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Hey, it's HighScalability time:
- 1 trillion: number of scents your nose can smell; millions of square feet: sprawling new server farms
- Quotable Quotes:
- Gideon Lewis-Kraus: As the engineer and writer Alex Payne put it, these startups represent “the field offices of a large distributed workforce assembled by venture capitalists and their associate institutions,” doing low-overhead, low-risk R&D for five corporate giants. In such a system, the real disillusionment isn’t the discovery that you’re unlikely to become a billionaire; it’s the realization that your feeling of autonomy is a fantasy, and that the vast majority of you have been set up to fail by design.
- @aphyr: I was already sold on immutability, pure functions, combinators, etc. What forced me out of Haskell was the impenetrable, haphazard docs.
- @monicalent: Going to be migrating away from Rackspace to save some cash. Recommendations? Both Digital Ocean and Linode are half the price for 1GB RAM.
- Linus Torvalds: So while I'd love for 'make' to be super-efficient, at the same time I'd much rather optimize the kernel to do what make needs really well, and have CPU's that don't take too long either.
- Joe Landman: when the networking revolution comes, the cheap switches will be the first ones against the wall
- @etherealmind: Buying public cloud can say I can't afford a house so I'll buy a tent. Because that works just as well, right ?
- Neil DeGrasse Tyson: The act of doing it perfectly is the measure of it going unnoticed.[....] when it's done perfectly it goes unnoticed or, at best, it's just taken for granted.
- How we scaled Freshdesk (Part I) – Before Sharding. Requests per week boomed from 2 million to 65 million. They scaled vertically for as long as they could to handle the increased load. Increasing RAM, CPU and I/O. First using read slaves for their heavily read weighted traffic, then assigning queries to particular slaves. Writes still needed to scale, so they turned on MySQL partitioning. Then caching of objects and html partials. They also used different storage engines for different functions. RedShift for analytics and data mining. Redis for state and as a job queue. But in the end they had to embrace the shard.
- This took some guts. Fouresquare uses data driven decision making to decide to deportalze their app: We looked at the session analysis and saw that only 1 in 20 sessions had both social and discovery. Why not actually just split those apart, because 19 out of 20 times, tapping on one icon or the other, you have satisfied your need completely.
- The blockchain story is bullshit: Looking at the blockchain from a realist’s standpoint, it is not obvious that there is a need for a worse-performing database, that an unregulated oligarchy has disproportionate power over, that isn’t improved with administrator arbitration. It looks like a technology looking for a problem to solve, rather than a technology created to solve a problem.
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