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Category Archives for "High Scalability"

Sponsored Post: Datadog, InMemory.Net, Triplebyte, Etleap, Scalyr, MemSQL

Who's Hiring? 

  • Triplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Make your job search O(1), not O(n). Apply here.

  • Need excellent people? Advertise your job here! 

Fun and Informative Events

  • Advertise your event here!

Cool Products and Services

  • Datadog is a cloud-scale monitoring platform that combines infrastructure metrics, distributed traces, and logs all in one place. With out-of-the-box dashboards and seamless integrations with over 200 technologies, Datadog provides end-to-end visibility into the health and performance of modern applications at scale. Build your own rich dashboards, set alerts to identify anomalies, and collaborate with your team to troubleshoot and fix issues fast. Start a free trial and try it yourself.

  • 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

How Ably Efficiently Implemented Consistent Hashing

This is a guest post by Srushtika Neelakantam, Developer Advovate for Ably Realtime, a realtime data delivery platform.

Ably’s realtime platform is distributed across more than 14 physical data centres and 100s of nodes. In order for us to ensure both load and data are distributed evenly and consistently across all our nodes, we use consistent hashing algorithms.

In this article, we’ll understand what consistent hashing is all about and why it is an essential tool in scalable distributed system architectures. Further, we’ll look at data structures that can be used to implement this algorithm efficiently at scale. At the end, we’ll also have a look at a working example for the same.

Hashing revisited

Remember the good old naïve Hashing approach that you learnt in college? Using a hash function, we ensured that resources required by computer programs could be stored in memory in an efficient manner, ensuring that in-memory data structures are loaded evenly. We also ensured that this resource storing strategy also made information retrieval more efficient and thus made programs run faster.

The classic hashing approach used a hash function to generate a pseudo-random number, which is then divided by the size of the memory Continue reading

Stuff The Internet Says On Scalability For June 15th, 2018

Hey, it's HighScalability time:

 

Scaling fake ratings. A 5 star 10,000 phone Chinese click farm. (English Russia)

Do you like this sort of Stuff? Please lend me your support on Patreon. It would mean a great deal to me. And if you know anyone looking for a simple book that uses lots of pictures and lots of examples to explain the cloud, then please recommend my new book: Explain the Cloud Like I'm 10. They'll love you even more.

  • 1.6x: better deep learning cluster scheduling on k8s; 100,000: Large-scale Diverse Driving Video Database; 3rd: reddit popularity in the US; 50%: increase in Neural Information Processing System papers, AI bubble? 420 tons: leafy greens from robot farms; 75%: average unused storage on EBS volumes; 12TB: RAM on new Azure M-series VM; 10%: premium on Google's single-tenant nodes; $7.5B: Microsoft's cost of courting developers; 100th: flip-flop invention anniversary; 1 million: playlist dataset from Spotify; 38GB torrent: Stackoverflow public database; 85%: teens use YouTube; 20%-25%: costs savings using Aurora; 80%: machine learning Ph.D.s work at Google or Facebook; 18: years of Continue reading

Open Source Database HA Resources from Severalnines

 

Severalnines has spent the last several years writing blogs and crafting content to help make your open source database solutions highly available. We are fans of highscalability.com and wanted to post some links to our top resources to help readers learn more how to make MySQL, MongoDB, MariaDB, Percona and PostgreSQL databases scalable.

Top HA Resources for MySQL & MariaDB

Stuff The Internet Says On Scalability For June 8th, 2018

Hey, it's HighScalability time:

 

Slovenia. A gorgeous place to break your leg. Highly recommended.

Do you like this sort of Stuff? Please lend me your support on Patreon. It would mean a great deal to me. And if you know anyone looking for a simple book that uses lots of pictures and lots of examples to explain the cloud, then please recommend my new book: Explain the Cloud Like I'm 10. They'll love you even more.

Gone Fishin’

Well, not exactly Fishin', but I'll be on a month long vacation starting today. I won't be posting new content, so we'll all have a break. Disappointing, I know. Please use this time for quiet contemplation and other inappropriate activities. Se vidiva kmalu!

 

If you really need a quick fix there's always all the back catalog of Stuff the Internet Says. Odds are there's a lot you didn't read yet.

Stuff The Internet Says On Scalability For April 27th, 2018

Hey, it's HighScalability time:

 

Did ancient Egyptians invent Wi-Fi? @sherifhanna

Do you like this sort of Stuff? Please lend me your support on Patreon. It would mean a great deal to me. And if you know anyone looking for a simple book that uses lots of pictures and lots of examples to explain the cloud, then please recommend my new book: Explain the Cloud Like I'm 10. They'll love you even more.

