MongoDB Technical Administration and Operations Training Course

Module 1: Introduction and MongoDB Architecture (4h)

Key Concepts:

• Historical context and the MongoDB ecosystem.
• Typical use cases, along with advantages and limitations.
• General architecture: instances, processes, and configuration.

Practical Application:

• Interactive exploration via the Mongo Shell or CLI.
• Creation of a sample database and collection.

Module 2: Installation and Initial Configuration (6h)

Key Concepts:

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

Practical Application:

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

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

Key Concepts:

• BSON documents, collections, and databases.
• Modeling strategies: embedding versus referencing, and data design patterns.
• Basic indexes (revisiting foundational concepts).
• Operations using the Mongo Shell and scripting examples with drivers.

Practical Application:

• Modeling a specific use case, such as an inventory or billing system.
• Implementing CRUD operations.
• Applying schema validation using JSON Schema in MongoDB.

Module 4: Indexes and Performance (4h)

Key Concepts:

• Types of indexes: simple, compound, multikey, text, and geospatial.
• Utilizing explain() and analyzing performance metrics.
• The impact of indexes on write performance and memory usage.

Practical Application:

• Creating collections populated with test data.
• Testing queries with and without indexes; interpreting explain() outputs.
• Optimizing indexes based on observed access patterns.

Module 5: Security (5h)

Key Concepts:

• Authentication mechanisms: SCRAM, LDAP/Kerberos (introduction).
• Defining users and establishing custom roles.
• Implementing TLS/SSL between clients and servers.
• Encryption at rest: key configuration.
• Basic audit logging practices.

Practical Application:

• Creating users with minimal necessary privileges.
• Configuring TLS in local instances.
• Testing unauthorized access attempts and reviewing audit logs.

Module 6: Replication and High Availability (6h)

Key Concepts:

• Core replication concepts: Primary, Secondary nodes, and the oplog.
• Replica set configuration: initiation, membership, and arbitration.
• Monitoring cluster status and elections.
• Maintenance tasks: adding/removing members and reassigning priorities.

Practical Application:

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

Module 7: Sharding and Horizontal Scalability (6h)

Key Concepts:

• Sharding fundamentals: shard key, config servers, and the mongos router.
• Shard key selection and associated risks.
• Deploying config servers, shards, and mongos instances.
• Rebalancing and chunk migration processes.

Practical Application:

• Configuring a simple sharded cluster.
• Inserting large-scale data to observe distribution patterns.
• Exploring shard key modifications and understanding their limitations.

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

Key Concepts:

• Native tools: mongodump/mongorestore and filesystem snapshots.
• Backup strategies for replica sets and sharded clusters.
• Using Cloud Manager/Ops Manager for backup management.
• Disaster Recovery (DR) planning: defining RTO and RPO.

Practical Application:

• Executing backup and restore operations on a test database.
• Simulating failure scenarios and recovering from backups.
• Designing a DR plan for a hypothetical scenario.

Module 9: Monitoring and Alerts (4h)

Key Concepts:

• Monitoring tools: mongostat, mongotop, and Cloud Manager/Atlas Monitoring.
• Integration with Prometheus and Grafana (concepts and examples).
• Key metrics to track: CPU, memory, I/O, oplog size, and latencies.
• Alerting strategies: defining thresholds and notifications.

Practical Application:

• Deploying a local or container-based monitoring agent.
• Setting up basic dashboards with sample metrics.
• Simulating system load to observe alert triggers.

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

Key Concepts:

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

Practical Application:

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

Summary and Next Steps