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AWS X1 instances – 1.9 TB of memory
- 1024core 10y agoSpot instances are about $13 - $19/hr, depending on zone. Not available in NorCal, Seoul, Sydney and a couple of other places.
- snewman 10y agoDo you mean on-demand instances? The announcement says "Spot bidding is on the near-term roadmap." And $13 / hour is the on-demand price in US East.
- dharma1 10y agoIndeed, doesn't look like it's there yet. Based on that I guess the spot prices will be around $1-3/h - not bad, if you have a workload that can be interrupted.
- krschultz 10y agoA bit under $35,000 for the year.
- zetazzed 10y agoUnder $35k per year AFTER you've paid the $98k up-front cost for a reserved instance. The blog post shows pricing for reserved instances. Hourly price is $13.338 without up-front payment. Expensive, but still nice to have this available as an option for niche scenarios that need all that RAM.
- toomuchtodo 10y agoI'd love to see someone benchmark how fast you can get ~2TB of data into that instance from S3, process it, get the results back into S3, and power down. Big data version of Cannonball Run.
- mentat 10y agoOr you could just use BigQuery =).
- toomuchtodo 10y agoWhat fun would that be :)
- dvirsky 10y agoIIRC that's not a whole lot more than i2.8xl, which has 1/8 of the RAM. But anyway, most likely this will probably be used for on demand "Small Data" type jobs that will benefit from running on a single machine.
- Rezo 10y ago$9.6K/mo without a reservation, but a hefty 70% off with a 3-year reserved instance purchase. It's actually good value, it's 8x the RAM of the nearest memory optimized instance (R3.8XLarge) at just 5x the price. If you have a whole bunch of memory optimized instances, this can allow you to simplify and consolidate and still save you money. Still, don't put all your eggs in one virtual basket.
- helper 10y agoIf you paid hourly (instead of using a reserved instance) it costs $116840.88 per year (13.338 per hour * 24 * 365). A 1 year reservation + hourly charges for a year is $67197.96 (all up front).
- matt4077 10y agoSo this thing is worth about three humans in the western world :( (not that I don't understand that this could be said of many things, might actually be true in economic terms etc. It just never occured to me with other heavy machinery).
- nitrogen 10y agoIt's always fun when making devops forecasts to plot the date when the servers will be paid more than you due to anticipated growth.
- kabdib 10y agoYou can buy a server from Dell with 1.5 TB of RAM and four beefy processors (80 cores) for about $60K. You can power and cool it for a year for maybe $4K. Every time I look at AWS, it just doesn't make sense from a financial standpoint (even after you add another machine for redundancy, and remote hands -- you're ahead after 12 months).
- helper 10y agoI'm sure there are companies that will run this instance type 24/7 for years. But you can also spin one up for a short period of time, use it to do things you would normally need to do across a bunch of machines and then tear it down. Having this type of instance available via an API call is within seconds is really cool.
- snewman 10y agoYes, but only if you pay for three years up front. Spelling out all the options: * $117K / year on-demand * 81K / year for one-year commitment, nothing up front * 69K / year for one-year commitment, $34,285 up front * 67K / year for one-year commitment, $67,199 up front * 35K / year for three-year commitment, $52,166 up front * 33K / year for three-year commitment, $98,072 up front All these prices are total, e.g. for the last option, you pay $98,072 up front and then nothing more, which divides out to about $33K / year over the three years. Plus, eventually, the spot market, and of course you can run save money with on-demand if you only need the instance occasionally.
- hartator 10y agoAWS pricing is a bit ridiculous. $100,000 can buy some much hardware even while taking account of the additional costs like electricity and hardware failures.
- blowski 10y agoAnd the staff costs of good sysadmins, and the reliable network, and everything else that comes with AWS? For some use cases, the pricing of AWS makes sense.
- Chronic51 10y agoFor most personal and business use cases, it does not make sense.
- throwaway2016a 10y agoI tend to agree with you on AWS. I swear by it. But in this case I would probably go at it this way... How many hours can I run the machine before it costs more than building one? Probably a month? (random guess) Will I be running it longer than that? If yes, build the machine, if no, just rent it from AWS. I can't even imagine a scenario where I run this 24 hours a day 365 that I wouldn't build out a Hadoop cluster or similar for.
- bluedino 10y agoAn R930 on Dell's site configures out to double that. And that doesn't include power/bandwidth. I'm sure you would also get a hefty discount if you were a customer who regularly buys servers that cost that much.
- tracker1 10y agoThanks for looking that up... I was going to say, I'd be surprised if these servers weren't costing Amazon over $70K to begin with.
- daigoba66 10y agoThe use cases for this class of machines, I think: spin up, do work for a few minutes/hours/whatever, then spin down. They're far from running 24/7 which _can_ make it more economical than buying dedicated hardware which might sit idle.
