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Tuesday
Dec062016

Sponsored Post: Loupe, New York Times, ScaleArc, Aerospike, Scalyr, Gusto, VividCortex, MemSQL, InMemory.Net, Zohocorp

Who's Hiring?

  • The New York Times is looking for a Software Engineer for its Delivery/Site Reliability Engineering team. You will also be a part of a team responsible for building the tools that ensure that the various systems at The New York Times continue to operate in a reliable and efficient manner. Some of the tech we use: Go, Ruby, Bash, AWS, GCP, Terraform, Packer, Docker, Kubernetes, Vault, Consul, Jenkins, Drone. Please send resumes to: technicaljobs@nytimes.com

  • IT Security Engineering. At Gusto we are on a mission to create a world where work empowers a better life. As Gusto's IT Security Engineer you'll shape the future of IT security and compliance. We're looking for a strong IT technical lead to manage security audits and write and implement controls. You'll also focus on our employee, network, and endpoint posture. As Gusto's first IT Security Engineer, you will be able to build the security organization with direct impact to protecting PII and ePHI. Read more and apply here.

Fun and Informative Events

  • Your event here!

Cool Products and Services

  • A note for .NET developers: You know the pain of troubleshooting errors with limited time, limited information, and limited tools. Log management, exception tracking, and monitoring solutions can help, but many of them treat the .NET platform as an afterthought. You should learn about Loupe...Loupe is a .NET logging and monitoring solution made for the .NET platform from day one. It helps you find and fix problems fast by tracking performance metrics, capturing errors in your .NET software, identifying which errors are causing the greatest impact, and pinpointing root causes. Learn more and try it free today.

  • ScaleArc's database load balancing software empowers you to “upgrade your apps” to consumer grade – the never down, always fast experience you get on Google or Amazon. Plus you need the ability to scale easily and anywhere. Find out how ScaleArc has helped companies like yours save thousands, even millions of dollars and valuable resources by eliminating downtime and avoiding app changes to scale. 

  • Scalyr is a lightning-fast log management and operational data platform.  It's a tool (actually, multiple tools) that your entire team will love.  Get visibility into your production issues without juggling multiple tabs and different services -- all of your logs, server metrics and alerts are in your browser and at your fingertips. .  Loved and used by teams at Codecademy, ReturnPath, Grab, and InsideSales. Learn more today or see why Scalyr is a great alternative to Splunk.

  • InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. It runs natively on .Net, and provides a native .Net, COM & ODBC apis for integration. It also has an easy to use language for importing data, and supports standard SQL for querying data. http://InMemory.Net

  • VividCortex measures your database servers’ work (queries), not just global counters. If you’re not monitoring query performance at a deep level, you’re missing opportunities to boost availability, turbocharge performance, ship better code faster, and ultimately delight more customers. VividCortex is a next-generation SaaS platform that helps you find and eliminate database performance problems at scale.

  • MemSQL provides a distributed in-memory database for high value data. It's designed to handle extreme data ingest and store the data for real-time, streaming and historical analysis using SQL. MemSQL also cost effectively supports both application and ad-hoc queries concurrently across all data. Start a free 30 day trial here: http://www.memsql.com/

  • ManageEngine Applications Manager : Monitor physical, virtual and Cloud Applications.

  • www.site24x7.com : Monitor End User Experience from a global monitoring network. 

If any of these items interest you there's a full description of each sponsor below...

Click to read more ...

Monday
Dec052016

The Tech that Turns Each of Us Into a Walled Garden

 

How we treat each other is based on empathy. Empathy is based on shared experience. What happens when we have nothing in common?

Systems are now being constructed so we’ll never see certain kinds of information. Each of us live in our own algorithmically created Skinner Box /silo/walled garden, fed only information AIs think will be simultaneously most rewarding to you and their creators (Facebook, Google, etc).

We are always being manipulated, granted, but how we are being manipulated has taken a sharp technology driven change and we should be aware of it. This is different. Scary different. And the technology behind it all is absolutely fascinating.

Divided We Are Exploitable

Click to read more ...

Friday
Dec022016

Stuff The Internet Says On Scalability For December 2nd, 2016

Hey, it's HighScalability time:

 

A phrase you've probably heard a lot this week: AWS announces...

 

If you like this sort of Stuff then please support me on Patreon.

