While the natural habitat of HPC storage is supercomputing and enterprise datacenters, the growing popularity of edge computing means sometimes that hardware must live outside its comfort zone. …
High Performance Storage Sets Sail was written by Michael Feldman at The Next Platform.
This post is a textual version of the talk I gave at NLNOG 2019, You can watch the recording of the talk on youtube below if that’s your preferred medium:
<iframe width=“700” height=“328” src=“https://www.
All the posts I’ve published so far about Kubernetes Cluster API (CAPI) assume that the underlying infrastructure needs to be created. This is fine, because generally speaking that’s part of the value of CAPI—it will create new cloud infrastructure for every Kubernetes cluster it instantiates. In the case of AWS, this includes VPCs, subnets, route tables, Internet gateways, NAT gateways, Elastic IPs, security groups, load balancers, and (of course) EC2 instances. But what if you didn’t want CAPA to create AWS infrastructure? In this post, I’ll show you how to consume pre-existing AWS infrastructure with Cluster API for AWS (CAPA).
Why would one not want CAPA to create the necessary AWS infrastructure? There are a variety of reasons, but the one that jumps to my mind immediately is that an organization may have established/proven expertise and a process around the use of infrastructure-as-code (IaC) tooling like Terraform, CloudFormation, or Pulumi. In cases like this, such organizations would very likely prefer to continue to use the tooling they already know and with which they are already familiar, instead of relying on CAPA. Further, the use of third-party IaC tooling may allow for greater customization of the infrastructure than CAPA Continue reading
The companies are collaborating to support operators as they combine VNFs, SDN, and 5G in ONAP.
In this post I’ll explore replacing the heart of a network operating system’s configuration mechanism with the software developers take on version control. It can be argued that network operating systems, or at least good ones, already have a version control system. It’s that very system that allows you to roll back and carry out operations like commit-confirmed. More specifically, this is a version control system like Git but not specifically git.
As my day job rotates around Junos, I’ll concentrate on that. So why would anyone want to rip out the heart of Junos and replace it with a git backed directory full of configuration snippets? Software developers and now automation skilled engineers want the advantages of being able to treat the network like any other service delivering node. Imagine committing human readable configuration snippets to a network configuration directory and having the network check it out and do something with it.
Junos already has a configuration engine capable of rollbacks and provides sanity through semantic and syntax commit time checks. Mgd (the service you interact with) provides mechanisms to render interfaces through YANG models and generates the very configuration tree you interact with. You could say mgd takes Continue reading
Last week we started the Autumn 2019 Building Network Automation Solutions online course with an interesting presentation from Matthias Luft focused on open-source supply chain security
TL&DR: Can I download whatever stuff I found as my first Google hit and use it in my automation solution? ****, NO!
Matthias covered these topics:
Read more ...Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., VLDB’19
I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. These clusters are in high demand and approximate query processing both saves their users time and lightens the overall load on the cluster.
What’s especially nice about this paper is that we get a glimpse into the practical adoption issues of persuading users that it’s ok to approximate too.
We have implemented support for query time sampling in production big-data clusters at Microsoft: these clusters consist of tens of thousands of multi-core, multi-disk servers and are used by developers from many different businesses including Bing, Azure, and Windows. In total, the clusters store a few exabytes of data and are primarily responsible for all of the batch analytics at Microsoft.
Control over approximation is put into the hands of the user via extensions to the query language. In particular, support for expressing sampling requirements Continue reading
There are a more mobile phone connections (~7.9 billion) than the number of humans (~7.7 billion) colonising this planet.
Let me explain.
Clearly, not every person in the world has a mobile device. Here we’re talking about mobile connections that come from people with multiple devices (dual SIMs, tablets) and other integrated devices like cars, and other smart vehicles, and of course the myriad IOT devices. I don’t have to go too far — my electric 2 wheeler has a mobile connection that it uses to cheerfully download the updated firmware version and the software patches every now and then.
