A computer-implemented capacity planning method for Always On Availability Group, AG (AG1, AG2, AG3, AG4, AG5, AG6), cluster renewal, the method comprising - selecting a source AG cluster to be replaced with a target AG cluster; - selecting at least one performance monitor; - monitoring performance of instances (101a, 101b, 102) and databases (105, 105a, 106, 305) of the source AG cluster with the at least one performance monitor to obtain time series; - defining trends of the time series; - obtaining at least one benchmark value for source nodes (100, 300) in the source AG cluster and target nodes (100, 300) in the target AG cluster and calculating at least one benchmark ratio, wherein the benchmark ratio is defined for each benchmark as a ratio between a source node benchmark value and a respective target node benchmark value; - adjusting said time series based on the defined trends and adjusting at least one of said time series based on the at least one benchmark ratio; characterized in that the method further comprises - constituting a logical grouping of instances (101a, 101b, 102) and databases (105, 105a, 106, 305) of the source AG cluster for forming logical groups; - calculating workloads of said logical groups for each node (100, 300) of the source AG cluster on basis of the adjusted time series, and calculating, for each node (100, 300), a maximum total predicted workload caused by all instances (101a, 101b, 102) and databases (105, 105a, 106, 305) that may at any point of time be instantiated on the node (100, 300) by summing workloads of the respective logical groups; - predicting a required capacity of the target AG cluster nodes (100, 300) on basis of calculated workloads, wherein the required capacity of a selected parameter is obtained on basis of predicted maximum of the respective capacity requirement among all nodes (100, 300) in the AG cluster; and - comparing the required capacity of the target AG cluster nodes (100, 300) to at least one target node (100, 300) capacity to verify, whether the target node (100, 300) has sufficient capacity for all selected parameters. - selecting a source AG cluster to be replaced with a target AG cluster; - selecting at least one performance monitor; - monitoring performance of instances (101a, 101b, 102) and databases (105, 105a, 106, 305) of the source AG cluster with the at least one performance monitor to obtain time series; - defining trends of the time series; - obtaining at least one benchmark value for source nodes (100, 300) in the source AG cluster and target nodes (100, 300) in the target AG cluster and calculating at least one benchmark ratio, wherein the benchmark ratio is defined for each benchmark as a ratio between a source node benchmark value and a respective target node benchmark value; - adjusting said time series based on the defined trends and adjusting at least one of said time series based on the at least one benchmark ratio; - constituting a logical grouping of instances (101a, 101b, 102) and databases (105, 105a, 106, 305) of the source AG cluster for forming logical groups; - calculating workloads of said logical groups for each node (100, 300) of the source AG cluster on basis of the adjusted time series, and calculating, for each node (100, 300), a maximum total predicted workload caused by all instances (101a, 101b, 102) and databases (105, 105a, 106, 305) that may at any point of time be instantiated on the node (100, 300) by summing workloads of the respective logical groups; - predicting a required capacity of the target AG cluster nodes (100, 300) on basis of calculated workloads, wherein the required capacity of a selected parameter is obtained on basis of predicted maximum of the respective capacity requirement among all nodes (100, 300) in the AG cluster; and - comparing the required capacity of the target AG cluster nodes (100, 300) to at least one target node (100, 300) capacity to verify, whether the target node (100, 300) has sufficient capacity for all selected parameters.