1. 1. AI & ML Services
    ❱
    1. 1.1. AI Building Blocks
    2. 1.2. AI Hub
    3. 1.3. AI Platform
    4. 1.4. Cloud AutoML
  3. 2. Compute Services
    ❱
    1. 2.1. App Engine
    2. 2.2. Cloud Functions
    3. 2.3. Compute Engine
    4. 2.4. Kubernetes Engine
  5. 3. Data Analytics Services
    ❱
    1. 3.1. BigQuery
      ❱
      1. 3.1.1. Storage & Database Services
        ❱
        1. 3.1.1.1. database_services
      3. 3.1.2. Architecture
      4. 3.1.3. Automatic schema detection
      5. 3.1.4. Best practices
      6. 3.1.5. Build Streaming data pipelines
      7. 3.1.6. CLI
      8. 3.1.7. Caching
      9. 3.1.8. Clustered Tables
      10. 3.1.9. Copying dataset
      11. 3.1.10. Create & Query Permanent Table on Cloud Storage bucket
      12. 3.1.11. Create Cloud Storage bucket
      13. 3.1.12. Designing Efficient Schemas
      14. 3.1.13. Example of End-to-end Data Pipeline
      15. 3.1.14. Execution Plan
      16. 3.1.15. External data source Limitations
      17. 3.1.16. Field partition
      18. 3.1.17. Ingestion time partition tables
      19. 3.1.18. Managing access
      20. 3.1.19. Manual operations on Table
      21. 3.1.20. Materialized Views
      22. 3.1.21. Maximum bytes billed
      23. 3.1.22. Native operations on Table for Schema change
      24. 3.1.23. Pricing
      25. 3.1.24. Python lib
      26. 3.1.25. Query settings
      27. 3.1.26. Saved queries
      28. 3.1.27. Scheduled queries
      29. 3.1.28. Streaming data
      30. 3.1.29. Table partitioning
      31. 3.1.30. UI
      32. 3.1.31. Views
      33. 3.1.32. When to use Clustering or Partitioning or Both
      34. 3.1.33. Wildcards
    3. 3.2. Big Query
    4. 3.3. Cloud Dataflow
    5. 3.4. Cloud Datalab
    6. 3.5. Cloud Dataproc
    7. 3.6. Cloud Pub Sub
    8. 3.7. Data Studio
  7. 4. DevOps Services
    ❱
    1. 4.1. Cloud Build
    2. 4.2. Cloud Source Repositories
    3. 4.3. Container Registry
    4. 4.4. Example1
  9. 5. GCP-Notions
    ❱
    1. 5.1. Project
    2. 5.2. Resource
  11. 6. Identity & Access Management
  12. 7. Images
  13. 8. Network Services
  14. 9. Notions
    ❱
    1. 9.1. CI-CD
    2. 9.2. Docker
    3. 9.3. Ingestion
    4. 9.4. Kubernetes
    5. 9.5. NoSQL
    6. 9.6. Normalization-Denormalization
    7. 9.7. RDBMS
    8. 9.8. REST
    9. 9.9. Redis
    10. 9.10. Serverless
    11. 9.11. Window function
    12. 9.12. failover
    13. 9.13. in-memory data store
    14. 9.14. on-premises
    15. 9.15. provisioning
  16. 10. Main

Redis