The paper aims to calculate indicators of resilience in cows and evaluate the effects on them. After editing, 254,141 data on daily milk yield from seven farms from 2022 to 2023 remained in the file. The farms used three milking technologies: a milking parlour, a robotic milking parlour, and milking robots. A regression function described by Legendre polynomials of the third degree was used to calculate the predicted lactation curve for individual lactations. The yield fluctuations were represented by four parameters in total, namely the variance of daily milk yield, as well as three indicators defined based on deviations of actual yield from the predicted lactation curve, namely variance, lag-1 autocorrelation and skewness of deviations. All evaluated indicators were statistically significantly influenced by systematic effects of the environment, such as the farm (thus the milking technology used), the year and calving season, the order of lactation and the average productivity of the dairy cow. Noticeable differences were also found between the breed groups. In further analyses, i.e., the model equations must consider these effects in estimating genetic parameters and genomic breeding values.