Their service runs apps in a consistent hybrid cloud environment.
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The post Worth Reading: Data Centric Computing appeared first on 'net work.
The computing industry is facing a number of challenges as Moore’s Law improvements in circuitry slow down, and they don’t all have to do with transistor counts and memory bandwidth and such. Another problem is that it has gotten progressively more costly to design chips at the same time that mass customization seems to be the way to provide unique processing capability specifically for precise workloads.
In recent decades, the US Defense Advanced Research Project Agency pumped huge sums of money into designing and manufacturing gigascale, terascale, and petascale systems, but in recent years this development arm of the US …
Adapteva Joins The Kilocore Club With Epiphany-V was written by Timothy Prickett Morgan at The Next Platform.
Nobody wants to be left out of the SD-WAN party.
docker run -e "RTPROP=-Ddns.servers=10.0.0.1" \The following Python script dnspair.py uses the sFlow-RT REST API to define a flow and log the resulting flow records:
-p 8008:8008 -p 6343:6343/udp -d sflow/sflow-rt
#!/usr/bin/env pythonRunning the script generates the following output:
import requests
import json
flow = {'keys':'dns:ipsource,dns:ipdestination',
'value':'bytes','activeTimeout':10,'log':True}
requests.put('http://localhost:8008/flow/dnspair/json',data=json.dumps(flow))
flowurl = 'http://localhost:8008/flows/json?name=dnspair&maxFlows=10&timeout=60'
flowID = -1
while 1 == 1:
r = requests.get(flowurl + "&flowID=" + str(flowID))
if r.status_code != 200: break
flows = r.json()
if len(flows) == 0: continue
flowID = flows[0]["flowID"]
flows.reverse()
for f in flows:
print json.dumps(f,indent=1)
$ ./dnspair.py
{
"value": 233370.92322668363,
"end": 1476234478177,
"name": "dnspair",
"flowID": Continue reading