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CLMC monitoring specification for a basic scenario.md 4.70 KiB

Adaptive Streaming Use Case Scenario

Infrastructure Slice

compute_node_config

compute_node_config slice location comp_node cpu memory storage timestamp
compute_node_config SLICE1 locA dc1 4 8 16 1515583926868000000
compute_node_config SLICE1 locB dc2 8 16 64 1515583926868000000
compute_node_config SLICE1 locC dc3 48 128 4000 1515583926868000000

network_config

| network_config | slice | network | bandwidth | timestamp | | --- | --- | --- | --- | --- | --- |--- | | network_config | SLICE1 | data1 | 100 | 1515583926868000000 |

How do we describe network configuration ? What is a format of an infrastructure slices ? What is the relevant information ?

network_interface_config

network_interface_config slice comp_node port network rx_constraint tx_constraint timestamp
network_config SLICE1 dc1 enps03 data1 1000 1000 1515583926868000000
network_config SLICE1 dc2 enps03 data1 1000 1000 1515583926868000000
network_config SLICE1 dc3 enps03 data1 1000 1000 1515583926868000000

NAP

ipendpoint_route

ipendpoint_route location ipendpoint_id cont_nav avg_http_requests_fqdn_rate avg_network_fqdn_latency time
ipendpoint_route <common tags> DC1 ipendpoint1 http://netflix.com/scream 386, 50

Media Service

There are various aggregated metrics we can calculate but in the use case scenario we postpone that till later.

sfc_instance_config

sfc_i_config,<common_tags>,state <fields> timestamp

sf_i_config

sf_i_config,<common_tags>,state <fields> timestamp

IPEndpoint

All IPEndpoint measurements have the following global tags injected by a configured Telegraf agent

  • location
  • compute_node
  • sfc
  • sfc_i
  • sf
  • sfc_i
  • ipendpoint

Also NOTE: the metrics provided in the measurements below are effectively a 'snapshot' of usage over a relatively small period of time. The length of this snapshot may vary, depending on the underlying implementation of the instrumentation, so we might have to assume this snapshot is essentially an average of a period of 1 second. Measuring 'usage' is dependent on the units, for example as a proportion of a resource or as a proportion of time.

ipendpoint_config

ipendpoint_config location sfc sfc_i sf sf_i ipendpoint state cpu memory storage timestamp
ipendpoint_config dc1 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint1 placed 2 4 16 1515583926868000000
ipendpoint_config dc2 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint2 placed 8 16 64 1515583926868000000
ipendpoint_config dc3 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint3 placed 48 128 4000 1515583926868000000
ipendpoint_config dc1 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint1 booted 2 4 16 1515583926868000000
ipendpoint_config dc2 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint2 booted 8 16 64 1515583926868000000
ipendpoint_config dc3 MediaServiceTemplate MediaServiceA AdaptiveStreamingComp AdaptiveStreamingComp1 ipendpoint3 booted 48 128 4000 1515583926868000000

cpu_usage

cpu_usage <common tags> cpu avg_cpu_time_user avg_cpu_time_idle timestamp
cpu <common tags> 1 40 5 1515583926868000000

net_port_io

net_port_io <common tags> avg_packet_drop_rate avg_packet_error_rate rx_bytes_port_m rx_packets_m tx_bytes_port_m tx_packets_port_m timestamp
net_port_io <common tags> 0.3 0.1 13567 768 8102 356 1515583926868000000

mpegdash_service

mpegdash_service_mon <common tags> cont_nav cont_rep user_profile avg_req_rate avg_resp_time peak_resp_time avg_error_rate avg_throughput avg_quality_delivered avg_startup_delay avg_dropped_segments timestamp
mpegdash_service_mon <common tags> http://netflix.com/scream h264 profileA 10 40 230 0.2 200 5 1200 2