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