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Comment Re:Interesting how few controls there are (Score 2) 49

I've worked for big companies most of my career, and regular employees making purchases, signing contracts, etc. takes an act of God. I can't spend $100 on supplies without getting competitive bids.

See, that's where you're going wrong. I've actually had clients tell me that a proposal has to be _over_ a certain dollar amount - if it's less than (for example) $50k, it's subject to a lot more oversight than, say, $1M. Small, petty cash type purchases are even more difficult, relatively speaking. Good luck trying to get approval for a new mouse for your workstation!

Comment Re:Virtual Private Raid (Score 2) 151

What you want for this is some variation on Shamir's Secret Sharing algorithm. Yes, he's the Shamir in RSA.
https://en.wikipedia.org/wiki/...
What this does is break a secret up into n different parts, but unlike raid, you can break it up in such a way that there is a threshold for the number of parts required to reconstruct the secret. So, for example, you could break a secret up into 6 parts and specify that any 4 parts will reconstruct the original data. If you have only 3 parts, then the secret is completely unknown (not just partially known).

Comment Re:I fail to see the problem (Score 1) 456

That sounds like a pretty bad experience with voicemail. With my voicemail, I open the Phone app on my phone and go to the Voicemail tab.
In here, I get a list of either the number of everyone who has left me a voicemail or their name if they are in my address book.
I have a blue dot next to the ones I haven't listened to. I tap on the message to listen to it. If I don't do anything, it's then kept, otherwise if I delete it it goes into the Deleted Messages. Want to listen to a message again? Tap on it.

Couldn't be easier.

Comment First ask yourself, what are you guarding against? (Score 3) 140

First ask yourself, what are you guarding against?

What guidelines has the client given you, what expectations do they have?
There's no point in you being so secure that the machine is virtually useless if the client happily stores these files on Dropbox/Google Drive etc.

Are you guarding against random drive-by hacking, script kiddies and the like, or are you guarding against an advanced persistent threat?
If you're guarding against the US Govt then your threat model is very different to if you're simply protecting yourself against casual hacking.

If you're concerned about an APT, then what level of threat do you expect to face? Is this a competitors company that has some guy who knows computers? Is it a multinational corporation with a large budget and a cybersecurity team? Is it a nation state? Is it the US Government?

The answers to those questions will heavily influence the appropriate course of action to take. If you're worried about casual hacking and the client has provided the files to you via Dropbox, then simply don't connect to any open wifi networks and don't connect to any wifi networks you don't know are secure. Make sure the wifi networks use WPA2.
If however you are concerned that the Govt. is likely out to get to your secrets, and they're specifically targeting you (as opposed to you being caught in a drift net) then you will want to physically disable the wifi, probably by taking the wifi card out of the laptop - it's likely on a small mezzanine card that is usually easily removed with a small Philips head screwdriver.

Comment Re:Crowdsourcing! (Score 1) 553

I donâ(TM)t work for free. If they want me to solve problems, they can sign a consulting contract.

But hereâ(TM)s an idea, if they are going to force software engineers to do this sort of thing, maybe they can break up some vexing Homeland Security software problem and piecemeal it out, sort of like crowdsourcingâ¦

I know, why don't they put them to work converting Slashcode to support Unicode?

Comment TVs, no. Monitors, yes. (Score 1) 179

The manufacturers can't even agree on which curvature is better, concave or convex (although most are concave now).
If you live on your own and watching TV is purely a solitary experience, or maybe with one other person, a curved TV can be OK, but if you're getting a few friends over to watch a movie or a sports game, only the person in the centre will have a decent view.

For a monitor, on the other hand, you're sitting on your lonesome, right in the sweet spot and a curved monitor can be great for some tasks.

Comment Re:WTF does it do? (Score 3, Informative) 48

OK, now it's starting to make more sense looking at the use cases

Here is a description of a few of the popular use cases for Apache Kafka. For an overview of a number of these areas in action, see this blog post.

