Cloud compute scheduling using a heuristic contention model

A method for contention monitoring for cloud computing, the method comprising:

• collecting, by a compute node of a cloud computing cluster, performance data indicative of cache memory contention of the compute node;
• determining, by the compute node, a contention score as a function of the performance data, the contention score including a contention metric and a contention score level indicative of the contention metric, wherein determining the contention score comprises determining the contention score level by comparing the rate of cache misses per reference number of instructions to one or more threshold values;
• and
• storing, by the compute node, the contention score in a cloud state database, the cloud state database accessible by a cloud controller of the cloud computing cluster;
• wherein determining the contention score level further comprises:
• comparing the rate of cache misses per reference number of instructions to a low contention threshold value;
• setting the contention score level to a low contention level in response to determining that the rate is less than the low contention threshold value;
• comparing the rate of cache misses per reference number of instructions to a high contention threshold value;
• setting the contention score level to a medium contention level in response to determining that the rate is greater than or equal to the low contention threshold value and less than the high contention threshold value;
• and
• setting the contention score level to a high contention level in response to determining that the rate is greater than or equal to the high contention threshold value.

One or more computer-readable storage media comprising a plurality of instructions that in response to being executed cause a compute node of a cloud computing cluster to:

• collect performance data indicative of cache memory contention of the compute node;
• determine a contention score as a function of the performance data, the contention score including a contention metric and a contention score level indicative of the contention metric, wherein to determine the contention score comprises to determine the contention score level by comparing the rate of cache misses per reference number of instructions to one or more threshold values;
• and
• store the contention score in a cloud state database, the cloud state database accessible by a cloud controller of the cloud computing cluster;
• wherein to determine the contention score level further comprises to:
• compare the rate of cache misses per reference number of instructions to a low contention threshold value;
• set the contention score level to a low contention level in response to determining that the rate is less than the low contention threshold value;
• compare the rate of cache misses per reference number of instructions to a high contention threshold value;
• set the contention score level to a medium contention level in response to determining that the rate is greater than or equal to the low contention threshold value and less than the high contention threshold value;
• and
• set the contention score level to a high contention level in response to determining that the rate is greater than or equal to the high contention threshold value.