MongoDB Technical Administration and Operations Training Course

Module 1: Introduction and MongoDB Architecture (4h)

Content:

• History and the broader MongoDB ecosystem
• Typical use cases, advantages, and limitations
• General architecture: instances, processes, and configuration parameters

Practice:

• Interactive exploration: connecting via Mongo Shell/CLI
• Creating a sample database and collection

Module 2: Installation and Initial Configuration (6h)

Content:

• Hardware and resource requirements
• Installation procedures on Linux (deb/rpm), Windows, and macOS
• YAML configuration files (mongod.conf): dataDir, logDir, bindIp, port
• Startup options and systemd/service management

Practice:

• Deploying instances on local VMs or Docker containers
• Adjusting configurations for development versus production environments
• Verifying secure remote connectivity

Module 3: Data Modeling and Basic Operations (5h)

Content:

• BSON documents, collections, and databases
• Modeling strategies: embedding vs. referencing; data design patterns
• Introduction to basic indexes
• Operations using Mongo Shell and scripting examples with drivers

Practice:

• Modeling a use case: inventory or billing system
• Implementing CRUD operations
• Applying schema validation using JSON Schema in MongoDB

Module 4: Indexes and Performance (4h)

Content:

• Simple, compound, multikey, text, and geospatial indexes
• Utilizing explain() and analyzing performance metrics
• Impact of indexes on write performance and memory usage

Practice:

• Creating collections with test data
• Testing queries with and without indexes; interpreting explain() output
• Adjusting indexes based on specific access patterns

Module 5: Security (5h)

Content:

• Authentication mechanisms: SCRAM, LDAP/Kerberos (introduction)
• Defining users and custom roles
• TLS/SSL configuration between clients and servers
• At-rest encryption: key configuration
• Basic audit logging

Practice:

• Creating users with minimal necessary privileges
• Configuring TLS for local instances
• Verifying unauthorized access prevention and reviewing audit logs

Module 6: Replication and High Availability (6h)

Content:

• Replication concepts: Primary, Secondary, oplog
• Replica set configuration: initiation, membership, arbitration
• Monitoring status and election processes
• Maintenance tasks: adding/removing members, reassigning priorities

Practice:

• Deploying a three-node replica set (locally or on VMs)
• Simulating primary failure and observing failover behavior
• Rebuilding secondary nodes and recovering replicas

Module 7: Sharding and Horizontal Scalability (6h)

Content:

• Sharding concepts: shard key, config servers, mongos router
• Selecting shard keys and understanding associated risks
• Deploying config servers, shards, and mongos instances
• Rebalancing and chunk migration strategies

Practice:

• Configuring a simple sharded cluster
• Inserting large-scale data and observing distribution
• Introducing shard key changes and understanding their limitations

Module 8: Backup, Restore, and Disaster Recovery (4h)

Content:

• Native tools: mongodump/mongorestore, filesystem snapshots
• Backup strategies for replica sets and sharded clusters
• Basic use of Cloud Manager/Ops Manager for backup operations
• Disaster Recovery (DR) planning: defining RTO and RPO

Practice:

• Performing backup and restore on a test database
• Simulating failure and recovering from backups
• Designing a DR plan for a hypothetical scenario

Module 9: Monitoring and Alerts (4h)

Content:

• Tools: mongostat, mongotop, Cloud Manager/Atlas Monitoring
• Integration with Prometheus + Grafana (concepts and examples)
• Key metrics: CPU, memory, I/O, oplog size, latencies
• Alerts: defining thresholds and notifications

Practice:

• Deploying a local or container-based monitoring agent
• Setting up basic dashboards with sample metrics
• Simulating load and observing alert triggers

Module 10: Maintenance, Upgrades, and Best Practices (4h)

Content:

• Upgrade strategies for replica sets and sharded clusters
• Data cleanup, compaction, integrity checks
• Reviewing logs and conducting regular audits
• Automating routine tasks (scripts, cronjobs, Ansible, Terraform)
• Data retention and archiving policies

Practice:

• Simulating minor and major upgrades in a controlled environment
• Creating automation scripts for backup and monitoring
• Developing a periodic maintenance checklist

Summary and Next Steps