Messaging
Kafka works well as a replacement for a more traditional message broker. Message brokers are used for a variety of reasons (to decouple processing from data producers, to buffer unprocessed messages, etc). In comparison to most messaging systems Kafka has better throughput, built-in partitioning, replication, and fault-tolerance which makes it a good solution for large scale message processing applications.
In our experience messaging uses are often comparatively low-throughput, but may require low end-to-end latency and often depend on the strong durability guarantees Kafka provides.

In this domain Kafka is comparable to traditional messaging systems such as ActiveMQ or RabbitMQ.

Website Activity Tracking
The original use case for Kafka was to be able to rebuild a user activity tracking pipeline as a set of real-time publish-subscribe feeds. This means site activity (page views, searches, or other actions users may take) is published to central topics with one topic per activity type. These feeds are available for subscription for a range of use cases including real-time processing, real-time monitoring, and loading into Hadoop or offline data warehousing systems for offline processing and reporting.
Activity tracking is often very high volume as many activity messages are generated for each user page view.

Metrics
Kafka is often used for operational monitoring data. This involves aggregating statistics from distributed applications to produce centralized feeds of operational data.

Log Aggregation
Many people use Kafka as a replacement for a log aggregation solution. Log aggregation typically collects physical log files off servers and puts them in a central place (a file server or HDFS perhaps) for processing. Kafka abstracts away the details of files and gives a cleaner abstraction of log or event data as a stream of messages. This allows for lower-latency processing and easier support for multiple data sources and distributed data consumption. In comparison to log-centric systems like Scribe or Flume, Kafka offers equally good performance, stronger durability guarantees due to replication, and much lower end-to-end latency.

Stream Processing
Many users of Kafka process data in processing pipelines consisting of multiple stages, where raw input data is consumed from Kafka topics and then aggregated, enriched, or otherwise transformed into new topics for further consumption or follow-up processing. For example, a processing pipeline for recommending news articles might crawl article content from RSS feeds and publish it to an "articles" topic; further processing might normalize or deduplicate this content and published the cleansed article content to a new topic; a final processing stage might attempt to recommend this content to users. Such processing pipelines create graphs of real-time data flows based on the individual topics. Starting in 0.10.0.0, a light-weight but powerful stream processing library called Kafka Streams is available in Apache Kafka to perform such data processing as described above. Apart from Kafka Streams, alternative open source stream processing tools include Apache Storm and Apache Samza.

Event Sourcing
Event sourcing is a style of application design where state changes are logged as a time-ordered sequence of records. Kafka's support for very large stored log data makes it an excellent backend for an application built in this style.

Commit Log
Kafka can serve as a kind of external commit-log for a distributed system. The log helps replicate data between nodes and acts as a re-syncing mechanism for failed nodes to restore their data. The log compaction feature in Kafka helps support this usage. In this usage Kafka is similar to Apache BookKeeper project.

Comment WTF does it do? (Score 1) 48

I've got no idea what Kafka does, and the summary really doesn't tell you much at all. I was about to put in a helpful post saying what it is, but even after visiting their home page I've still got no idea.

Apparently Kafka is used for building real-time data pipelines and streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.

How about the Intro
We think of a streaming platform as having three key capabilities:
It lets you publish and subscribe to streams of records. In this respect it is similar to a message queue or enterprise messaging system.
      It lets you store streams of records in a fault-tolerant way.
      It lets you process streams of records as they occur.

What is Kafka good for?
It gets used for two broad classes of application:
      Building real-time streaming data pipelines that reliably get data between systems or applications
      Building real-time streaming applications that transform or react to the streams of data

OK, I still am not really sure what it does.

Comment Re:battery life a braindead argument (Score 1) 300

I have a 2013 Mac Pro and a new 2016 MacBook Pro 13".
Whilst multi-thread performance is a different matter altogether, single core performance is pretty much on par (with a slight edge to the laptop) when comparing the two machines. The vast majority of software I run is single threaded, as I don't do video editing, 3D or gaming.

This is a Intel Xeon E5-1620 quad-core versus an i7-6567U

https://ark.intel.com/products...
https://ark.intel.com/products...

Power consumption is 130W to the Xeon versus 28W to the i7.

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