Leveraging AWS to Build a Scalable Data Pipeline

While at Netflix and LinkedIn Siddharth "Sid" Anand wrote some great articles for HS. Sid is back, this time as a Data Architect at Agari. Original article is here.

Data-rich companies (e.g. LinkedIn, Facebook, Google, and Twitter) have historically built custom data pipelines over bare metal in custom-designed data centers. In order to meet strict requirements on data security, fault-tolerance, cost control, job scalability, and uptime, they need to closely manage their core technology. Like serving systems (e.g. web application servers and OLTP databases) that need to be up 24x7 to display content to users the world over, data pipelines need to be up and running in order to pick the most engaging and up-to-date content to display. In other words, updated ranking models, new content recommendations, and the like are what make data pipelines an integral part of an end user’s web experience by picking engaging, personalized content. 

Agari, a data-driven email security company, is no different in its demand for a low-latency, reliable, and scalable data pipeline.  It must process a flood of inbound email and email authentication metrics, analyze this data in a timely manner, often enriching it with 3rd party data and model-driven derived data, and publish findings. One twist is that Agari, unlike the companies listed above, operates completely in the cloud, specifically in AWS.  This has turned out to be more a boon than a disadvantage. 

Below is one such data pipeline used at Agari.

Data Flow

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Gone Fishin' 2015

Well, not exactly Fishin', but I'll be on a month long vacation starting today.

I won't be posting (much) new content, so we'll all have a break. Disappointing, I know.

Please use this time for quiet contemplation and other inappropriate activities.

See you on down the road...

Stuff The Internet Says On Scalability For June 5th, 2015

Hey, it's HighScalability time:

Stunning Multi-Wavelength Image Of The Solar Atmosphere.

• 4x: amount spent by Facebook users
• Quotable Quotes:
  • Facebook: Facebook's average data set for CF has 100 billion ratings, more than a billion users, and millions of items. In comparison, the well-known Netflix Prize recommender competition featured a large-scale industrial data set with 100 million ratings, 480,000 users, and 17,770 movies (items).
  • @BenedictEvans: The number of photos shared on social networks this year will probably be closer to 2 trillion than to 1 trillion.
  • @jeremysliew: For every 10 photos shared on @Snapchat, 5 are shared on @Facebook and 1 on @Instagtam. 8,696 photos/sec on Snapchat.
  • @RubenVerborgh: “Don’t ask for an API, ask for data access. Tim Berners-Lee called for open data, not open services.” —@pietercolpaert #SemDev2015 #ESWC2015
  • Craig Timberg: When they thought about security, they foresaw the need to protect the network against potential intruders or military threats, but they didn’t anticipate that the Internet’s own users would someday use the network to attack one another. 
  • Janet Abbate: They [ARPANET inventors] thought they were building a classroom, and it turned into a bank.
  • A.C. Hadfield: The power of accurate observation is often called cynicism by those who don’t possess it.
  • @plightbo: Every business is becoming a software business
  • @potsdamnhacker: Replaced Go service with an Erlang one. Already used hot-code reloading, fault tolerance, runtime inspectability to great effect. #hihaters
  • @PHP_CEO: WE SPENT 18 MONTHS MIGRATING FROM A MONOLITH TO MICROSERVICES RESULT:- GITHUB GETS PAID FOR MORE PRIVATE REPOS - FIND/REPLACE IS HARDER
  • @alsargent: Given continuous deployment, average lifetime of a #Docker image @newrelic is 12hrs. Different ops pattern than VMs. #velocityconf
  • @PHP_CEO: ALSO THE NODE GUY WHO WAS A RUBY GUY THAT REWROTE IT ALL BECAME A RUST GUY AND MOVED TO THAILAND TO BECOME A NOMAD STARTUP GUY
  • @abt_programming: "If you think good architecture is expensive, try bad architecture" - Brian Foote - and Joseph Yoder
  • @KlangianProverb: "I thought studying distributed systems would make me understand software better—it made me understand reality better."—Old Klangian Proverb
  • @rachelmetz: google's error rate for image recognition was 28 percent in 2008, now it's like 5 percent, quoc le says.


• Fear or strength? Apple’s Tim Cook Delivers Blistering Speech On Encryption, Privacy. With Google Now on Tap Google is saying we've joyously crossed the freaky line and we unapologetically plan to leverage our huge lead in machine learning to the max. Apple knows they can't match this feature. Google knows this is a clear and distinct exploitable marketing idea, like a super thin MacBook Air slowly slipping out of a manila envelope.


