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ISSN 1477-8092
Inside information
Broadband networks and all that comes with them – CDNs , nodes , edge servers etc , were expected to fall over in the pandemic . The forecast of friction points , and outright failure , as traffic caused by WFH and more time to use entertainment , was so solid that the big streamers voluntarily cut their data intensity , trading some loss of quality for lower volume ( a cynic might also point out that they also , thereby , cut their power bill ). But they needn ’ t have bothered . With almost no exceptions , networks worldwide held up pretty well . Sure , there were few live events but , even so , chapeau to the nets . Their resilience was in no small part down to the advances in real time monitoring , diagnostics , and even healing , provided by the participants in our annual survey of the test and monitor scene . It is striking that , for many , the only major amber light on the dash was in the human side of the story : how do you win new customers , how do you coach new deployments , how do you recruit and train new staff , without human interaction ? Of course , players in this field are more used to virtual working than most , but it has still been a major challenge . Darn it . When will they iron out this last wrinkle in the virtual world ? Every time a bad thing happens , what is the faulty component ? As I write this , Facebook and all its spawn have just come back online after six hours of global outage . They haven ’ t named a reason for the ‘ calamity ’ as yet , but it seems pretty sure it was a human making some kind of change to the DNS . And because Facebook ’ s greed , I mean constant search for economic and technological efficiency , had led it to lump all its services – FB , Insta , WhatsApp and all – on one private net to speed up availability and cross-sell ads to your cross-matched data , when the public Internet couldn ’ t find the top line FB DNS it couldn ’ t find anything at all . There is something very comforting that when calamity comes , most likely it still isn ’ t an unexplained catastrophe in the machine learned code , nor a sinister invader from cyberspace , but an over worked techy , or an over-confident intern , or someone with just oversize fingers , plain old getting it wrong .
Inside The Wrap 3-7 Research 8 Cover Story 10-16 Executive interview 18
Editorial
EUROMEDIA 3