  • $17,500: price to give up Google search; 51.8,31.2,18.79: % using AWS, Azure, Google for IoT; 400: items per second shipped by peak Amazon; 43%: music revenues came from streaming; 800%: boost in downloads from apps featured by the Apple App Store; 45: average age of startup founder; 

  • Quotable Quotes:
    • Broad Band: By the mid-twentieth century, computing was so much considered a woman’s job that when computing machines came along, evolving alongside and largely independently from their human counterparts, mathematicians would guesstimate their horsepower by invoking “girl-years,” and describe units of machine labor as equivalent to one “kilogirl.”
    • thegayngler: Most engineers would not hire themselves. That has been apparent to me for awhile now. Continue reading

Update: What will programming look like in the future?

 

Update: Ólafur Arnalds built a robotic music system to accompany him on the piano. He calls his system of two semi generative, self playing pianos—STRATUS. You can hear his most recent song re:member. There's more explanation in The Player Pianos pt. II and a short Facebook live session. His software reacts to his playing in real-time. Then he has to react to the robots because he's not sure what they're going to do. He's improvising like a jazz band would do, but it's with robots. It's his own little orchestra. The result is beautiful. The result is also unexpected. Ólafur makes the fascinating point that usually your own improvisation is limited by your own muscle memory. But with the randomness of the robots you are forced to respond in different ways. He says you get a "pure unrestricted creativity." And it's fun he says with a big smile on his face.

 

 

Maybe programming will look something like the above video. Humans and AIs working together to produce software better than either can separately.

The computer as a creative agent, working in tandem with a human partner, to produce software, in a beautiful act of Continue reading

Google: Addressing Cascading Failures

Like the Spanish Inquisition, nobody expects cascading failures. Here's how Google handles them.

This excerpt is a particularly interesting and comprehensive chapter—Chapter 22 - Addressing Cascading Failures—from Google's awesome book on Site Reliability Engineering. Worth reading if it hasn't been on your radar. And it's free!

Written by Mike Ulrich

If at first you don't succeed, back off exponentially."

Dan Sandler, Google Software Engineer

Why do people always forget that you need to add a little jitter?"

Ade Oshineye, Google Developer Advocate

A cascading failure is a failure that grows over time as a result of positive feedback.107 It can occur when a portion of an overall system fails, increasing the probability that other portions of the system fail. For example, a single replica for a service can fail due to overload, increasing load on remaining replicas and increasing their probability of failing, causing a domino effect that takes down all the replicas for a service.

We’ll use the Shakespeare search service discussed in Shakespeare: A Sample Service as an example throughout this chapter. Its production configuration might look something like Figure 22-1.

Example production configuration for the Shakespeare search service.Figure 22-1. Example production configuration for the Shakespeare search service

Causes of Cascading Failures and Designing to Avoid Them

Sponsored Post: Datadog, InMemory.Net, Triplebyte, Etleap, Scalyr, MemSQL

Who's Hiring? 

  • Triplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Make your job search O(1), not O(n). Apply here.

  • Need excellent people? Advertise your job here! 

Fun and Informative Events

  • Advertise your event here!

Cool Products and Services

  • Datadog is a cloud-scale monitoring platform that combines infrastructure metrics, distributed traces, and logs all in one place. With out-of-the-box dashboards and seamless integrations with over 200 technologies, Datadog provides end-to-end visibility into the health and performance of modern applications at scale. Build your own rich dashboards, set alerts to identify anomalies, and collaborate with your team to troubleshoot and fix issues fast. Start a free trial and try it yourself.

  • 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

Strategy: Use TensorFlow.js in the Browser to Reduce Server Costs

 

One of the strategies Jacob Richter describes (How we built a big data platform on AWS for 100 users for under $2 a month) in his relentless drive to lower AWS costs is moving ML from the server to the client.

Moving work to the client is a time honored way of saving on server side costs. Not long ago it might have seemed like moving ML to the browser would be an insane thing to do. What was crazy yesterday often becomes standard practice today, especially when it works, especially when it saves money:

Our post-processing machine learning models are mostly K-means clustering models to identify outliers. As a further step to reduce our costs, we are now running those models on the client side using TensorFlow.js instead of using an autoscaling EC2 container. While this was only a small change using the same code, it resulted in a proportionally massive cost reduction. 

To learn more Alexis Perrier has a good article on Tensorflow with Javascript Brings Deep Learning to the Browser:

Tensorflow.js has four layers: The WebGL API for GPU-supported numerical operations, the web browser for user interactions, and two APIs: Continue reading

Stuff The Internet Says On Scalability For April 20th, 2018

Hey, it's HighScalability time:

 

Freeman Dyson dissects Geoffrey West's book on universal scaling laws, Scale. (Image: Steve Jurvetson)

If you like this sort of Stuff then please support me on Patreon. And I'd appreciate if you would recommend my new book—Explain the Cloud Like I'm 10—to anyone who needs to understand the cloud (who doesn't?). I think they'll learn a lot, even if they're already familiar with the basics. 

