KubeCon 2018 Day 2 Keynote

This is a liveblog of the day 2 (Wednesday) keynotes at KubeCon/CloudNativeCon 2018 in Seattle, WA. For additional KubeCon 2018 coverage, check out other articles tagged KubeCon2018.

Kicking off the day 2 keynotes, Liz Rice takes the stage at 9:02am (same time as yesterday, making me wonder if my clock is off by 2 minutes). Rice immediately brings out Janet Kuo, Software Engineer at Google and co-chair with Rice of the KubeCon/CloudNativeCon event program. Kuo will be delivering a Kubernetes project update.

Kuo starts off by reiterating the announcement of the Kubernetes 1.13 release, and looking back on her very first commit to Kubernetes in 2015 (just prior to the 1.0 release and the formation of the CNCF). Kuo talks about how Kubernetes, as a software cycle, has matured through the cycle of first focusing on innovation, then expanding to include scale, and finally expanding again to include stability (critical for enterprise adopters).

Reviewing usage details, Kuo states that she believes Kubernetes has moved—in the context of the technology adoption curve—from early adopters to early majority, the first phase in the mainstream market (and, for those who think in these terms, has crossed the chasm). However, this also Continue reading

Juniper CTO talks cloud, high-speed networking

Cloud computing is changing everything – just ask Juniper CTO Bikash Koley.Along with that notion Koley says that there are a number of certainties about the future of building out large cloud infrastructures: Multicloud is a real inflection point for enterprises and service providers; there will be private clouds and that the way all infrastructure will be built going forward will be different from the way things are done today.[ Learn who's developing quantum computers. ] juniper Bikash KoleyTo read this article in full, please click here

How we selected 10 hot data-center virtualization startups to watch

The selection process for our roundup of 10 data-center virtualization startups to watch began with 33 recommendations and nominations that were sent via HARO, LinkedIn, Twitter, and subscribers to the Startup50 email newsletter.Several of those startups had to be eliminated right off the bat not because they wouldn’t be a good fit for this roundup – they would be – but because they had already been covered in previous roundups, including those focused on storage, hybrid cloud and business continuity.To read this article in full, please click here

Juniper CTO talks cloud, high-speed networking

Cloud computing is changing everything – just ask Juniper CTO Bikash Koley.Along with that notion Koley says that there are a number of certainties about the future of building out large cloud infrastructures: Multicloud is a real inflection point for enterprises and service providers; there will be private cloud;s and that the way all infrastructure will be built going forward will be different from the way things are done today.[ Learn who's developing quantum computers. ] juniper Bikash KoleyTo read this article in full, please click here

How we selected 10 hot data-center virtualization startups to watch

The selection process for our roundup of 10 data-center virtualization startups to watch began with 33 recommendations and nominations that were sent via HARO, LinkedIn, Twitter, and subscribers to the Startup50 email newsletter.Several of those startups had to be eliminated right off the bat not because they wouldn’t be a good fit for this roundup – they would be – but because they had already been covered in previous roundups, including those focused on storage, hybrid cloud and business continuity.To read this article in full, please click here

GraphIt: A high-performance graph DSL

GraphIt: a high-performance graph DSL Zhang et al., OOPSLA’18

See also: http://graphit-lang.org/.

The problem with finding the optimal algorithm and data structures for a given problem is that so often it depends. This is especially true when it comes to graph algorithms.

It is difficult to implement high-performance graph algorithms. The performance bottlenecks of these algorithms depend not only on the algorithm and the underlying hardware, but also on the size and structure of the graph. As a result, different algorithms running on the same machine, or even the same algorithm running with different types of graph on the same machine, can exhibit different performance bottlenecks.

What we’d like therefore, is some way of expressing a graph algorithm at a high level such that we can map it into different implementations, each applying different optimisations as needed. For bonus points, we could then automate the search within the optimisation space to find the best performing combination for the circumstances at hand.

This is exactly what GraphIt does. GraphIt combines a DSL for specifying graph algorithms with a separate scheduling language that determines implementation policy. You can specify a schedule yourself, or use autotuning to discover optimal schedules for Continue reading

Notes about hacking with drop tools

In this report, Kasperky found Eastern European banks hacked with Raspberry Pis and "Bash Bunnies" (DarkVishnya). I thought I'd write up some more detailed notes on this.

