It might be clearer with an example. After running the optimize!() function, CPLEX prints out information such as
julia> optimize!(model)
CPXPARAM_TimeLimit 3600
CPXPARAM_Threads 1
Warning: Nonintegral bounds for integer variables rounded.
1 of 1 MIP starts provided solutions.
MIP start ‘m1’ defined initial solution with objective 1003023.1305.
Warning: Nonintegral bounds for integer variables rounded.
Tried aggregator 1 time.
MIP Presolve eliminated 20 rows and 0 columns.
MIP Presolve modified 10 coefficients.
Reduced MIP has 1448 rows, 9520 columns, and 45848 nonzeros.
Reduced MIP has 428 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.00 sec. (27.40 ticks)
Tried aggregator 1 time.
Reduced MIP has 1448 rows, 9520 columns, and 45848 nonzeros.
Reduced MIP has 428 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.02 sec. (25.30 ticks)
Probing time = 0.00 sec. (6.45 ticks)
Clique table members: 20.
MIP emphasis: balance optimality and feasibility.
MIP search method: dynamic search.
Parallel mode: none, using 1 thread.
Root relaxation solution time = 0.00 sec. (19.96 ticks)
Nodes Cuts/
Node Left Objective IInf Best Integer Best Bound ItCnt Gap

0+ 0 1003023.1305 9110496.3688 
0 0 937733.4054 78 1003023.1305 937733.4054 672 6.51%
0 0 960438.9696 95 1003023.1305 Cuts: 285 770 4.25%
0 0 967788.9910 92 1003023.1305 Cuts: 193 842 3.51%
0 0 972277.3234 113 1003023.1305 Cuts: 134 940 3.07%
0 0 975773.3675 98 1003023.1305 Cuts: 130 1039 2.72%
0 0 978571.6876 101 1003023.1305 Cuts: 124 1122 2.44%
0 0 980584.2773 126 1003023.1305 Cuts: 108 1221 2.24%
0 0 983789.9356 72 1003023.1305 Cuts: 116 1347 1.92%
0 0 985012.8528 92 1003023.1305 Cuts: 65 1418 1.80%
0 0 985850.9575 96 1003023.1305 Cuts: 69 1494 1.71%
0 0 986708.7299 96 1003023.1305 Cuts: 67 1575 1.63%

0+ 0 992729.7930 986708.7299 0.61%
0 0 986922.4191 74 992729.7930 Cuts: 61 1643 0.58%
0 0 987047.8536 86 992729.7930 Cuts: 67 1706 0.57%
0 0 987160.9933 62 992729.7930 Cuts: 46 1771 0.56%
0 0 987241.1345 101 992729.7930 Cuts: 34 1837 0.55%
0 0 987461.5478 88 992729.7930 Cuts: 59 1890 0.53%
0 0 987706.3188 100 992729.7930 Cuts: 72 1989 0.51%
0 0 987831.4118 83 992729.7930 Cuts: 56 2066 0.49%
0 0 987919.9779 98 992729.7930 Cuts: 47 2125 0.48%
0 2 987919.9779 98 992729.7930 987920.8848 2125 0.48%
Elapsed time = 1.77 sec. (2902.57 ticks, tree = 0.01 MB, solutions = 2)
30 22 988495.5139 68 992729.7930 988068.2933 2716 0.47%
89 57 990548.1597 51 992729.7930 988253.6533 3398 0.45%
120 70 989589.1727 66 992729.7930 988534.2782 3918 0.42%
178 91 989630.9612 58 992729.7930 988878.3892 4525 0.39%
228 108 992527.9493 50 992729.7930 989338.6592 5330 0.34%
283 124 990903.1868 43 992729.7930 989599.2238 6041 0.32%
360 152 992513.4992 33 992729.7930 989942.6504 6892 0.28%
422 148 cutoff 992729.7930 990394.5056 7779 0.24%
493 155 992336.9089 25 992729.7930 990788.1302 8577 0.20%
Cover cuts applied: 2
Implied bound cuts applied: 7
Flow cuts applied: 107
Mixed integer rounding cuts applied: 41
Flow path cuts applied: 39
Root node processing (before b&c):
Real time = 1.77 sec. (2896.93 ticks)
Sequential b&c:
Real time = 1.67 sec. (3203.84 ticks)

Total (root+branch&cut) = 3.44 sec. (6100.77 ticks)
I would like to access this information.
There’s no function directly in the CPLEX API for C that does this as far as I’m aware, so it’s probably not just me missing a JuMP function or a missing bridge.
It’s probably local variables that are destroyed when CPLEX is done running. As these are not Julia variables in the first place, I have little hope that it’s possible to retrieve these information in a neat way but I might be wrong.