  • 5x: BPF over iptables; 51.21%: SSL certificates now issued by Let's Encrypt; 15,000x: acceleration from a genomics co-processor on long read assembly; 100 Million: Amazon Prime members; 20 minutes: time it takes a robot to assemble an Ikea chair; 1.7 Tbps: DDoS Attack; 200 Gb/sec: future network fabric speeds; $7: average YouTube earnings per 1000 views; 800 million: viruses cascading onto every square meter of the planet each day; <10m: error in  Uber's GPS enhancement; $45 million: total value of Bitcoin ransomware extortion; 

  • Quotable Quotes:
    • @sachinrekhi: Excited to read the latest Amazon shareholder letter. Amazing the scale they are operating at: 100M prime members, $20B AWS business, >50% of products sold from third-party sellers...Bezos Continue reading

Google: A Collection of Best Practices for Production Services

This excerpt—Appendix B - A Collection of Best Practices for Production Services—is from Google's awesome book on Site Reliability Engineering. Worth reading if it hasn't been on your radar. And it's free!

 

Fail Sanely

Sanitize and validate configuration inputs, and respond to implausible inputs by both continuing to operate in the previous state and alerting to the receipt of bad input. Bad input often falls into one of these categories:

Incorrect data

Validate both syntax and, if possible, semantics. Watch for empty data and partial or truncated data (e.g., alert if the configuration is N% smaller than the previous version).

Delayed data

This may invalidate current data due to timeouts. Alert well before the data is expected to expire.

Fail in a way that preserves function, possibly at the expense of being overly permissive or overly simplistic. We’ve found that it’s generally safer for systems to continue functioning with their previous configuration and await a human’s approval before using the new, perhaps invalid, data.

Examples

In 2005, Google’s global DNS load- and latency-balancing system received an empty DNS entry file as a result of file permissions. It accepted this empty file and served NXDOMAIN for Continue reading

Stuff The Internet Says On Scalability For April 13th, 2018

Hey, it's HighScalability time:

 

Bathroom tile? Grandma's needlepoint? Nope. It's a diagram of the dark web. Looks surprisingly like a tumor.

If you like this sort of Stuff then please support me on Patreon. And I'd appreciate if you would recommend my new book—Explain the Cloud Like I'm 10—to anyone who needs to understand the cloud (who doesn't?). I think they'll learn a lot, even if they're already familiar with the basics. 

  • $23 billion: Amazon spend on R&D in 2017; $0.04: cost to unhash your email address; $35: build your own LIDAR; 66%: links to popular sites on Twitter come from bots; 60.73%: companies report JavaScript as primary language; 11,000+: object dataset provide real objects with associated depth information; 150 years: age of the idea of privacy; 30%~ AV1's better video compression; 100s of years: rare-earth materials found underneath Japanese waters; 67%: better image compression using Generative Adversarial Networks; 1000 bit/sec: data exfiltrated from air-gapped computers through power lines using conducted emissions; 

  • Quotable Quotes:

Sponsored Post: InMemory.Net, Educative, Triplebyte, Exoscale, Loupe, Etleap, Aerospike, Scalyr, Domino Data Lab, MemSQL

Who's Hiring? 


  • Triplebyte now hires software engineers for top tech companies and hundreds of the most exciting startups like Apple, Dropbox, Mixpanel, and Instacart. They identify your strengths from an online coding quiz and let you skip resume and recruiter screens at multiple companies at once. It's free, confidential, and background-blind. Apply here.

  • Need excellent people? Advertise your job here! 

Fun and Informative Events

  • 5 Signs You’ve Outgrown DynamoDB. Companies often select a database that seems to be the best choice at first glance, as well as the path of least resistance, and then are subsequently surprised by cost overruns and technology limitations that quickly hinder productivity and put the business at risk. This seems to be the case with many enterprises that chose Amazon Web Service’s (AWS) DynamoDB. In this white paper we’ll cover elements of costing as well as the results of benchmark-based testing. Read 5 Signs You’ve Outgrown DynamoDB to determine if your organization has outgrown this technology.

  • Advertise your event here!

Cool Products and Services

  • 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 Continue reading

Give Meaning to 100 billion Events a Day – The Analytics Pipeline at Teads

This is a guest post by Alban Perillat-Merceroz, Software Engineer at Teads.tv.

In this article, we describe how we orchestrate Kafka, Dataflow and BigQuery together to ingest and transform a large stream of events. When adding scale and latency constraints, reconciling and reordering them becomes a challenge, here is how we tackle it.