  • 18 minutes: latency to Mars; 100TB: biggest dynamodb table; 55M: visits to Kaiser were virtual; $2 Billion: yearly Uber losses; 91%: Apple's take of smartphone profits; 825: AI patents held by IBM; $8: hourly cost of a spot welding in the auto industry; 70%: Walmart website traffic was mobile; $3 billion: online black friday sales; 80%: IT jobs replaceable by automation; $7500: cost of the one terabit per second DDoS attack on Dyn; 

  • Quotable Quotes:
    • @BotmetricHQ: #AWS is deploying tens of thousands of servers every day, enough to power #Amazon in 2005 when it was a $8.5B Enterprise. #reInvent
    • bcantrill: From my perspective, if this rumor is true, it's a relief. Solaris died the moment that they made the source proprietary -- a decision so incredibly stupid that it still makes my head hurt six years later.
    • Dropbox: it can take up to 180 milliseconds for data traveling by undersea cables at nearly the speed of light to cross the Pacific Ocean. Data traveling across the Atlantic can take up to 90 milliseconds.
    • @James_R_Holmes: The AWS development cycle: 1) Have fun writing code for a few months 2) Delete and use new AWS service that replaces it
    • @swardley: * asked "Can Amazon be beaten?" Me : of course * : how? Me : ask your CEO * : they are asking Me : have you thought about working at Amazon?
    • @etherealmind: Whatever network vendors did to James Hamilton at AWS, he is NEVER going to forgive them.
    • Stratechery: the flexibility and modularity of AWS is the chief reason why it crushed Google’s initial cloud offering, Google App Engine, which launched back in 2008. Using App Engine entailed accepting a lot of decisions that Google made on your behalf; AWS let you build exactly what you needed.
    • @jbeda: AWS Lambda@Edge thing is huge. It is the evolution of the CDN. We'll see this until there are 100s of DCs available to users.
    • erikpukinskis: Everyone in this subthread is missing the point of open source industrial equipment. The point is not to get a cheap tractor, or even a good one. The point is not to have a tractor you can service. The point is to have a shared platform.
    • John Furrier: Mark my words, if Amazon does not start thinking about the open-source equation, they could see a revolt that no one’s ever seen before in the tech industry. If you’re using open source to build a company to take territory from others, there will be a revolt.
    • @toddtauber: As we've become more sophisticated at quantifying things, we've become less willing to take risks. via @asymco
    • Resilience Thinking: Being efficient, in a narrow sense, leads to elimination of redundancies-keeping only those things that are directly and immediately beneficial. We will show later that this kind of efficiency leads to drastic losses in resilience.
    • Connor Gibson: By placing advertisements around the outside of your game (in the header, footer and sidebars) as well as the possibility video overlays it is entirely possible to earn up to six figures through this platform.
    • Google Analytics: And maybe, if nothing else, I guess it suggests that despite the soup du jour — huge seed/A rounds, massive valuations, binary outcomes— you can sometimes do alright by just taking less money and more time.
    • badger_bodger: I'm starting to get Frontend Fatigue Fatigue.
    • Steve Yegge: But now, thanks to Moore's Law, even your wearable Android or iOS watch has gigs of storage and a phat CPU, so all the decisions they made turned out in retrospect to be overly conservative.  And as a result, the Android APIs and frameworks are far, far, FAR from what you would expect if you've come from literally any other UI framework on the planet.  They feel alien. 
    • David Rosenthal: Again we see that expensive operations with cheap requests create a vulnerability that requires mitigation. In this case rate limiting the ICMP type 3 code 3 packets that get checked is perhaps the best that can be done.
    • @IAmOnDemand: Private on public cloud means the you can burst public/private workloads intothe public and shut down yr premise or... #reinvent
    • @allingeek: It isn’t “serverless" if you own the server/device. It is just a functional programing framework. #reinvent
    • brilliantcode: If you told me to use Azure two years ago I would've laughed you out of the room. But here I am in 2016, using Azure, using ASP.net + IIS on Visual Studio. that's some powerful shit and currently AWS has cost leadership and perceived switching cost as their edge.
    • seregine: Having worked at both places for ~4 years each, I would say Amazon is much more of a product company, and a platform is really a collection of compelling products.
      Amazon really puts customers first...Google really puts ideas (or technology) first.
    • api: Amazon seems to be trying to build a 100% proprietary global mainframe that runs everywhere.
    • Athas: No, it [Erlang] does not use SIMD to any great extent. Erlang uses message passing, not data parallelism. Erlang is for concurrency, not parallelism, so it would benefit little from these kinds of massively parallel hardware.
    • @chuhnk: @adrianco @cloud_opinion funnily those of us who've built platforms at various startups now think a cloud provider is the best place to be.
    • @jbeda: So the guy now in charge of building OSS communities at @awscloud says you should just join Amazon? Communities are built on diversity.
    • @JoeEmison: There's also an aspect of some of these AWS services where they only exist because of problems with other AWS services.
    • logmeout: Until bandwidth pricing is fixed rather than nickel and dimeing us to death; a lot of us will choose fixed pricing alternatives to AWS, GCP and Rackspace.
    • arcticfox: 100%. I can't stand it [AWS]. It's unlimited liability for anyone that uses their service with no way to limit it. If you were able to set hard caps, you could have set yours at like $5 or even $0 (free tier) and never run into that.
    • @edw519: I hate batch processing so much that I won't even use the dishwasher. I just wash, dry, and put away real time.
    • @CodeBeard: it could be argued that games is the last real software industry. Libraries have reduced most business-useful code to glue.
    • Gall's Law: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system.
    • @mathewlodge: AWS now also designing its own ASICs for networking #Reinvent
    • @giano: From instances to services, AWS better than anybody else understood that use case specific wins over general purpose every day. #reinvent
    • @ben11kehoe: AWS hitting breadth of capability hard. Good counterpoint to recent "Google is 50% cheaper" news #reinvent
    • Michael E. Smith: But there are also positive effects of energized crowding. Urban economists and economic geographers have known for a long time that when businesses and industries concentrate themselves in cities, it leads to economies of scale and thus major gains in productivity. These effects are called agglomeration effects.
    • Andrew Huang: The inevitable slowdown of Moore’s Law may spell trouble for today’s technology giants, but it also creates an opportunity for the fledgling open-hardware movement to grow into something that potentially could be very big. 
    • Stratechery: This is Google’s bet when it comes to the enterprise cloud: open-sourcing Kubernetes was Google’s attempt to effectively build a browser on top of cloud infrastructure and thus decrease switching costs; the company’s equivalent of Google Search will be machine learning.