Drop tools

A common hacking/pen-testing technique is to drop a box physically on the local network. On this blog, there are articles going back 10 years discussing this. In the old days, this was done with $200 "netbook" (cheap notebook computers). These days, it can be done with $50 "Raspberry Pi" computers, or even $25 consumer devices reflashed with Linux.

A "Raspberry Pi" is a $35 single board computer, for which you'll need to add about another $15 worth of stuff to get it running (power supply, flash drive, and cables). These are extremely popular hobbyist computers that are used everywhere from home servers, robotics, and hacking. They have spawned a large number of clones, like the ODROID, Orange Pi, NanoPi, and so on. With a quad-core, 1.4 GHz, single-issue processor, 2 gigs of RAM, and typically at least 8 gigs of flash, these are pretty powerful computers.

Typically what you'd do is install Kali Linux. This is a Linux "distro" that contains all the tools hackers want to Continue reading

The Case of the Missing LDP Neighbor

R1 and R2 are cabled up twice to each other via their gig0/0/1 interfaces and their gig0/0/7 interfaces. Each connection is in its own subnet, and each interface configured for OSPF and MPLS.  But while we have 2 OSPF neighbors between them… we only have 1 LDP neighbor.

R1#show mpls int
Interface   IP        Tunnel    BGP Static Operational
Gi0/0/1   Yes (ldp)     No       No  No     Yes
Gi0/0/7   Yes (ldp)     No       No  No     Yes
R1#

So as you can see from the output of show mpls interface, gig0/0/1 and gig0/0/7 are both configured for MPLS LDP.  Why then if we look below do we see only 1 MPLS LDP neighbor between them?  

What is the problem?  Actually… in this situation there isn’t a problem.  This is actually expected behavior.

R1#sh mpls ldp neighbor
    Peer LDP Ident: 10.100.100.2:0; Local LDP Ident 10.100.100.1:0
    TCP connection: 10.100.100.2.22592 - 10.100.100.1.646
    State: Oper; Msgs sent/rcvd: 184/184; Downstream
    Up time: 02:32:11
    LDP discovery sources:
      GigabitEthernet0/0/1, Src IP addr: 10.1.1.2
      GigabitEthernet0/0/7, Src IP addr: 10.1.7.2
        Addresses bound to peer LDP Ident:
           Continue reading

OAuth Auth Server through Workers

OAuth Auth Server through Workers

Let’s pretend I own a service and I want to grant other services access to my service on behalf of my users. The familiar OAuth 2.0 is the industry standard used by the likes of Google sign in, Facebook, etc. to communicate safely without inconveniencing users.

Implementing an OAuth Authentication server is conceptually simple but a pain in practice. We can leverage the power of Cloudflare Worker to simplify the implementation, reduce latency, and segregate our service logic from the authentication layer.

For those unfamiliar with OAuth, I highly recommend reading a more in depth article.

The steps of the OAuth 2.0 workflow are as follows:

  1. The consumer service redirects the user to a callback URL that was setup by the auth server. At this callback URL, the auth server asks the user to sign in and accept the consumer permissions requests.
  2. The auth server redirects the user to the consumer service with a code.
  3. The consumer service asks to exchange this code for an access token. The consumer service validates their identity by including their client secret in the callback URL.
  4. The auth server gives the consumer the access token.
  5. The consumer service can now use Continue reading

How Java has stood the test of time

Java has survived for more than two decades and continues to be one of the top programming languages in use today. What accounts for the language's success and how has it changed to accommodate more modern technology?Java's rise to power Java initially appeared in 1995, evolving from a 1991 innovation called "Oak". It was apparently the right time for engineers looking to grow distributed systems. Some of the more popular languages back then -- C, C++, and even Cobol for some efforts -- involved steep learning curves. Java's multi-threading, allowing the concurrent execution of two or more parts of a program, ended the struggle to get multi-tasking working. Java quickly became the de facto language for mission-critical systems. Since that time, new languages have come and gone, but java has remained entrenched and hard to replace. In fact, Java has stood as one of the top two computing languages practically since its initial appearance as this Top Programming Languages article suggests.To read this article in full, please click here

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