MongoDB Technical Administration and Operations Training Course

Module 1: Overview and MongoDB Architectural Framework (4 Hours)

Curriculum:

• Historical development and ecosystem components of MongoDB
• Operational applicability, strategic advantages, and potential limitations
• Core architectural components: instances, processes, and configuration structures

Practical Application:

• Interactive environment exploration: Establishing connectivity via Mongo Shell/CLI
• Provisioning a demonstration database and associated collections

Module 2: Deployment and Initial Configuration Protocols (6 Hours)

Curriculum:

• Hardware infrastructure and resource allocation requirements
• Installation procedures for Linux (deb/rpm), Windows, and macOS platforms
• YAML configuration standards (mongod.conf): data directories, logging, network binding, and port management
• Service initialization parameters and system service management (systemd/services)

Practical Application:

• Provisioning instances within local virtual machines or Docker container environments
• Configuring parameters for development versus production operational contexts
• Validating secure remote connectivity protocols

Module 3: Data Architecture and Foundational Operations (5 Hours)

Curriculum:

• BSON document structure, collection organization, and database hierarchy
• Data modeling strategies: Embedding versus referencing; design pattern implementations
• Foundational indexing concepts (previously introduced)
• Operational execution via Mongo Shell and driver-based scripting examples

Practical Application:

• Designing data models for inventory or billing system use cases
• Executing Create, Read, Update, and Delete (CRUD) operations
• Implementing schema validation using JSON Schema standards within MongoDB

Module 4: Indexing Strategies and Performance Optimization (4 Hours)

Curriculum:

• Index types: Single-field, compound, multikey, text, and geospatial
• Utilizing the explain() command and interpreting performance metrics
• Evaluating the impact of indexing on write throughput and memory consumption

Practical Application:

• Populating collections with synthetic test data
• Conducting comparative query tests with and without indexes; analyzing explain() outputs
• Optimizing index configurations based on observed access patterns

Module 5: Security Governance and Access Control (5 Hours)

Curriculum:

• Authentication frameworks: SCRAM, LDAP/Kerberos (foundational overview)
• User account management and custom role definition
• TLS/SSL encryption protocols for client-server communication
• Data-at-rest encryption: Key management and configuration
• Implementation of basic audit logging procedures

Practical Application:

• Creating user accounts adhering to the principle of least privilege
• Configuring TLS encryption on local instances
• Testing for unauthorized access attempts and reviewing generated audit logs

Module 6: Replication Mechanisms and High Availability (6 Hours)

Curriculum:

• Core replication concepts: Primary nodes, Secondary nodes, and the oplog
• Replica set configuration: Initialization, membership management, and arbitration
• Monitoring replica set status and election processes
• Maintenance procedures: Adding/removing members and adjusting priority settings

Practical Application:

• Deploying a three-node replica set (local or virtual machine environment)
• Simulating primary node failure and observing automatic failover
• Rebuilding secondary nodes and synchronizing replica sets

Module 7: Sharding and Horizontal Scaling Strategies (6 Hours)

Curriculum:

• Sharding fundamentals: Shard keys, config servers, and mongos routers
• Shard key selection criteria and associated operational risks
• Deployment of config servers, data shards, and routing layers
• Rebalancing processes and chunk migration management

Practical Application:

• Configuring a basic sharded cluster environment
• Ingesting large-scale datasets and analyzing data distribution
• Exploring shard key modifications and understanding functional limitations

Module 8: Data Resilience, Backup, and Disaster Recovery (4 Hours)

Curriculum:

• Native tooling: mongodump/mongorestore and filesystem snapshot capabilities
• Backup strategies for replica sets and sharded clusters
• Foundational utilization of Cloud Manager/Ops Manager for backup operations
• Disaster Recovery (DR) planning: Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO)

Practical Application:

• Executing backup and restoration procedures on a test database
• Simulating system failures and recovering data from backups
• Developing a disaster recovery plan for a hypothetical operational scenario

Module 9: Performance Monitoring and Alerting Systems (4 Hours)

Curriculum:

• Monitoring utilities: mongostat, mongotop, and Cloud Manager/Atlas Monitoring
• Integration concepts with Prometheus and Grafana (examples and methodology)
• Key performance indicators: CPU utilization, memory usage, I/O throughput, oplog size, and latency metrics
• Alerting mechanisms: Defining thresholds and notification protocols

Practical Application:

• Deploying local or container-based monitoring agents
• Configuring basic dashboards using sample performance metrics
• Simulating load conditions and verifying alert triggers

Module 10: Lifecycle Management, Upgrades, and Best Practices (4 Hours)

Curriculum:

• Upgrade strategies for replica sets and sharded cluster environments
• Data maintenance: Cleanup, compaction, and integrity verification
• Log analysis and periodic security audits
• Automation of routine tasks (scripting, cronjobs, Ansible, Terraform)
• Data retention and archival policy implementation

Practical Application:

• Simulating minor and major version upgrades in a controlled environment
• Developing automation scripts for backup and monitoring workflows
• Formulating a periodic maintenance checklist for ongoing operations

Course Summary and Professional Development Path