  • Just what has Amazon been up to?

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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Monday
Nov282016

How to Make Your Database 200x Faster Without Having to Pay More?

This is a guest repost Barzan Mozafari, an assistant professor at University of Michigan and an advisor to a new startup, snappydata.io, that recently launched an open source OLTP + OLAP Database built on Spark.

Almost everyone these days is complaining about performance in one way or another. It’s not uncommon for database administrators and programmers to constantly find themselves in a situation where their servers are maxed out, or their queries are taking forever. This frustration is way too common for all of us. The solutions are varied. The most typical one is squinting at the query and blaming the programmer for not being smarter with their query. Maybe they could have used the right index or materialized view or just re-write their query in a better way. Other times, you might have to spin up a few more nodes if your company is using a cloud service. In other cases, when your servers are overloaded with too many slow queries, you might set different priorities for different queries so that at least the more urgent one (e.g., CEO queries) finish faster. When the DB does not support priority queues, your admin might even cancel your queries to free up some resources for the more urgent queries.

No matter which one of these experiences you’ve had, you’re probably familiar with the pain of having to wait for slow queries or having to pay for more cloud instances or buying faster and bigger servers. Most people are familiar with traditional database tuning and query optimization techniques, which come with their own pros and cons. So we’re not going to talk about those here. Instead, in this post, we’re going to talk about more recent techniques that are far less known to people and in many cases actually lead to much better performance and saving opportunities.

To start, consider these scenarios:

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Friday
Nov252016

Stuff The Internet Says On Scalability For November 25th, 2016

Hey, it's HighScalability time:

 

Margaret Hamilton was honored with the Presidential Medal of Freedom for writing Apollo guidance software. Oddly, she's absent from best programmers of all time lists.

 

If you like this sort of Stuff then please support me on Patreon.