- dajonker 10y agoThe cost of those machines are tiny compared to the SAP HANA licenses you'll need for your "Enterprise-Scale SAP Workloads" mentioned in the blog.
- realworldview 10y agoRecompiling tetris with BIGMEM option now...
- dman 10y agoGoing to comment out the deallocation bits in all my code now.
- kylehotchkiss 10y agoAdd some bitcoin mining with the power you still have afterwards
- tracker1 10y agoMemory leaks be damned... Seriously, that is just huge.
- PeCaN 10y agoYou jest, but sometimes that's exactly what you need for short-lived programs¹. Bump alloc and free on exit is super fast if your space complexity is bounded. ¹ http://www.drdobbs.com/cpp/increasing-compiler-speed-by-over-75/240158941 http://www.drdobbs.com/cpp/increasing-compiler-speed-by-over...
- sedachv 10y agoJonL White actually wrote a serious paper about just this idea in 1980: http://dl.acm.org/citation.cfm?id=802797 http://dl.acm.org/citation.cfm?id=802797
- gaul 10y agoFull paper: http://3e8.org/pub/scheme/doc/lisp-pointers/v1i3/p17-white.pdf http://3e8.org/pub/scheme/doc/lisp-pointers/v1i3/p17-white.p...
- vegancap 10y agoFinally, an instance made for Java!
- granos 10y agoI dislike developing in Java. I am not a fanboy by any stretch of the imagination. That being said, someone who takes the time to understand how the JVM works and how to configure their processes with a proper operator's mindset can do amazing things in terms of resource usage. It's easy to poke at Java for being a hog when in reality its just poor coding and operating practices that lead to bloated runtime behavior.
- yongjik 10y ago> ...can do amazing things in terms of resource usage. Sorry, but you just made my day. :P
- placeybordeaux 10y agoFor a long time I wondered if it was a failing of the language or the culture. After spending 4 days trying to diagnose a problem with hbase given the two errors "No region found" and "No table provided" and finally figuring out it was due to a version mismatch I now believe it is the culture. At the very least you should be printing a WARN when you connect to an incompatible version.
- electrum 10y agoBad code is bad code, no matter what language it is written in.
- sk5t 10y agoBad logging is not endemic to the Java development mindset... in fact I'd give Java the nod for the _option_ to generate tremendously large quantities of log data when requested, above almost any other platform, excepting maybe Windows if you figure out how to turn on ETL. If you want bad logging, look at most PHP projects... For really thoughtful logging, the Apache HTTP client and HikariCP are good Java examples.
- MasterScrat 10y agoAs a reference the archive of all Reddit comments from October 2007 to May 2015 is around 1 terabyte uncompressed. You could do exhaustive analysis on that dataset fully in memory.
- jedberg 10y agoYour point is accurate, but I'd like to point out that the dataset isn't actually all the comments on Reddit -- it's inly what they could scrape, which is limited to 1000 comments per account. So basically it's missing a lot of the historical comments of the oldest accounts. I only point this out to try and correct a common error I see. You're absolutely right that it is awesome that the entire data set can be analyzed in RAM!
- samstave 10y agoIt would be interested to see the distribution of 1000 comments from each account over the period of 12 months. Some people go dormant - like vacation, or depression, or lack of interest in topics - then cluster a bunch of comments when, say, they are on a drunken rage binge. What time of day the accounts most frequently comment. (I'd bet there is an interesting grouping of those that post while at work during the day, and those who post from home at night. or what subreddits people comment in most during the day vs which /r/ they post to at night ;)
- MasterScrat 10y agoSome of those have already been done. Sounds like you'd enjoy reading this guy's stuff: https://www.reddit.com/user/minimaxir/submitted/?sort=top https://www.reddit.com/user/minimaxir/submitted/?sort=top
- samstave 10y agoLove it thanks!
- MasterScrat 10y ago
- amazon_not 10y agoThe pricing is surprisingly enough not terrible. Given that dedicated servers cost $1-1.5 per GB of RAM per month the three year price is actually almost reasonable. That being said, a three year commitment is still hard to swallow compared to dedicated servers that are month-to-month.
- bdcravens 10y agoIt's not just the commitment, but the fact you have to cough up $52,000-$98,000 up front.
- ChuckMcM 10y agoThat is pretty remarkable. One of the limitations of doing one's own version of mass analytics is the cost of acquiring, installing, configuring, and then maintaining the hardware. Generally I've found AWS to be more expensive but you get to "turn it on, turn it off" which is not something you can do when you have to pay monthly for data center space. It makes for an interesting exercise to load in your data, do your analytics, and then store out the meta data. I wonder if the oil and gas people are looking at this for pre-processing their seismic data dumps.
