{
  "format": "dataset-manifest/1",
  "slug": "virtual-machine-operations-in-manufacturing",
  "version": 3,
  "seed": "virtual-machine-operations-in-manufacturing:1",
  "spec": {
    "format": "dataset/1",
    "slug": "virtual-machine-operations-in-manufacturing",
    "name": "Virtual Machine Operations in Manufacturing",
    "tagline": "Performance and configuration data of virtual machines in manufacturing, including storage, network, and backup details.",
    "description": "Virtual machines streamline production workflows in manufacturing facilities, enabling efficient management of workloads and resource allocation. These digital instances help ensure that physical machines operate at optimal capacity and facilitate seamless transitions between stages of production. The dataset captures various facets of virtual machine operations, including performance metrics, configuration details, storage usage, network setups, backup protocols, and replication strategies, all essential for maintaining a robust manufacturing environment.\n\nEach row in the vm_performance table represents performance metrics for individual virtual machines, such as CPU usage and memory consumption, which can be analyzed against the configurations recorded in the vm_configuration table. The vm_storage table details the storage allocation and utilization, while the vm_network table outlines network configurations, including bandwidth allocations and connectivity statuses. The vm_backup table logs backup schedules and success rates, whereas the vm_replication table tracks the replication of virtual machines across different environments, highlighting operational strategies tailored to specific manufacturing needs.\n\nBy examining this synthetic data, developers can explore critical questions regarding resource optimization, performance bottlenecks, and the efficacy of backup and replication strategies. This dataset offers valuable insights into how virtual machines can be configured and managed to enhance overall manufacturing efficiency, allowing users to practice their data analysis and querying skills. It's an excellent resource to experiment with complex joins across multiple tables, giving a holistic view of the interconnected components that drive virtual machine operations in a manufacturing setting.",
    "domain": "manufacturing",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "virtual machines",
      "manufacturing",
      "performance metrics",
      "resource allocation",
      "network configuration",
      "storage usage"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "vm_performance": {
        "description": "This table tracks the performance metrics of virtual machines over time, linking to the 'vm_configuration' table. Each row represents a snapshot of performance data at a specific timestamp.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the performance record."
          },
          "vm_id": {
            "kind": "fk",
            "ref": "vm_configuration.id",
            "description": "Reference to the virtual machine configuration."
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time of the performance measurement."
          },
          "cpu_usage": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 2,
            "description": "CPU usage percentage.",
            "distribution": "high"
          },
          "memory_usage": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 2,
            "description": "Memory usage percentage.",
            "distribution": "high"
          },
          "disk_io": {
            "kind": "decimal",
            "min": 0,
            "max": 1000,
            "scale": 2,
            "description": "Disk I/O operations per second.",
            "distribution": "normal"
          },
          "network_io": {
            "kind": "decimal",
            "min": 0,
            "max": 1000,
            "scale": 2,
            "description": "Network I/O in Mbps.",
            "distribution": "normal"
          }
        }
      },
      "vm_configuration": {
        "description": "This table contains details about the configuration of each virtual machine. It serves as a reference for performance data in the 'vm_performance' table.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the virtual machine."
          },
          "vm_name": {
            "kind": "fullName",
            "description": "Name of the virtual machine."
          },
          "cpu_count": {
            "kind": "int",
            "min": 1,
            "max": 16,
            "description": "Number of virtual CPUs allocated."
          },
          "memory_size": {
            "kind": "decimal",
            "min": 1,
            "max": 64,
            "scale": 2,
            "description": "Memory size allocated in GB."
          },
          "storage_size": {
            "kind": "decimal",
            "min": 1,
            "max": 1024,
            "scale": 2,
            "description": "Storage size allocated in GB."
          },
          "network_configuration": {
            "kind": "words",
            "max": 3,
            "description": "Description of the network configuration.",
            "nullable": true,
            "when": {
              "column": "replication_strategy",
              "in": [
                "synchronous",
                "asynchronous"
              ]
            },
            "pool": [
              "protocol",
              "firewall",
              "bandwidth",
              "topology",
              "gateway",
              "subnet",
              "address",
              "routing",
              "interface",
              "latency",
              "switch",
              "monitoring",
              "segmentation",
              "encryption",
              "load-balancer",
              "dns",
              "vpn",
              "access-control",
              "traffic",
              "configuration",
              "management"
            ],
            "min": 1
          },
          "replication_strategy": {
            "kind": "enum",
            "values": [
              "none",
              "synchronous",
              "asynchronous"
            ],
            "description": "Replication strategy employed.",
            "nullable": true,
            "weights": [
              8,
              2,
              1
            ]
          }
        }
      },
      "vm_storage": {
        "description": "This table details the storage usage of each virtual machine, linking back to the 'vm_configuration' table, and records how storage is utilized over time.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the storage record."
          },
          "vm_id": {
            "kind": "fk",
            "ref": "vm_configuration.id",
            "description": "Reference to the virtual machine configuration."
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time of the storage measurement."
          },
          "used_storage": {
            "kind": "decimal",
            "min": 0,
            "max": 1024,
            "scale": 2,
            "description": "Amount of storage used in GB.",
            "distribution": "long-tail"
          },
          "available_storage": {
            "kind": "decimal",
            "min": 0,
            "max": 1024,
            "scale": 2,
            "description": "Amount of storage available in GB.",
            "distribution": "long-tail"
          }
        }
      },
      "vm_network": {
        "description": "This table tracks network configurations and performance metrics for virtual machines, linking to the 'vm_configuration' table.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the network record."