  • 98 seconds: before camera infected with malware; zeptosecond: smallest fragment of time ever measured; 50%: Google Cloud cheaper than AWS; 50%: of the world is on-line;

  • Quotable Quotes:
    • @skamille: Sometimes I think that human societies just weren't meant to scale to billions of people sharing arbitrary information
    • @joshk0: At @GetArbor we use #kubernetes to host a 30K QPS ad-tech serving platform. Maybe smaller than Pokemon Go but nothing to sneeze at.
    • HFT Guy: 2016 should be remembered as the year Google became a better choice than AWS. If 50% cheaper is not a solid argument, I don’t know what is.
    • Glenn Marcus: Hybrid [Progressive Web App] development takes 260% more effort man hours than Native development.
    • Bruce Schneier: I want to suggest another way of thinking about it in that everything is now a computer: This is not a phone. It’s a computer that makes phone calls. A refrigerator is a computer that keeps things cold. ATM machine is a computer with money inside. Your car is not a mechanical device with a computer. It’s a computer with four wheels and an engine… And this is the Internet of Things, and this is what caused the DDoS attack we’re talking about.
    • Bruce Schneier: I don’t like this. I like the world where the internet can do whatever it wants, whenever it wants, at all times. It’s fun. This is a fun device. But I’m not sure we can do that anymore.
    • southpolesteve: [Lambda] is cheaper and simpler to operate than our previous ec2+Opsworks setup. We get code to production faster and spend more time on actual business problems vs infrastructure problems.
    • Carlo Rovelli: Meaning = Information + Evolution
    • chadscira: We have been using Rancher as well... It allowed us to move away from DO and AWS. Now most of our infra is from OVH :). It's been smooth sailing. Because of massive costs savings we were able to just reinvest it in our own redundancy. Also 12-factor apps are pretty damn resilient.
    • Fiahil: Making separate [Google] accounts might not be enough considering they allegedly banned accounts related to each others by recovery address. Why would you think they would not do the same with accounts sharing occasionally the same laptop, the same ip address, and the same first and last name ?
    • @swardley: Arghhh, one of those "can IBM beat Amazon?" .... the answer has three parts 1) the game has become harder  2) yes it could  3) no it won't
    • fest: Replaying the sensor inputs and evaluating new estimated state is a really good way of debugging failures (because you can't just stop the system mid-air and evaluate internal state). It also helps with regression test suite and trying out new algorithms quickly.
    • @Tibocut: «Institutions prefer to have trillions sitting still than redistributing them towards opportunities» @asymco https://youtu.be/nD8QszyiVTY  at 2h45
    • @AlanaMassey: A gathering of two or more average looking white men is referred to by biologists as "a podcast."
    • @RyanHoliday: "How slow men are in matters when they believe they have time and how swift they are when necessity drives them to it." Machiavelli
    • agataygurturk: We use route53 health checks to invoke API gateway and thus the backend Lambda.
    • Paul Biggar: Yeah, BDSM. It’s San Francisco. Everyone’s into distributed systems and BDSM.
    • @mims: Since the Apollo program, we've privatized the R&D that drives all innovation. That might be a problem.
    • Backblaze:  We have fewer drives because over the last quarter we swapped out more than 3,500 2 terabyte (TB) HGST and WDC hard drives for 2,400 8 TB Seagate drives. So we have fewer drives, but more data.
    • @lee_newcombe: Fun finding from my talk earlier.  40 attendees: 37 on cloud, 3 about to start.  Only one trying serverless.  There's your opportunity folks
    • Resilience Thinking: In resilient systems everything is not necessarily connected to everything else. Overconnected systems are susceptible to shocks and they are rapidly transmitted through the system. A resilient system opposes such a trend; it would maintain or create a degree of modularity.

  • Security expert Rob Graham with a stunning blow by blow twitter story of a botnet infecting his brand new security camera. The whole process starts within 98 seconds of putting the camera on the internet, which is far faster than an ordinary mortal can configure the device to be secure. This was a cheap camera that had good reviews. At some point we need to think about all this too cheap equipment as being funded by a Botnet Subsidy. It's almost too much of a coincidence that all these cheap devices, meant to be bought like candy in the mass consumer market, have such obviously poor security. Maybe it's not an accident? See also, Pre-installed Backdoor On 700 Million Android

  • Their profit margin is your opportunity. With The Era of Cloud Price Discounts Is Fading and the cost of metal continuing to decrease, is now a good time to consider transitioning to bare metal on-premise type infrastructures? The incentives are now coming into alignment. Kubernetes: Finally...A True Cloud Platform by Sam Ghods, Co-founder, Box makes a good case for Kubernetes as the only truly portable infrastructure option.