Teads for Publisher, one of the webapps powered by Analytics

 

In digital advertising, day-to-day operations generate a lot of events we need to track in order to transparently report campaign’s performances. These events come from:

  • Users’ interactions with the ads, sent by the browser. These events are called tracking events and can be standard (start, complete, pause, resume, etc.) or custom events coming from interactive creatives built with Teads Studio. We receive about 10 billion tracking events a day.
  • Events coming from our back-ends, regarding ad auctions’ details for the most part (real-time bidding processes). We generate more than 60 billion of these events daily, before sampling, and should double this number in 2018.

In the article we focus on tracking events as they are on the most critical path of our business.

Simplified overview of our technical context with the two main Continue reading

Stuff The Internet Says On Scalability For April 6th, 2018

Hey, it's HighScalability time:

 

Programmable biology - engineered cells execute programmable multicellular full-adder logics. (Programmable full-adder computations)

If you like this sort of Stuff then please support me on Patreon. And I'd appreciate if you would recommend my new book—Explain the Cloud Like I'm 10—to anyone who needs to understand the cloud (who doesn't?). I think they'll learn a lot, even if they're already familiar with the basics. 

  • $1: AI turning MacBook into a touchscreen; $2000/month: BMW goes subscription; 20MPH: 15′ Tall, 8000 Pound Mech Suit; 1,511,484 terawatt hours: energy use if bitcoin becomes world currency; $1 billion: Fin7 hacking group; 1.5 million: ethereum TPS, sort of; 235x: AWK faster than Hadoop cluster; 37%: websites use a vulnerable Javascript library; $0.01: S3, 1 Gig, 1 AZ; 

  • Quotable Quotes:
    • Huang’s Law~ GPU technology advances 5x per year because the whole stack can be optimized. 
    • caseysoftware: Metcalfe lives here in Austin and is involved in the local startup community in a variety of ways.  One time I asked him how he came up with the law and he said something close Continue reading

Do you have too many microservices? – Five Design Attributes that can Help

This is a guest Post by Jake Lumetta, Founder and CEO, ButterCMS, an API-first CMS. For more content like this, follow @ButterCMS on Twitter and subscribe to our blog.

Are your microservices too small or too tightly coupled? Are you confident in your decision-making about service boundaries? In interviews with dozens of experienced CTOs, they offered design attributes that they consider when creating a set of microservices. This article distills that wisdom into five key principles to help you better design microservices.

The importance of microservice boundaries

The design attributes discussed below matter because reaping the benefits of microservices requires designing thoughtful microservice boundaries.

One of the major challenges when it comes to creating a new system with a microservice architecture. It came about when I mentioned that one of the core benefits of developing new systems with microservices is that the architecture allows developers to build and modify individual components independently — but problems can arise when it comes to minimizing the number of callbacks between each API. The solution according to McFadden, is to apply the appropriate service boundaries.

But in contrast to the sometimes difficult-to-grasp and abstract concept of domain driven design (DDD) —  a framework for Continue reading

How ipdata serves 25M API calls from 10 infinitely scalable global endpoints for $150 a month

This is a guest post by Jonathan Kosgei, founder of ipdata, an IP Geolocation API. 

I woke up on Black Friday last year to a barrage of emails from users reporting 503 errors from the ipdata API.

Our users typically call our API on each page request on their websites to geolocate their users and localize their content. So this particular failure was directly impacting our users’ websites on the biggest sales day of the year. 

I only lost one user that day but I came close to losing many more.

This sequence of events and their inexplicable nature — cpu, mem and i/o were nowhere near capacity. As well as concerns on how well (if at all) we would scale, given our outage, were a big wake up call to rethink our existing infrastructure.

Our Tech stack at the time

Stuff The Internet Says On Scalability For March 30th, 2018

Hey, it's HighScalability time:

 

Objective painting is not good painting unless it is good in the abstract sense. A hill or tree cannot make a good painting just because it is a hill or tree. It is lines and colors put together so that they may say something.” – Georgia O’Keeffe

 

If you like this sort of Stuff then please support me on Patreon. And I'd appreciate if you would recommend my new book—Explain the Cloud Like I'm 10—to anyone who needs to understand the cloud (who doesn't?). I think they'll learn a lot, even if they're already familiar with the basics.

 

  • 6,000: new viri spotted by AI; 300,000: Uber requests per second; 10TB & 600 years: new next-gen optical disk; 32,000: sites running Coinhive’s JavaScript miner code; $1 billion: Uber loss per quarter; 3.5%: global NAND flash output lost to power outage; 100TB: new SSD; 48TB: RAM on one server; 200 million: Telegram monthly active users; 2,000: days Curiosity Rover on Mars; 225: emerging trends; 4,425: SpaceX satellites approved; 

  • Quotable Quotes:
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