• How does Kubernetes compare to Mesos? cmcluck, who works at Google and was one of the founders of the project explains: we looked really closely at Apache Mesos and liked a lot of what we saw, but there were a couple of things that stopped us just jumping on it. (1) it was written in C++ and the containers world was moving to Go -- we knew we planned to make a sustained and considerable investment in this and knew first hand that Go was more productive (2) we wanted something incredibly simple to showcase the critical constructs (pods, labels, label selectors, replication controllers, etc) and to build it directly with the communities support and mesos was pretty large and somewhat monolithic (3) we needed what Joe Beda dubbed 'over-modularity' because we wanted a whole ecosystem to emerge, (4) we wanted 'cluster environment' to be lightweight and something you could easily turn up or turn down, kinda like a VM; the systems integrators i knew who worked with mesos felt that it was powerful but heavy and hard to setup (though i will note our friends at Mesosphere are helping to change this). so we figured doing something simple to create a first class cluster environment for native app management, 'but this time done right' as Tim Hockin likes to say everyday. < Also, CoreOS (YC S13) Raises $12M to Bring Kubernetes to the Enterprise.


• If structure arises in the universe because electrons can't occupy the same space, why does structure arise in software?


• The cost of tyranny is far lower than one might hope. How much would it cost for China to intercept connections and replace content flowing at 1.9-terabits/second? About $200K says Robert Graham in Scalability of the Great Cannon. Low? Probably. But for the price of a closet in the new San Francisco you can edit an entire people's perception of the Internet in real-time.

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

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Paper: Heracles: Improving Resource Efficiency at Scale

Underutilization and segregation are the classic strategies for ensuring resources are available when work absolutely must get done. Keep a database on its own server so when the load spikes another VM or high priority thread can't interfere with RAM, power, disk, or CPU access. And when you really need fast and reliable networking you can't rely on QOS, you keep a dedicated line.

Google flips the script in Heracles: Improving Resource Efficiency at Scale, shooting for high resource utilization while combining different load profiles.

I'm assuming the project name Heracles was chosen not simply for his legendary strength, but because when strength failed, Heracles could always depend on his wits. Who can ever forget when Heracles tricked Atlas into taking the sky back onto his shoulders? Good times.

The problem: better utilization of compute resources while complying  service level objectives (SLOs) for latency-critical (LC) and best effort batch (BE) tasks: 

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What Does it Mean to Poke a Complex System?

A little bit of follow up...

In How Can We Build Better Complex Systems? Containers, Microservices, And Continuous Delivery I had a question about what Mary Poppendieck meant when she talked about poking complex systems.

InfoQ interviewed Mary & Tom Poppendieck and found out the answer:

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Why You Dont' Want to Aim for 100% Uptime According to Google's Urs Hölzle

Wait, you don't want 100% uptime? Who said such a crazy thing? Risk taker Urs Hölzle, senior VP for technical infrastructure, in Google's Infrastructure Chief Talks SDN:

Whenever you try something new, there are going to be problems with it....We were willing to take the risk to get the innovation. Our VP who runs our site reliability gave a great talk about not aiming for 100% uptime....The easiest way to make it be at 100% is to resist change, because change is when bad things happen. Looks great for your SLA, but it's bad for your business because you slow down innovation.... In the first year of running B4, [we asked] "Will we have an outage?" Realistically, yes there's a high chance because it was all new code. Are we going to be perfect? Probably not. You have to have a willingness to take a little risk.

Developing Products in the Style of Etsy

How should you go about structuring your project? We have two general paradigms that I'll characterize as flowing from the Etsy coaching tree, emphasising the monolith, and from the Netflix coaching tree, emphasizing microservices. This is of course an over simplification, but it's for instructional purposes only. For a broad comparison of the two approaches take a look at The Great Microservices Vs Monolithic Apps Twitter Melee.

This is not a good vs. evil sort of mythos. The Force is truly one. We simply have two valid and functional ways of looking the world.

I think wdewind nails the heart of the difference:

The point of the article is that local optimization gives you this tiny boost in the beginning for a long term cost that eventually moves the organization is a direction of shipping less. It's not that innovative technologies are bad.

The mentioned article is Choose Boring Technology by Dan McKinley, in which Dan does a great job exploring Etsy style development with both insight and wisdom. 

Dan explores four different principles:

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Stuff The Internet Says On Scalability For May 29th, 2015

Hey, it's HighScalability time:

Just imagine. 0-100 mph in 1.2 seconds. Astronaut's view from the Dragon spacecraft.