  • This is both pure genius and a sure sign of the apocalypse. Exclusive Interview: How Jared Kushner Won Trump The White House. Democrats may have thought they had a technological lead because of the last presidential election, but it turns out they were fighting the last war. Technology changed and they did not. Old: targeting, organizing and motivating voters. New: Moneyball meets Social Media with a twist of message tailoring, sentiment manipulation and machine learning. If this presidential election could be represented as a battle between Peter Thiel and Eric Schmidt: Thiel triumphed. Traditional microtargeting is almost quaint. Now, using Facebook's ability to target users with dark posts, a newsfeed message seen by no one aside from the users being targeted, each user can be shown a world specifically tailored to push and prod their particular buttons. For an explanation see The Secret Agenda of a Facebook Quiz. That's why it's both genius and apocalyptical. Things will never be the same. 

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 ...

Tuesday
Nov222016

IT Hare: Ultimate DB Heresy: Single Modifying DB Connection. Part I. Performanc

Sergey Ignatchenko continues his excellent book series with a new chapter on databases. This is a guest repost

The idea of single-write-connection is used extensively in the post, as it's defined elsewhere I asked Sergey for a definition so the article would make a little more sense...

As for single-write-connection - I mean that there is just one app (named "DB Server" in the article) having a single DB connection to the database which is allowed to issue modifying statements (UPDATEs/INSERTs/DELETEs). This allows to achieve several important simplifications - first of all, all fundamentally non-testable concurrency issues (such as missing SELECT FOR UPDATE and deadlocks) are eliminated entirely, second - the whole thing becomes deterministic (which is a significant help to figure out bugs - even simple text logging has been seen to make the system quite debuggable, including post-mortem), and last but not least - this monopoly on updates can be used in quite creative ways to improve performance (in particular, to keep always-coherent app-level cache which can be like 100x-1000x more efficient than going to DB).

After we finished with all the preliminaries, we can now get to the interesting part – implementing our transactional DB and DB Server. We already mentioned implementing DB Server briefly in Chapter VII, but now we need much more detailed discussion on this all-important topic.

Hare pointing out:Transactional / operational DB is a place where all the automated decisions are made about your game (stock exchange, bank, etc.)First of all, let’s re-iterate what we’re speaking about. Transactional/operational DB is a place where all the automated decisions are made about your game (stock exchange, bank, etc.).

It stores things such as player accounts, with all their persistent attributes etc. etc.; it also stores communications related to payment processing, and so on, and so forth. And “DB Server” is our app handling access to DBMS (as noted in Chapter VII, I am firmly against having SQL statements issued directly by your Game Servers/Game Logic, so an intermediary such as DB Server is necessary).

As discussed above, ACID properties tend to be extremely important for transactional/operational DB. We don’t want money – or that artifact which is sold for real $20K on eBay – to be lost or duplicated. For this and some other reasons, we’ll be speaking about SQL databases for our transactional/operational DB (while it is possible to use NoSQL for transactional/operational DB – achieving strict guarantees is usually difficult, in particular because of lack of multi-object ACID transactions in most of NoSQL DBs out there, see discussion in [[TODO]] section above).

And now, we’re finally ready to start discussing interesting things.

Multi-Connection DB Access

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Tuesday
Nov222016

Sponsored Post: Loupe, New York Times, ScaleArc, Aerospike, Scalyr, Gusto, VividCortex, MemSQL, InMemory.Net, Zohocorp

Who's Hiring?

  • The New York Times is looking for a Software Engineer for its Delivery/Site Reliability Engineering team. You will also be a part of a team responsible for building the tools that ensure that the various systems at The New York Times continue to operate in a reliable and efficient manner. Some of the tech we use: Go, Ruby, Bash, AWS, GCP, Terraform, Packer, Docker, Kubernetes, Vault, Consul, Jenkins, Drone. Please send resumes to: technicaljobs@nytimes.com

  • IT Security Engineering. At Gusto we are on a mission to create a world where work empowers a better life. As Gusto's IT Security Engineer you'll shape the future of IT security and compliance. We're looking for a strong IT technical lead to manage security audits and write and implement controls. You'll also focus on our employee, network, and endpoint posture. As Gusto's first IT Security Engineer, you will be able to build the security organization with direct impact to protecting PII and ePHI. Read more and apply here.

Fun and Informative Events

  • Your event here!

Cool Products and Services

  • A note for .NET developers: You know the pain of troubleshooting errors with limited time, limited information, and limited tools. Log management, exception tracking, and monitoring solutions can help, but many of them treat the .NET platform as an afterthought. You should learn about Loupe...Loupe is a .NET logging and monitoring solution made for the .NET platform from day one. It helps you find and fix problems fast by tracking performance metrics, capturing errors in your .NET software, identifying which errors are causing the greatest impact, and pinpointing root causes. Learn more and try it free today.

