Performance and Database Security - CloudScope/DevOpsWithCloudScope GitHub Wiki

Database Performance

  1. Indexing

    • Purpose: Improves query performance by allowing the database to locate data without scanning entire tables.
    • Types: Primary, Unique, and Composite indexes.
    • Best Practices:
      • Use indexes on columns that are frequently used in WHERE, JOIN, and ORDER BY clauses.
      • Avoid over-indexing, as each index consumes memory and can slow down write operations.
      • Monitor index usage periodically to ensure relevance.

  2. Query Optimization

    • Purpose: Reduces the time and resources required to execute queries.
    • Best Practices:
      • Use proper joins (e.g., INNER JOIN over OUTER JOIN if possible) and filter conditions.
      • Avoid SELECT *; instead, specify needed columns to minimize data transfer.
      • Analyze and rewrite complex subqueries as joins where feasible.
      • Use EXPLAIN plans to identify bottlenecks and understand query execution paths.

  3. Database Caching

    • Purpose: Reduces load on the database by temporarily storing query results.
    • Methods: Implement caching at various levels (e.g., application, database, and object caching).
    • Best Practices:
      • Use caching tools like Redis or Memcached for frequently accessed data.
      • Implement cache invalidation strategies to maintain data freshness.

  4. Connection Pooling

    • Purpose: Manages database connections efficiently, reducing latency by reusing existing connections.
    • Best Practices:
      • Configure an optimal pool size based on the database and server capabilities.
      • Close inactive connections to prevent resource waste.
      • Use connection pooling libraries suited to the application language or framework.

  5. Data Partitioning

    • Purpose: Distributes data across multiple physical or logical partitions to enhance performance.
    • Techniques: Horizontal partitioning (sharding) and vertical partitioning (splitting tables by columns).
    • Best Practices:
      • Partition large tables to optimize read/write times and manage data growth.
      • Use partition pruning to minimize the scanned partitions, enhancing query performance.

  6. Hardware and Scaling

    • Purpose: Ensures adequate resources for processing and storage.
    • Scaling Options:
      • Vertical Scaling: Adding resources (CPU, RAM) to a single server.
      • Horizontal Scaling: Adding more servers or instances (distributed databases).
    • Best Practices:
      • Monitor and upgrade hardware based on performance metrics and bottlenecks.
      • Use load balancers and replication to distribute traffic and enhance fault tolerance.

Database Security

  1. Access Control and Authentication

    • Purpose: Ensures only authorized users have access to the database.
    • Best Practices:
      • Implement Role-Based Access Control (RBAC) and grant permissions based on the principle of least privilege.
      • Use strong, unique passwords and Multi-Factor Authentication (MFA).
      • Limit database access to trusted IP addresses, and avoid default usernames for critical roles.

  2. Encryption

    • Purpose: Protects sensitive data in transit and at rest.
    • Best Practices:
      • Encrypt sensitive columns, such as PII (Personally Identifiable Information).
      • Use SSL/TLS to secure data in transit between the database and applications.
      • Enable Transparent Data Encryption (TDE) for databases storing sensitive information.

  3. Data Masking and Tokenization

    • Purpose: Protects data by substituting sensitive information with anonymized or masked values.
    • Best Practices:
      • Use data masking techniques to restrict sensitive data visibility for non-privileged users.
      • Apply tokenization for fields like credit card numbers, enabling secure storage and processing.

  4. Database Auditing and Logging

    • Purpose: Tracks and monitors database activity for security and compliance.
    • Best Practices:
      • Enable auditing to log critical operations, such as data access, modifications, and user logins.
      • Regularly review logs for unusual patterns or unauthorized access attempts.
      • Set up alerts for suspicious activities, such as failed login attempts or data exfiltration.

  5. Database Backup and Recovery

    • Purpose: Protects data from loss due to system failures, disasters, or security incidents.
    • Best Practices:
      • Perform regular backups, following the 3-2-1 rule (three copies, two media types, one offsite).
      • Encrypt backup files and ensure they are stored in a secure location.
      • Test recovery procedures periodically to ensure backup integrity and recovery readiness.

  6. Database Firewalls and Network Security

    • Purpose: Prevents unauthorized access to the database from external sources.
    • Best Practices:
      • Use firewall rules to restrict access to the database from trusted IPs only.
      • Implement Virtual Private Network (VPN) access for remote connections.
      • Regularly patch the database software to address known vulnerabilities.

  7. Vulnerability Management and Patching

    • Purpose: Keeps the database secure by addressing security vulnerabilities.
    • Best Practices:
      • Apply database patches and updates as soon as they’re available.
      • Conduct regular vulnerability scans to identify and mitigate potential weaknesses.
      • Consider automated patch management solutions if managing a large-scale database environment.