• $850B: mobile web market in 2018; 107: unicorns; 3.2 billion: # of people on the Internet; 10^82: atoms in the observable universe
• Quotable Quotes:
  • @cloud_opinion: appropriate term for people that resist Docker is "VM Huggers"
  • @mikeloukides: Scale systems, not teams. Adding scale shouldn’t mean adding people. Teams should scale sublinearly.  @shinynew_oz @ #velocityconf
  • Marc Levinson: If the market repeatedly misjudged the container, so did the state. Governments in New York City and San Francisco ignored the consequences of containerization as they wasted hundreds of millions of dollars reconstructing ports that were outmoded before the concrete was dry
  • @corbett: doesn't describe ultimate origin but "Inflation describes how the universe emerges from a patch of 10^-28cm & mass of only a few grams" -AG
  • @Gizmodo: Since last year, over 600 million more people have smartphones. It’s the age of mobile, says Sundar Pichai. #io15
  • @stshank: Android in a nutshell: >1 billion users, 4000 devices, 500 carriers, 400 device makers says @sundarpichai at #io15 
  • Carlos C:  Congratulations, FP hackers. You won the battle of simplicity to express...and here is where Go wins the battle of simplicity to achieve.
  • @markimbriaco: @joestump In my day, we emitted HTML from our apps. Pushed the packets uphill to the browsers. Through driving DDoS. And we liked it.
  • aikah: Yep, hail "Isomorphic micro-service oriented management."
  • @bitfield: "We haven't got time to automate this stuff, because we're too busy dealing with the problems caused by our lack of automation." —Everyone
  • @raju: India reported 851 Million active mobile connections in February 2015
  • @ValaAfshar: The average smartphone user checks their mobile device 214 times per day... and 86% of the time is apps (vs 14% browser). #codecon
  • @BradStone: Meeker: 87 percent millennials say smartphones never leave their side night or day. 44 percent use camera at least once a day. #CodeCon
  • @sequoia: "We're close to 1M people everyday staying at an @Airbnb home. We're here to stay" @bchesky #codecon
  • @pmarca: Moore's Law used to be about faster, now it's more about cheaper. Huge change with the biggest possible consequences. 
  • Nicolas Liochon: CAP: if all you have is a timeout, everything looks like a partition
  • See the complete post for the full list...


• This would change things. What Memory Will Intel’s Purley Platform Use?: One slide, titled: “Purley: Biggest Platform Advancement Since Nehalem” includes this post’s graphic, which tells of a memory with: “Up to 4x the capacity & lower cost than DRAM, and 500x faster than NAND.” Also, What High-Bandwidth Memory Is and Why You Should Care


• The question seldom asked with these kind of efforts: Does your idea of merit have merit? Startup Aims to Make Silicon Valley an Actual Meritocracy.


• The reason for us to save everything is that our collective data is the training ground for future AIs. We should train them to understand all of humanity. Hopefully they'll learn pity. Oh, wait...  The Internet With A Human Face: I've come to believe that a lot of what's wrong with the Internet has to do with memory. The Internet somehow contrives to remember too much and too little at the same time. 


• If you would like a rich exploration of the ethical implications of post-humanism then Apex: Nexus Arc Book 3 by Ramez Naam is the book for you. The framework is a game of iterated tit-for-tat. Ultimately if we don't want post-humans to destroy us lowly humans then we humans need to treat them well, from the start. If we harm them then the correct move on their part is to tat us. That won't be good. So open with a trust move and be nice. This radical notion might even work with normal humans.

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

Click to read more ...

A Toolkit to Measure Basic System Performance and OS Jitter

Jean Dagenais published a great response on a mechanical-sympathy thread to Gil Tene's article, The Black Magic Of Systematically Reducing Linux OS Jitter. It's full of helpful tools for tracking down jitter problems. I apologize for the incomplete attribution. I did not find a web presence for Jean. 

To complement the great information I got on the “Systematic Way to Find Linux Jitter”, I have created a toolkit that I now used to evaluate current and future trading platforms.

In case this can be useful, I have listed these tools, as well as the URLs to get the source code and a description of their usage. I am learning a lot by reading the source code, and the blog entry associated.

This is far from an exhaustive list, as every week I find either a new problem area or a new tool that improve my understanding of this beautiful problem domain ;)

These tools are grouped into these categories: 

1. CPU, Memory, Disk, Network
2. X86, Linux, and Java time resolution
3. Context Switches & Inter Thread Latency
4. System Jitter
5. Application Building Blocks: distruptor, openHft, Aeron & Workload Generator
6. Application Performance Testing

Happy Benchmarking and Jitter Chasing!

1. CPU, Memory, Disk, Network

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