The importance of non-visual and on-line monitoring of udder health increases as the contact between humans and animals decreases, for example, in robotic milking systems. Several indicator systems have been introduced commercially, and a number of techniques are currently in use. This study describes the kinetics of seven indigenous milk parameters for monitoring udder inflammation in an Escherichia coli lipopolysaccharide (LPS, endotoxin)-induced mastitis model. Proportional milk from LPS-infused quarters was compared with milk from parallel quarters, which were placebo-treated with sterile 0.9% NaCl solution. Somatic cell counts (SCCs), the acute phase proteins (APP), that is, milk amyloid A (MAA) and haptoglobin (Hp), and the enzymes N-acetyl-β-D-glucosaminidase (NAGase), lactate dehydrogenase (LDH), alkaline phosphatase (AP) and acid phosphatase (AcP) were measured at fixed intervals during the period from −2 to +5 days after LPS and NaCl infusions. All parameters responded significantly faster and were more pronounced to the LPS infusions compared with the NaCl infusions. All parameters were elevated in the proportional milk collected at the first milking 7 h after infusion and developed a monophasic response, except Hp and MAA that developed biphasic response. SCC, LDH, NAGase and Hp peaked at 21 h followed by AP, AcP and MAA peaking at 31 h with the highest fold changes seen for MAA (23 780×), LDH (126×), NAGase (50×) and Hp (16×). In the recovery phase, AP, AcP and Hp reached base levels first, at 117 h, whereas LDH, NAGase and MAA remained elevated following the pattern of SCC. Minor increases of the milk parameters were also seen in the neighboring (healthy) quarters. Distinction between inflamed and healthy quarters was possible for all the parameters, but only for a limited time frame for AP and AcP. Hence, when tested in an LPS mastitis model, the enzymes LDH, NAGase and AP in several aspects performed equally with SCC and APP as inflammatory milk indicators of mastitis. Furthermore, these enzymes appear potent in the assessment of a valuable time sequence of inflammation, a necessary ingredient in modeling of programs in in-line surveillance systems.