  • ScaleArc's database load balancing software empowers you to “upgrade your apps” to consumer grade – the never down, always fast experience you get on Google or Amazon. Plus you need the ability to scale easily and anywhere. Find out how ScaleArc has helped companies like yours save thousands, even millions of dollars and valuable resources by eliminating downtime and avoiding app changes to scale. 

  • Scalyr is a lightning-fast log management and operational data platform.  It's a tool (actually, multiple tools) that your entire team will love.  Get visibility into your production issues without juggling multiple tabs and different services -- all of your logs, server metrics and alerts are in your browser and at your fingertips. .  Loved and used by teams at Codecademy, ReturnPath, Grab, and InsideSales. Learn more today or see why Scalyr is a great alternative to Splunk.

  • InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. It runs natively on .Net, and provides a native .Net, COM & ODBC apis for integration. It also has an easy to use language for importing data, and supports standard SQL for querying data. http://InMemory.Net

  • VividCortex measures your database servers’ work (queries), not just global counters. If you’re not monitoring query performance at a deep level, you’re missing opportunities to boost availability, turbocharge performance, ship better code faster, and ultimately delight more customers. VividCortex is a next-generation SaaS platform that helps you find and eliminate database performance problems at scale.

  • MemSQL provides a distributed in-memory database for high value data. It's designed to handle extreme data ingest and store the data for real-time, streaming and historical analysis using SQL. MemSQL also cost effectively supports both application and ad-hoc queries concurrently across all data. Start a free 30 day trial here: http://www.memsql.com/

  • ManageEngine Applications Manager : Monitor physical, virtual and Cloud Applications.

  • www.site24x7.com : Monitor End User Experience from a global monitoring network. 

If any of these items interest you there's a full description of each sponsor below...

Click to read more ...

Friday
Nov182016

Stuff The Internet Says On Scalability For November 18th, 2016

Hey, it's HighScalability time:

 

Now you don't have to shrink yourself to see inside a computer. Here's a fully functional 16-bit computer that's over 26 square feet huge! Bighex machine

 

If you like this sort of Stuff then please support me on Patreon.

  • 50%: drop in latency and CPU load after adopting PHP7 at Tumblr; 4,425: satellites for Skynet; 13%: brain connectome shared by identical twins; 20: weird & wonderful datasets for machine learning; 200 Gb/sec: InfiniBand data rate; 15 TB: data generated nightly by Large Synoptic Survey Telescope; 17.24%: top comments that were also first comments on reddit; $120 million: estimated cost of developing Kubernetes; 3-4k: proteins involved in the intracellular communication network;

