EC2 is generally very expensive for CPU. RAM and storage are okay but CPU is crazy.
I'm leaning towards becoming an EC2 apologist on here, but just running quick benchmarks on a t2.micro versus both the $5 and $10 Droplets.
sysbench --test=cpu --cpu-max-prime=40000 run
$5 Droplet ("2.0Ghz", bogomips 4000)- 99.4981s
$10 Droplet ("2.4Ghz", bogomips 4800) - 88.3740s
(I can't find any actual documentation detailing the $10 option being faster, so perhaps this is just random luck on instantiation)
t2.micro ("2.5Ghz", bogomips 5000) - 69.5248s
Now of course the t2.micro won't let you run that around the clock, which for many workloads is entirely fine: as a standard blog host and the like, or the overwhelming majority of server implementations, bursty CPU is exactly what most natural workloads look like.
Of particular relevance is that the Amazon instance (E5-2670) exposes SSE4 and AVX to your VM, which for many workloads could dramatically increase its advantage.
I guess the whole point of this is that the vague CPU terminology that the various cloud vendors use is seldom really comparable. However to your core question, Amazon becomes a value proposition when you are using all of the parts -- S3, load balances, elastic IPs, shared volumes, availability zones, security zones, VPCs, private networks...it is all multipliers to the value of the platform.
As a quick addition on this, the m3.medium -- running on the same processor but governed differently -- takes 160 seconds to run the same benchmark (after repeated runs).
Amazon used to promote their instances via the somewhat comparable ECU metrics. Now, however, unless I'm missing something, you need to try to determine by narrative, because 1 vCPU is very much not equal to 1 vCPU on other instance types.
They still use ECU, but I'm not sure it's comparable across generations of instances, e.g. an m3 with more ECU than an older m1 instance of similar size seems at times to be slower.
I'm leaning towards becoming an EC2 apologist on here, but just running quick benchmarks on a t2.micro versus both the $5 and $10 Droplets.
sysbench --test=cpu --cpu-max-prime=40000 run
$5 Droplet ("2.0Ghz", bogomips 4000)- 99.4981s
$10 Droplet ("2.4Ghz", bogomips 4800) - 88.3740s
(I can't find any actual documentation detailing the $10 option being faster, so perhaps this is just random luck on instantiation)
t2.micro ("2.5Ghz", bogomips 5000) - 69.5248s
Now of course the t2.micro won't let you run that around the clock, which for many workloads is entirely fine: as a standard blog host and the like, or the overwhelming majority of server implementations, bursty CPU is exactly what most natural workloads look like.
Add comparisons of the CPUINFO for each-
Both droplets (identical cpuinfo flags) -
flags : fpu de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pse36 clflush mmx fxsr sse sse2 syscall nx lm rep_good nopl pni vmx cx16 popcnt hypervisor lahf_lm
Amazon t2.micro-
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx rdtscp lm constant_tsc rep_good nopl xtopology eagerfpu pni pclmulqdq ssse3 cx16 pcid sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm xsaveopt fsgsbase smep erms
Of particular relevance is that the Amazon instance (E5-2670) exposes SSE4 and AVX to your VM, which for many workloads could dramatically increase its advantage.
I guess the whole point of this is that the vague CPU terminology that the various cloud vendors use is seldom really comparable. However to your core question, Amazon becomes a value proposition when you are using all of the parts -- S3, load balances, elastic IPs, shared volumes, availability zones, security zones, VPCs, private networks...it is all multipliers to the value of the platform.