          },
          "vm_id": {
            "kind": "fk",
            "ref": "vm_configuration.id",
            "description": "Reference to the virtual machine configuration."
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time of the network measurement."
          },
          "latency": {
            "kind": "decimal",
            "min": 0,
            "max": 200,
            "scale": 2,
            "description": "Network latency in milliseconds.",
            "distribution": "normal"
          },
          "throughput": {
            "kind": "decimal",
            "min": 0,
            "max": 1000,
            "scale": 2,
            "description": "Network throughput in Mbps.",
            "distribution": "normal"
          }
        }
      },
      "vm_backup": {
        "description": "This table records the backup operations performed on virtual machines, linking to the 'vm_configuration' table.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the backup record."
          },
          "vm_id": {
            "kind": "fk",
            "ref": "vm_configuration.id",
            "description": "Reference to the virtual machine configuration."
          },
          "backup_time": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time when the backup was performed.",
            "dayProfile": "business"
          },
          "backup_size": {
            "kind": "decimal",
            "min": 1,
            "max": 1024,
            "scale": 2,
            "description": "Size of the backup in GB.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "failure"
              ]
            },
            "distribution": "long-tail"
          },
          "status": {
            "kind": "enum",
            "values": [
              "success",
              "failure"
            ],
            "description": "Status of the backup operation.",
            "nullable": true,
            "weights": [
              7,
              3
            ]
          }
        }
      },
      "vm_replication": {
        "description": "This table logs the replication events for virtual machines, linking to the 'vm_configuration' table to track replication activities.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the replication record."
          },
          "vm_id": {
            "kind": "fk",
            "ref": "vm_configuration.id",
            "description": "Reference to the virtual machine configuration."
          },
          "replication_time": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time when the replication occurred.",
            "dayProfile": "business"
          },
          "status": {
            "kind": "enum",
            "values": [
              "successful",
              "failed"
            ],
            "description": "Status of the replication operation.",
            "nullable": true,
            "weights": [
              6,
              4
            ]
          },
          "data_size": {
            "kind": "decimal",
            "min": 1,
            "max": 500,
            "scale": 2,
            "description": "Size of data replicated in GB.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "failed"
              ]
            },
            "distribution": "long-tail"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "monetary",
      "categorical"
    ],
    "analysisQuestions": [
      "What are the peak usage times for CPU and memory across virtual machines?",
      "How does storage usage change over time for different virtual machines?",
      "What replication strategies are most commonly employed and how do they affect performance?",
      "What are the success rates of backup operations and how do they correlate with storage usage?",
      "How does network latency impact the performance of virtual machines during peak hours?"
    ],
    "suggestedQueries": [
      {
        "title": "Join VM Performance and Configuration",
        "sql": "SELECT vm_performance.timestamp, vm_configuration.vm_name, vm_performance.cpu_usage FROM vm_performance JOIN vm_configuration ON vm_performance.vm_id = vm_configuration.id;",
        "dialect": "postgres"
      },
      {
        "title": "Average CPU Usage by VM",
        "sql": "SELECT vm_configuration.vm_name, AVG(vm_performance.cpu_usage) AS avg_cpu_usage FROM vm_performance JOIN vm_configuration ON vm_performance.vm_id = vm_configuration.id GROUP BY vm_configuration.vm_name;",
        "dialect": "postgres"
      },
      {
        "title": "Daily Network Latency",
        "sql": "SELECT DATE(vm_network.timestamp) AS date, AVG(vm_network.latency) AS avg_latency FROM vm_network GROUP BY date;",
        "dialect": "postgres"
      },
      {
        "title": "Backup Success Rates",
        "sql": "SELECT vm_configuration.vm_name, COUNT(*) FILTER (WHERE vm_backup.status = 'success') AS successful_backups, COUNT(*) AS total_backups FROM vm_backup JOIN vm_configuration ON vm_backup.vm_id = vm_configuration.id GROUP BY vm_configuration.vm_name;",
        "dialect": "postgres"
      },
      {
        "title": "Replication Event Summary",
        "sql": "SELECT vm_configuration.vm_name, COUNT(*) AS total_replications, SUM(CASE WHEN vm_replication.status = 'successful' THEN 1 ELSE 0 END) AS successful_replications FROM vm_replication JOIN vm_configuration ON vm_replication.vm_id = vm_configuration.id GROUP BY vm_configuration.vm_name;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Manufacturing Operations Analysis",
        "body": "Manufacturing analysts can use this dataset to monitor the performance of virtual machines deployed in production. By examining CPU utilization and memory usage over time, they can identify peaks in resource demand and optimize VM configurations accordingly to enhance efficiency."
      },
      {
        "title": "Resource Allocation Optimization",
        "body": "IT managers in manufacturing can leverage this dataset to assess storage and resource allocation across multiple virtual machines. By analyzing trends in storage usage and network performance, they can make informed decisions on resource distribution, replication strategies, and backup frequencies."
      },
      {
        "title": "Performance Benchmarking",
        "body": "Data scientists can utilize this dataset to benchmark the performance of various virtual machines under different configurations and workloads. By conducting detailed analyses of performance metrics, they can derive insights into which setups yield the best operational efficiency."
      },
      {
        "title": "Backup and Recovery Evaluation",
        "body": "System administrators can use this dataset to evaluate the effectiveness of backup and recovery strategies for virtual machines. By analyzing backup success rates and the sizes of backup files, they can identify areas for improvement in their data protection strategies."
      }
    ]
  },
  "counts": {
    "vm_configuration": 100,
    "vm_backup": 200,
    "vm_network": 150,
    "vm_performance": 500,
    "vm_replication": 150,
    "vm_storage": 300
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