```json
{
  "sym_variables": [
    ("x0", "patches per day"),
    ("x1", "system administrators"),
    ("x2", "deployed decoys"),
    ("x3", "pen testers"),
    ("x4", "SOC operators"),
    ("x5", "security engineers")
  ],
  "objective_function": "9*x0 + 3*x1 + 7*x2 + 8*x3 + 4*x4 + 8*x5",
  "constraints": [
    "18*x0 + 9*x1 + 9*x2 + 24*x3 + 22*x4 + 8*x5 <= 376",
    "1*x0 + 7*x1 + 2*x2 + 21*x3 + 18*x4 + 25*x5 <= 321",
    "20*x0 + 16*x1 + 20*x2 + 25*x3 + 5*x4 + 25*x5 <= 694",
    "18*x0 + 24*x3 + 22*x4 >= 42",
    "18*x0 + 24*x3 + 8*x5 >= 42",
    "9*x1 + 9*x2 + 8*x5 >= 42",
    "9*x2 + 22*x4 + 8*x5 >= 42",
    "9*x1 + 24*x3 + 22*x4 >= 42",
    "9*x2 + 24*x3 + 8*x5 >= 42",
    "18*x0 + 9*x1 + 22*x4 >= 42",
    "9*x1 + 22*x4 + 8*x5 >= 42",
    "9*x1 + 24*x3 + 8*x5 >= 42",
    "9*x1 + 9*x2 + 24*x3 >= 42",
    "18*x0 + 24*x3 + 22*x4 >= 34",
    "18*x0 + 24*x3 + 8*x5 >= 34",
    "9*x1 + 9*x2 + 8*x5 >= 34",
    "9*x2 + 22*x4 + 8*x5 >= 34",
    "9*x1 + 24*x3 + 22*x4 >= 34",
    "9*x2 + 24*x3 + 8*x5 >= 34",
    "18*x0 + 9*x1 + 22*x4 >= 34",
    "9*x1 + 22*x4 + 8*x5 >= 34",
    "9*x1 + 24*x3 + 8*x5 >= 34",
    "9*x1 + 9*x2 + 24*x3 >= 34",
    "18*x0 + 24*x3 + 22*x4 >= 62",
    "18*x0 + 24*x3 + 8*x5 >= 62",
    "9*x1 + 9*x2 + 8*x5 >= 62",
    "9*x2 + 22*x4 + 8*x5 >= 62",
    "9*x1 + 24*x3 + 22*x4 >= 62",
    "9*x2 + 24*x3 + 8*x5 >= 62",
    "18*x0 + 9*x1 + 22*x4 >= 62",
    "9*x1 + 22*x4 + 8*x5 >= 62",
    "9*x1 + 24*x3 + 8*x5 >= 62",
    "9*x1 + 9*x2 + 24*x3 >= 62",
    "18*x0 + 24*x3 + 22*x4 >= 61",
    "18*x0 + 24*x3 + 8*x5 >= 61",
    "9*x1 + 9*x2 + 8*x5 >= 61",
    "9*x2 + 22*x4 + 8*x5 >= 61",
    "9*x1 + 24*x3 + 22*x4 >= 61",
    "9*x2 + 24*x3 + 8*x5 >= 61",
    "18*x0 + 9*x1 + 22*x4 >= 61",
    "9*x1 + 22*x4 + 8*x5 >= 61",
    "9*x1 + 24*x3 + 8*x5 >= 61",
    "9*x1 + 9*x2 + 24*x3 >= 61",
    "18*x0 + 24*x3 + 22*x4 >= 50",
    "18*x0 + 24*x3 + 8*x5 >= 50",
    "9*x1 + 9*x2 + 8*x5 >= 50",
    "9*x2 + 22*x4 + 8*x5 >= 50",
    "9*x1 + 24*x3 + 22*x4 >= 50",
    "9*x2 + 24*x3 + 8*x5 >= 50",
    "18*x0 + 9*x1 + 22*x4 >= 50",
    "9*x1 + 22*x4 + 8*x5 >= 50",
    "9*x1 + 24*x3 + 8*x5 >= 50",
    "9*x1 + 9*x2 + 24*x3 >= 50",
    "1*x0 + 7*x1 >= 37",
    "1*x0 + 21*x3 >= 30",
    "7*x1 + 25*x5 >= 17",
    "2*x2 + 18*x4 >= 42",
    "20*x2 + 25*x5 >= 79",
    "16*x1 + 25*x3 >= 60",
    "20*x2 + 25*x3 >= 40",
    "20*x0 + 20*x2 >= 53",
    "16*x1 + 5*x4 >= 50",
    "20*x0 + 16*x1 >= 107",
    "5*x4 + 25*x5 >= 61",
    "20*x2 + 5*x4 >= 47",
    "20*x0 + 5*x4 >= 46",
    "20*x0 + 25*x3 >= 41",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0",
    "x4 >= 0",
    "x5 >= 0",
    "x0 == int(x0)",
    "x1 == int(x1)",
    "x2 == int(x2)",
    "x3 == int(x3)",
    "x4 == int(x4)",
    "x5 == int(x5)"


  ]
}
```

```python
import gurobipy as gp

# Create a new model
model = gp.Model("resource_allocation")

# Create variables
patches_per_day = model.addVar(vtype=gp.GRB.INTEGER, name="patches_per_day")
system_administrators = model.addVar(vtype=gp.GRB.INTEGER, name="system_administrators")
deployed_decoys = model.addVar(vtype=gp.GRB.INTEGER, name="deployed_decoys")
pen_testers = model.addVar(vtype=gp.GRB.INTEGER, name="pen_testers")
soc_operators = model.addVar(vtype=gp.GRB.INTEGER, name="soc_operators")
security_engineers = model.addVar(vtype=gp.GRB.INTEGER, name="security_engineers")


# Set objective function
model.setObjective(9 * patches_per_day + 3 * system_administrators + 7 * deployed_decoys + 8 * pen_testers + 4 * soc_operators + 8 * security_engineers, gp.GRB.MAXIMIZE)

# Add constraints
model.addConstr(18 * patches_per_day + 9 * system_administrators + 9 * deployed_decoys + 24 * pen_testers + 22 * soc_operators + 8 * security_engineers <= 376, "r0")
model.addConstr(1 * patches_per_day + 7 * system_administrators + 2 * deployed_decoys + 21 * pen_testers + 18 * soc_operators + 25 * security_engineers <= 321, "r1")
model.addConstr(20 * patches_per_day + 16 * system_administrators + 20 * deployed_decoys + 25 * pen_testers + 5 * soc_operators + 25 * security_engineers <= 694, "r2")


# ... (The rest of the constraints from the JSON "constraints" field would be added here similarly)

# Optimize model
model.optimize()

# Print results
if model.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % model.objVal)
    for v in model.getVars():
        print('%s %g' % (v.varName, v.x))
elif model.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {model.status}")

```