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Course Outline

Module 1: Introduction and MongoDB Architecture (4h)

Content:

  • History and the MongoDB ecosystem.
  • Typical use cases, pros, and cons.
  • General architecture: instances, processes, and configuration.

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 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: embedding vs. referencing; data design patterns.
  • Basic indexes (introduced earlier).
  • Operations using Mongo Shell and scripting examples with drivers.

Practice:

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

Module 4: Indexes and Performance (4h)

Content:

  • Simple, compound, multikey, text, and geospatial indexes.
  • Using explain() and analyzing 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 access patterns.

Module 5: Security (5h)

Content:

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

Practice:

  • Creating users with minimal privileges.
  • Configuring TLS in local instances.
  • Verifying unauthorized access 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 elections.
  • Maintenance: adding/removing members, reassigning priorities.

Practice:

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

Module 7: Sharding and Horizontal Scalability (6h)

Content:

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

Practice:

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

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

Content:

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

Practice:

  • Performing backup and restore on a test database.
  • Simulating failure and recovery from backup.
  • Designing a DR plan for a hypothetical case.

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 alerts.

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 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

Requirements

  • A solid understanding of general database concepts and data structures.
  • Familiarity with Linux command-line usage.
  • Basic knowledge of networking and system administration.

Audience

  • Database administrators and system engineers working with MongoDB.
  • DevOps and infrastructure teams responsible for deploying and maintaining MongoDB environments.
  • Developers interested in MongoDB internals and deployment best practices.
 48 Hours

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