- dastbe 10y agoAre you using seismic to describe what the data is, how big the data is, or both?
- ChuckMcM 10y agoHere is a good link: http://www.seismicsurvey.com.au/ http://www.seismicsurvey.com.au/ Basically you take waves that are transiting the area of interest and do transforms on them to ascertain the structure underground. Dave Hitz of NetApp used to joke these guys have great compression algorithm, they can convert a terabyte of data into 1 bit (oil/no-oil). One of the challenges is that the algorithms are running in a volume of space, so 'nearest neigbor' in terms of samples has more than 8 vectors. In the early 2000's they would stream their raw data off tape cartridges into a beowulf type cluster, process it, and then store the post processed (and smaller) data to storage arrays. Then that post processed data would go through its own round of processing. One of their challenges was that they ended up duplicating the data on multiple nodes because they needed it for their algorithm and it was too slow to fetch it across the network. A single system image with a TB of memory would let them go back to some of their old mainframe algorithms which, I'm told, were much easier to maintain.
- samstave 10y agoJust curious - but wouldnt the GPU based instances be more efficient for oil and gas people? Or load a data set in this monster and then use GPU workers to hit it?
- samstave 10y ago~$4/hour??? Thats amazing.
- 0xmohit 10y agoEncouraging folks to write more inefficient code? I'd be interested in hearing what Gates [1] has to say about it, though. [1] "640 kB ought to be enough for anybody"
- bdcravens 10y agoToo bad no one has a real source for that quote, probably because he never actually said it (though like "Beam me up Scotty" which was never quoted in the original Star Trek, he may have come close, but it's not nearly as memetastic)
- pritambarhate 10y agoQuestion for those who have used monster servers before: Can PostgreSQL/MySQL use such type of hardware efficiently and scale up vertically? Also can MemCached/Redis use all this RAM effectively? I am genuinely interested in knowing this. Most of the times I work on small apps and don't have access to anything more than 16GB RAM on regular basis.
- adwf 10y agoI've used Postgres out to the terabyte+ range with no probs, so it all works fine. Of course, whenever you approach huge data sizes like this, it tends to change how you access the data a little. eg. Do more threads equal more user connections, or more parallel computation? Generally though, databases aren't really hindered by CPU, instead by the amount of memory in the machine and this new instance is huge. No idea about MySQL, people tend to scale that out rather than up.
- alfalfasprout 10y agoI don't work on 2TB+ memory servers, but one of my servers is close to 1TB of RAM. PostgreSQL scales nicely here. Main thing you're getting is a huge disk cache. Makes repeated queries nice and fast. Still I/O bound to some extent though. Redis will scale nicely as well. But it won't be I/O bound. Honestly, if you really need 1TB+ it's usually going to be for numerically intensive code. This kind of code is generally written to be highly vectorizable so the hardware prefetcher will usually mask memory access latency and you get massive speedups by having your entire dataset in memory. Algorithms that can memoize heavily also benefit greatly.
- chucky_z 10y agoPostgres scales great up to 256gb, at least with 9.4. After that it'll use it, but there's no real benefit. I don't know about MySQL. SQL Server scales linearly with memory even up to and past the 1TB point. I did encounter some NUMA node spanning speed issues, but numactl tuning fixed that. I setup a handful of pgsql and Windows servers around this size. SQL Server at the time scaled better with memory. Pgsql never really got faster after a certain point, but with a lot of cores it handled tons of connections gracefully.
- samstave 10y ago16GB of ram should be enough for anyone. Edit, y'all don't get the reference: famous computer urban legend... http://www.computerworld.com/article/2534312/operating-systems/the--640k--quote-won-t-go-away----but-did-gates-really-say-it-.html http://www.computerworld.com/article/2534312/operating-syste...
- popey456963 10y agoJust imagining the entirety of Google running on 16GB of RAM :). To answer the question at hand though, MySQL seems great at up scaling with larger hardware, as does Redis (from what I've seen, it seems to almost get more efficient at sizes >500GB). MongoDB (my goto database) occasionally doesn't seem to scale very nicely off the bat, but after some configuration that too scales very well, possibly even better than MySQL.
- Pirate-of-SV 10y agoMongoDB's In-Memory storage engine would be pretty sweet to try out with the X1 instance :)
- 0xffff2 10y agoPretty sure every single person on HN gets the reference; it's just trite and doesn't add anything to the conversation.
- samstave 10y agoLighten up. You know what's funny - is that I have tons of friends in work, on multiple private slack groups and all over, guess what - we all joke. That's what make us friends. I'm not here to prove myself - I participate in the tech community here and it's like everyone like you just tries to put on some superiority complex and act like tech is ONLY serious business. That's bullshit. Get over yourself.
