MongoDB Technical Administration and Operations

• An 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 deploying and maintaining MongoDB environments
• Developers interested in MongoDB internals and deployment best practices

MongoDB is a popular NoSQL database known for its flexibility, scalability, and distributed architecture, making it ideal for modern application backends, data aggregation, and real-time analytics.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level technical staff who wish to gain practical, in-depth knowledge of MongoDB operations, from deployment to high availability, security, and disaster recovery.

By the end of this training, participants will be able to:

• Install, configure, and maintain MongoDB in various environments.
• Model data appropriately for performance and scalability.
• Configure secure access and define backup and recovery procedures.
• Set up high-availability clusters and monitor performance metrics.
• Handle real-world administrative tasks such as upgrades and automation.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Module 1: Introduction and MongoDB Architecture (4h)

Content:

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

Practice:

• Interactive exploration: connecting with 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 vs. production
• Verifying secure remote connectivity

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

Content:

• BSON documents, collections, databases
• Modeling: embedding vs referencing; data design patterns
• Basic indexes (introduced earlier)
• Operations with Mongo Shell and scripting examples using drivers

Practice:

• Modeling a use case: 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
• Index impact on write performance and memory

Practice:

• Creating collections with test data
• Testing queries with and without indexes; interpreting explain()
• 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