Hardware Selection and Configuration
- Choose hardware that meets your performance requirements, including CPU, RAM, and storage.
- Use SSDs for storage to improve read/write performance.
- Set up hardware redundancy to avoid single points of failure.
MongoDB Configuration:
- Choose the appropriate storage engine (e.g., WiredTiger) for your workload.
- Configure the MongoDB instance to use the recommended settings for your hardware and workload.
- Set up sharding if your data size exceeds the capacity of a single server.
Indexes and Query Optimization:
- Design efficient indexes based on your query patterns.
- Use the
explain() method to analyze and optimize queries. - Avoid unnecessary or inefficient queries.
Replication and High Availability:
- Implement replica sets for data redundancy and high availability.
- Monitor the health of replica set members.
- Configure automatic failover and recovery.
Backup and Disaster Recovery:
- Establish a robust backup and recovery strategy.
- Regularly back up data using tools like
mongodump or use online backup solutions. - Test and document the restore process.
Monitoring and Alerting:
- Set up monitoring tools like MongoDB's own monitoring and alerting tools, or third-party solutions.
- Create alerts for key performance metrics, such as CPU usage, memory usage, disk space, and query performance.
Scaling:
- Plan for horizontal scaling using sharding when data volume grows beyond the capacity of a single server.
- Add new shards to the cluster as needed to distribute the data load.
Security:
- Implement authentication and authorization for users and applications.
- Enable encryption for data in transit and at rest.
- Regularly audit and review security configurations.
Optimize Data Modeling:
- Normalize or denormalize data structures based on query patterns.
- Use best practices for schema design to reduce contention and improve performance.
Connection Pooling:
- Implement connection pooling to efficiently manage client connections.
- Adjust connection pool settings based on traffic and resource utilization.
Caching:
Load Testing:
Auto-Scaling (Cloud Deployments):
- If running in a cloud environment, set up auto-scaling based on predefined triggers and metrics.
Logs and Monitoring for Slow Queries:
- Monitor the MongoDB logs for slow queries and optimize them as needed.
- Use profiling to identify and optimize slow operations.
Documentation and Disaster Recovery Plan:
- Maintain thorough documentation of your MongoDB setup, configurations, and procedures.
- Have a well-documented disaster recovery plan in place.
Regular Maintenance:
- Schedule regular maintenance tasks such as index rebuilds and hardware upgrades as needed.
Testing and Staging Environment:
- Maintain a separate testing and staging environment to test changes and updates before applying them to the production environment.
Scalability Planning:
- Continuously monitor and plan for future scalability requirements to accommodate growing workloads.