  • Quotable Quotes:
    • Westworld: Survival is just another loop.
    • Leo Laporte: All bits should be treated equally. 
    • Paul Horner: Honestly, people are definitely dumber. They just keep passing stuff around. Nobody fact-checks anything anymore
    • @WSJ: "A conscious effort by a nation-state to attempt to achieve a specific effect" NSA chief on WikiLeaks 
    • encoderer: For the saas business I run, Cronitor, aws costs have consistently stayed around 10% total MRR. I think there are a lot of small and medium sized businesses who realize a similar level of economic utility.
    • @joshtpm: 1: Be honest: Facebook and Twitter maxed out election frenzy revenues and cracked down once the cash was harvested. Also once political ...
    • boulos: As a counter argument: very few teams at Google run on dedicated machines. Those that do are enormous, both in the scale of their infrastructure and in their team sizes. I'm not saying always go with a cloud provider, I'm reiterating that you'd better be certain you need to.
    • Renegade Facebook Employees: Sadly, News Feed optimizes for engagement. As we've learned in this election, bullshit is highly engaging. A bias towards truth isn't an impossible goal.
    • Russ White: The bottom line is this—don’t be afraid to use DNS for what it’s designed for in your network...We need to learn to treat DNS like it’s a part of the IP stack, rather than something that “only the server folks care about,” or “a convenience for users we don’t really take seriously for operations.”
    • Wizart_App: It's always about speed – never about beauty.
    • Michael Zeltser: MapReduce is just too low level and too dumb. Mixing complex business logic with MapReduce low level optimization techniques is asking too much. 
    • Michael Zeltser: One thing that always bugged me in MapReduce is its inability to reason about my data as a dataset. Instead you are forced to think in single key-value pair, small chunk, block, split, or file. Coming from SQL, it felt like going backwards 20 years. Spark has solved this perfectly.  
    • Guillaume Sachot: I can confirm that I've seen high availability appliances fail more often than non-clustered ones. And it's not limited to firewalls that crash together due to a bug in session sharing, I have noticed it for almost anything that does HA: DRBD instances, Pacemaker, shared filesystems...
    • Albert-Laszlo Barabasi: The bottom line is: Brother, never give up. When you give up, that’s when your creativity ends
    • SpaceX: According to a transcript received by Space News, he argued that the supercooled liquid oxygen that SpaceX uses as propellant actually became so cold that it turned into a solid. And that’s not supposed to happen.
    • Murat: Safety is a system-level property, unit testing of components is not enough.
    • @alexjc: 1/ As deep learning evolves as a discipline, it's becoming more about architecting highly complex systems that leverage data & optimization.
    • btgeekboy: Indeed. If there's one thing I've learned in >10 years of building large, multi-tenant systems, it's that you need the ability to partition as you grow. Partitioning eases growth, reduces blast radius, and limits complexity.
    • @postwait: Monitoring vendors that say they support histograms and only support percentiles are lying to their customers. Full stop. #NowYouKnow
    • @crucially: Fastly hit 5mm request per seconds tonight with a cache hit ratio of 96% -- proud of the team.
    • Rick Webb: Just because Silicon Valley has desperately wanted to believe for twenty years that communities can self-police does not make it true. 
    • Cybiote: Humans can additionally predict other agents and other things about the world based on intuitive physics. This is why they can get on without the huge array of sensors and cars cannot. Humans make up for the lack of sensors by being able to use the poor quality data more effectively. To put this in perspective, 8.75 megabits / second is estimated to pass through the human retina but only on the order of a 100 bits is estimated to reach conscious attention.
    • David Rand: What I found was consistent with the theory and the initial results: in situations where there're no future consequences, so it's in your clear self-interest to be selfish, intuition leads to more cooperation than deliberation.   
    • @crucially: Fastly hit 5mm request per seconds tonight with a cache hit ratio of 96% -- proud of the team
    • SpaceX: With deployment of the first 800 satellites, SpaceX will be able to provide widespread U.S. and international coverage for broadband services. Once fully optimized through the Final Deployment, the system will be able to provide high bandwidth (up to 1 Gbps per user), low latency broadband services for consumers and businesses in the U.S. and globally.
    • Steve Gibson: Anyone can make a mistake [regarding Pixel ownage], and Google is playing security catch up. But what they CAN and SHOULD be proud of is that they had the newly discovered problem patched within 24 hours!
    • dragonnyxx: Calling a 10,000 line program a "large project" is like calling dating someone for a week a "long-term relationship".
    • Brockman: I have three friends: confusion, contradiction, and awkwardness. That’s how I try to meander through life. Make it strange.
    • Martin Sústrik: In this particular case, almost everybody will agree that adding the abstraction was not worth it. But why? It was a tradeoff between code duplication and increased level of abstraction. But why would one decide that the well known cost of code duplication is lower than somewhat fuzzy "cost of abstraction"?

  • Biomedical engineering might be an area a lot of tech people interested in real-time monitoring and control at scale could be of help. Hr2: Wireless Spinal Tech, Climate Policy, Moon Impact. Researchers want to use wireless technology to record 100k+ neurons simultaneously, 24x7, for long periods of time. The goal is to use this data to control high dimensional systems, like when when reaching and grasping the shoulder, elbow, hand, wrist, and fingers must all work together in real-time. Sound familiar?

  • Making the Switch from Node.js to Golang. Digg switched a S3 heavy service from Node to Go and: Our average response time from the service was almost cut in half, our timeouts (in the scenario that S3 was slow to respond) were happening on time, and our traffic spikes had minimal effects on the service...With our Golang upgrade, we are easily able to handle 200 requests per minute and 1.5 million S3 item fetches per day. And those 4 load-balanced instances we were running Octo on initially? We’re now doing it with 2.

  • Not a lie. The best explanation to resilience. Resilience is how you maintain the self-organizing capacity of a system. Great explanation. The way you maintain the resilience of a system is by letting it probe its boundaries. The only way to make forest resilient to fire is to burn it. Efficiency is riding as close as possible to the boundary by using feedback to keep the system self-organizing.

