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We would need something like an X1 instance in terms of RAM, but it's hard to find something on AWS that has a well-tuned balance of RAM/CPU/disk for our needs.

We would need something like an X1 instance in terms of RAM, but it's hard to find something on AWS that has a well-tuned balance of RAM/CPU/disk for our needs. A lot of the big specialized instances are tuned for one particular limiting factor (RAM/GPU/storage/CPU/bandwidth/whatever) and I don't recall them having a good selection for "really big everything". Amazon is constantly expanding the selection, so it's possible they've added something since we last seriously looked into this.

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varenc 6y ago
Just curious, can you share general details on the types of services that need really big everything? For most every workload I can think of, as their load increases it's always one resource in particular that's the limiting factor. (RAM/CPU/Storage/etc). So it makes sense to me that AWS instances focus on optimizing one particular resource type. Would be interesting to hear about types of workloads that break this pattern. (Or maybe it's a few different types of workloads/services that need to be tightly integrated on one machine?)
- twoodfin 6y ago
  Redlining RAM + CPU is not difficult for the right kind of database application that needs in-memory latency. RAM is a limit on your (hot, at least) data size, and CPU is a limit on your query workload. In my experience, harder to also balance I/O so you’re close to hitting three limits, but update-heavy transactional workloads can manage it for disk-based DBMS’s.
- graycat 6y ago
  > For most every workload I can think of, as their load increases it's always one resource in particular that's the limiting factor. So this is a rediscovery, at least an example, of what could be called the bottleneck principle of system performance analysis and optimization! Sooo, just look for the bottleneck(s), work on those, and f'get about everything else until, say, everything is equally a bottleneck at which time have a well balanced, call it optimized, which can be appropriate, configuration! At times, e.g., at IBM's Watson lab, there has been a lot of work on applying queueing theory, analysis, and simulation to analyzing and then optimizing such systems, but, more closely to fully true than one might guess, all that really mattered were the bottlenecks(s)!
hey_ross 6y ago
We just launched (Oracle Cloud) an AMD Epyc 2 Compute service (called E3 on our compute page) that is the beginning of 'shapeless' or flexible computing - you can spec the cores for your shape from 1-64 and drive the balance on storage and memory. That might be a fit for you, as it's really inexpensive or the power.

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varenc 6y ago

Just curious, can you share general details on the types of services that need really big everything? For most every workload I can think of, as their load increases it's always one resource in particular that's the limiting factor. (RAM/CPU/Storage/etc). So it makes sense to me that AWS instances focus on optimizing one particular resource type. Would be interesting to hear about types of workloads that break this pattern. (Or maybe it's a few different types of workloads/services that need to be tightly integrated on one machine?)

twoodfin 6y ago
Redlining RAM + CPU is not difficult for the right kind of database application that needs in-memory latency. RAM is a limit on your (hot, at least) data size, and CPU is a limit on your query workload. In my experience, harder to also balance I/O so you’re close to hitting three limits, but update-heavy transactional workloads can manage it for disk-based DBMS’s.
graycat 6y ago
> For most every workload I can think of, as their load increases it's always one resource in particular that's the limiting factor. So this is a rediscovery, at least an example, of what could be called the bottleneck principle of system performance analysis and optimization! Sooo, just look for the bottleneck(s), work on those, and f'get about everything else until, say, everything is equally a bottleneck at which time have a well balanced, call it optimized, which can be appropriate, configuration! At times, e.g., at IBM's Watson lab, there has been a lot of work on applying queueing theory, analysis, and simulation to analyzing and then optimizing such systems, but, more closely to fully true than one might guess, all that really mattered were the bottlenecks(s)!

hey_ross 6y ago

We just launched (Oracle Cloud) an AMD Epyc 2 Compute service (called E3 on our compute page) that is the beginning of 'shapeless' or flexible computing - you can spec the cores for your shape from 1-64 and drive the balance on storage and memory. That might be a fit for you, as it's really inexpensive or the power.