- lotyrin 10y agoI've seen plenty of jokes that were good, relevant, and tasteful upvoted on HN. Do you think it is possible you are mistaken about the quality of yours?
- Erwin 10y agoI'm curious about this AWS feature mentioned: https://aws.amazon.com/blogs/aws/new-auto-recovery-for-amazon-ec2/ https://aws.amazon.com/blogs/aws/new-auto-recovery-for-amazo... We've experiemnted with something similar on Google Cloud, where an instance that is considered dead has its IP address and persistent disks taken away, then attached to another (live or just created instance). It's hard to say whether this can recover from all failures however without having experienced them or even work better than what Google claims it already does (moving around failing servers from hardware to hardware). Anyone with practical experience in this type of recovery where you don't duplicate your resource requirements?
- 0xmohit 10y agoWow! http://codegolf.stackexchange.com/a/22939 http://codegolf.stackexchange.com/a/22939 would now be available in production.
- lovelearning 10y agoThis is probably a dumb question, but what does the hardware of such a massive machine look like? Is it just a single server box with a single motherboard? Are there server motherboards out there that support 2 TB of RAM, or is this some kind of distributed RAM?
- schlarpc 10y agoDon't know what hardware AWS is using, but Ark has server boards supporting 1.5TB, which is close enough to make 2TB believable: http://ark.intel.com/products/94187/Intel-Server-Board-S2600WTTS1R http://ark.intel.com/products/94187/Intel-Server-Board-S2600... Edit: Supermicro has several 2TB boards, and even some 3TB ones: http://www.supermicro.com/products/motherboard/Xeon1333/#2011 http://www.supermicro.com/products/motherboard/Xeon1333/#201... (Disclaimer: AWS employee, no relation to EC2)
- yuhong 10y agoThis would require expensive 64GB DDR4 LR-DIMMs though.
- KSS42 10y agoMy guess is that it is not really DRAM but flash memory on a DIMM like this product form Diablo Technology: http://www.diablo-technologies.com/memory1/ http://www.diablo-technologies.com/memory1/
- zymhan 10y ago
- micro-ram 10y agoWhat happened to the other 16 threads? 18(core) * 4(cpus) * 2(+ht) = 144
- jedbrown 10y agoDoes anyone have numbers on memory bandwidth and latency? The x1 cost per GB is about 2/3 that of r3 instances, but you get 4x as many memory channels if spec the same amount of memory via r3 instances so the cost per memory channel is more than twice as high for x1 as r3. DRAM is valuable precisely because of its speed, but the speed itself is not cost-effective with the x1. As such, the x1 is really for the applications that can't scale with distributed memory. (Nothing new here, but this point is often overlooked.) Similarly, you get a lot more SSDs with several r3 instances, so the aggregate disk bandwidth is also more cost-effective with r3.
- sun_n_surf 10y agoNot sure I quite understand your math here. The largest R3 instance is the r3.8xlarge with 244 GB of memory. 4 times of that would only get you to 1 TB. Also, this: "DRAM is valuable precisely because of its speed", is wrong (https://en.wikipedia.org/wiki/Dynamic_random-access_memory https://en.wikipedia.org/wiki/Dynamic_random-access_memory).
- jedbrown 10y ago1. 4 of those R3 instances cost less than the X1 but offer nearly double the bandwidth. The X1 is cheaper per GB, but much more expensive per GB/s. 2. If DRAM was not faster than NVRAM/SSD, nobody would use it. "Speed" involves both bandwidth and latency. Latency is probably similar or higher for the X1 instances, but I haven't seen numbers. We can make better estimates about realizable bandwidth based on the system stats.
- ben_jones 10y agoI'd be guilty if I ever used something like this and under utilized the ram. "Ben we're not utilizing all the ram." "Add another for loop."
- mrmondo 10y agoI'm taking it this is so people can run NodeJS or MSSQL on AWS now? Heh, sorry for the jab - what could this be used for considering that AWS' top tier provisioned storage IOP/s are still so low (and expensive)? Something volatile running una RAM disk maybe?
- jayhuang 10y agoFunny how the title made me instantly think: SAP HANA. After not seeing it for the first 5 paragraphs or so, Ctrl+F, ah yes. Not too surprising given how close SAP and Amazon AWS have been ever since SAP started offering cloud solutions. Going back a couple years when SAP HANA was still in its infancy; trying it on servers with 20~100+ TB of memory, this seems like an obvious progression. Of course there's always the barrier of AWS pricing.
- manav 10y agoHmm around $4/hr after a partial upfront. I'm guessing that upfront is going to be just about the cost of a server which is around $50k.
- zbjornson 10y agoHow does this thing still only have 10 GigE (plus 10 dedicated to EBS)? It should have multiple 10 Gig NICs that could get it to way more than that.