  • Facebook does a lot of work making their mobile apps work over poor networks. One change they are making is Client-side ranking to more efficiently show people stories in feed. Previously, all story ranking occurred on the server and entries paged up to the device and displayed in order. The problem with this approach is that an article's rank could change while media is being loaded. Now a pool of stories is kept on the client and as new stories are added they are reranked and shown to users in rank order. This approach adapts well to slow networks because slow-loading content is temporarily down-ranked while it loads.

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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Wednesday
Nov162016

The Story of Batching to Streaming Analytics at Optimizely

Our mission at Optimizely is to help decision makers turn data into action. This requires us to move data with speed and reliability. We track billions of user events, such as page views, clicks and custom events, on a daily basis. To provide our customers with immediate access to key business insights about their users has always been our top most priority. Because of this, we are constantly innovating on our data ingestion pipeline.

In this article we will introduce how we transformed our data ingestion pipeline from batching to streaming to provide our customers with real-time session metrics.

Motivations 

Unification. Previously, we maintained two data stores for different use cases - HBase is used for computing Experimentation metrics, whereas Druid is used for calculating Personalization results. These two systems were developed with distinctive requirements in mind:

Experimentation

Personalization

Instant event ingestion

Delayed event ingestion ok

Query latency in seconds

Query latency in subseconds

Visitor level metrics

Session level metrics

As our business requirements evolve, however, things quickly became difficult to scale. Maintaining a Druid + HBase Lambda architecture (see below) to satisfy these business needs became a technical burden for the engineering team. We need a solution that reduces backend complexity and increases development productivity. More importantly, a unified counting infrastructure creates a generic platform for many of our future product needs.

Consistency. As mentioned above, the two counting infrastructures provide different metrics and computational guarantees. For example, Experimentation results show you the number of visitors visited your landing page whereas Personalization shows you the number of sessions instead. We want to bring consistent metrics to our customers and support both type of statistics across our products.

Real-time results. Our session based results are computed using MR jobs, which can be delayed up to hours after the events are received. A real-time solution will provide our customers with more up-to-date view of their data.

Druid + HBase

In our earlier posts, we introduced our backend ingestion pipeline and how we use Druid and MR to store transactional stats based on user sessions. One biggest benefit we get from Druid is the low latency results at query time. However, it does come with its own set of drawbacks. For example, since segment files are immutable, it is impossible to incrementally update the indexes. As a result, we are forced to reprocess user events within a given time window if we need to fix certain data issues such as out of order events. In addition, we had difficulty scaling the number of dimensions and dimension cardinality, and queries expanding long period of time became expensive.

On the other hand, we also use HBase for our visitor based computation. We write each event into an HBase cell, which gave us maximum flexibility in terms of supporting the kind of queries we can run. When a customer needs to find out “how many unique visitors have triggered an add-to-cart conversion”, for example, we do a scan over the range of dataset for that experimentation. Since events are pushed into HBase (through Kafka) near real-time, data generally reflect the current state of the world. However, our current table schema does not aggregate any metadata associated with each event. These metadata include generic set of information such as browser types and geolocation details, as well as customer specific tags used for customized data segmentation. The redundancy of these data prevents us from supporting large number of custom segmentations, as it increases our storage cost and query scan time.

SessionDB 

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Monday
Nov142016

How Urban Airship Scaled to 2.5 Billion Notifications During the U.S. Election

This is a guest post by Urban Airship. Contributors: Adam Lowry, Sean Moran, Mike Herrick, Lisa Orr, Todd Johnson, Christine Ciandrini, Ashish Warty, Nick Adlard, Mele Sax-Barnett, Niall Kelly, Graham Forest, and Gavin McQuillan

Urban Airship is trusted by thousands of businesses looking to grow with mobile. Urban Airship is a seven year old SaaS company and has a freemium business model so you can try it for free. For more information, visit www.urbanairship.com. Urban Airship now averages more than one billion push notifications delivered daily. This post highlights Urban Airship notification usage for the 2016 U.S. election, exploring the architecture of the system--the Core Delivery Pipeline--that delivers billions of real-time notifications for news publishers.

2016 U.S. Election

In the 24 hours surrounding Election Day, Urban Airship delivered 2.5 billion notifications—its highest daily volume ever. This is equivalent to 8 notification per person in the United States or 1 notification for every active smartphone in the world. While Urban Airship powers more than 45,000 apps across every industry vertical, analysis of the election usage data shows that more than 400 media apps were responsible for 60% of this record volume, sending 1.5 billion notifications in a single day as election results were tracked and reported.

 

Notification volume was steady and peaked when the presidential election concluded:

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