread affinity management
PRO
🔒
Day 246:
Day 246: Add adaptive batch sizing
PRO
🔒
Day 247:
Day 247: Implement zero-copy processing pipelines
PRO
📅 Storage Optimization
🔒
Day 248:
Day 248: Create LSM-tree based storage engine
PRO
🔒
Day 249:
Day 249: Implement columnar storage for analytics
PRO
🔒
Day 250:
Day 250: Add bloom filters for membership testing
PRO
🔒
Day 251:
Day 251: Create hierarchical storage management
PRO
🔒
Day 252:
Day 252: Implement incremental compaction strategies
PRO
🔒
Day 253:
Day 253: Add compression algorithm selection based on data
PRO
🔒
Day 254:
Day 254: Create append-only immutable data structures
PRO
👨🏫
Course Instructor
Senior AI Engineer & Educator
With 10+ years in AI/ML, teaching thousands worldwide.
⭐ 4.9👥 50K📚 15 Courses
Prerequisites
Basic programming knowledge and familiarity with software development concepts.
What's Included
📚
507 Video Lessons
Comprehensive course content
💻
Hands-On Projects
Build real-world applications
📝
Downloadable Resources
Code examples & materials
🏆
Certificate
Upon successful completion
♾️
Lifetime Access
Learn at your own pace
📱
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Access on any device
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