While the global population is growing at 1.08% annually, the mobile phone connections are growing at 2.0%. We will very soon be outnumbered by the number of mobile subscriptions, all happily chatting, tweeting and in general sending data over the network. Some of it would need low latency and low jitter, while some may be more tolerant to the delays and jitter.
What’s the big deal with mobile connections growing?
Well, historically most people have used their mobile phones to talk; to catch up on all the gossip on your neighbours and relatives.
Not anymore.
There are a more mobile phone connections (~7.9 billion) than the number of humans (~7.7 billion) colonising this planet.
Let me explain.
Clearly, not every person in the world has a mobile device. Here we’re talking about mobile connections that come from people with multiple devices (dual SIMs, tablets) and other integrated devices like cars, and other smart vehicles, and of course the myriad IOT devices. I don’t have to go too far — my electric 2 wheeler has a mobile connection that it uses to cheerfully download the updated firmware version and the software patches every now and then.
While the global population is growing at 1.08% annually, the mobile phone connections are growing at 2.0%. We will very soon be outnumbered by the number of mobile subscriptions, all happily chatting, tweeting and in general sending data over the network. Some of it would need low latency and low jitter, while some may be more tolerant to the delays and jitter.
So, what’s the big deal with mobile connections growing?
Well, historically most people have used their mobile phones to talk; to catch up on all the gossip on your neighbours and relatives.
Not Continue reading
Here are some of the most prominent venture capital and merger and acquisition news items from...
Hello my friends,
It is always cool to talk about various network technologies with the engineers from industry, and to meet some awesome chaps. I had a pleasure to attend such an event in London in the last months. Learn my findings on that.
In this episode, together with James Bensley and Richard Patterson from Sky we discuss the the NetLdn event series. The event, where you can discuss network technoligies with the peers and, perhaps, make some friends.
Don’t forget to subscribe for the channel, put likes and repost the video if you like that! 
If you have further questions or you need help with your networks, I’m happy to assist you, just send me message. Also don’t forget to share the article on your social media, if you like it.
BR,
Anton Karneliuk
The next phase of composable infrastructure involves 5G networks as a fabric type.
Verizon says 13 NFL stadiums will have 5G service when teams square off for week-one action.
$ docker run -p 6343:6343/udp sflow/sflowtoolThe -g option flattens the output so that it is more easily filtered using grep:
startDatagram =================================
datagramSourceIP 10.0.0.111
datagramSize 144
unixSecondsUTC 1321922602
datagramVersion 5
agentSubId 0
agent 10.0.0.20
packetSequenceNo 3535127
sysUpTime 270660704
samplesInPacket 1
startSample ----------------------
sampleType_tag 0:2
sampleType COUNTERSSAMPLE
sampleSequenceNo 228282
sourceId 0:14
counterBlock_tag 0:1
ifIndex 14
networkType 6
ifSpeed 100000000
ifDirection 0
ifStatus 3
ifInOctets 4839078
ifInUcastPkts 15205
ifInMulticastPkts 0
ifInBroadcastPkts 4294967295
ifInDiscards 0
ifInErrors 0
ifInUnknownProtos 4294967295
ifOutOctets 149581962744
ifOutUcastPkts 158884229
ifOutMulticastPkts 4294967295
ifOutBroadcastPkts 4294967295
ifOutDiscards 101
ifOutErrors 0
ifPromiscuousMode 0
endSample ----------------------
endDatagram =================================
$ docker run -p 6343:6343/udp sflow/sflowtool -g | grep ifInOctets
2019-09-03T22:37:21+0000 10.0.0.231 Continue reading
Wake up! It's HighScalability time:
Coolest or most coolest thing ever?
Do you like this sort of Stuff? I'd love your support on Patreon. I wrote Explain the Cloud Like I'm 10 for people who need to understand the cloud. And who doesn't these days? On Amazon it has 54 mostly 5 star reviews (125 on Goodreads). They'll learn a lot and likely add you to their will.
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