c3.large

While the chart above is a good start, there’s more than simply considering “Reserved vs. On Demand”. So let’s take a closer look at all the options…

I have a computation/IO heavy backend service (image processing) that I run on EC2 instance (c3.large). As I need to scale this service I consider allocating tens of c3.large instances or fewer of the larger c3 instances.

You have to do it manually.

The other answers here are correct, but for my use case the easiest thing was to let the instance expire and then "Purchase More Like These".

You don't actually 'renew' a reserved instance - you buy another one.

I have little query related to reserved c3.large going to 1 year and it was reserved for 1 year does it will renew automatically or i need to do it manually.

The`c3.large` is 40% faster and has more than double the memory than the `c1.medium` but costs about the same!

Coming out of Phoronix today for helping you measure cloud performance are benchmarks of all the new C3 instance types and compared to some bare metal systems running locally.

You don't actually 'renew' a reserved instance - you buy another one. Remember a reserved instance is just a billing construct and has nothing to do with any particular instance that may or may not be running. So when the term of the reserved instance runs out, any instances you have simply start getting billed at the on-demand rate, unless and until you purchase another reserved instance.

You have to do it manually.

The other answers here are correct, but for my use case the easiest thing was to let the instance expire and then "Purchase More Like These".

I benchmarked all these new instances: c3.large, c3.xlarge, c3.2xlarge, c3.4xlarge, and c3.8xlarge.

The C3.2xlarge instances have High Network Performance. If you are copying images onto and off these boxes you will see better performance with these.

The on-demand prices are indeed quite linear within each instance family, so if your workload works equally well on multiple classes (i.e., no single task requires a particularly large amount of memory) then there may not be a significant difference... the network I/O capacity also scales up, along with memory and ECU... and the under-appreciated ephemeral storage space, which incurs no I/O-based charges.

The`c3.large` is 40% faster and has more than double the memory than the `c1.medium` but costs about the same!

Coming out of Phoronix today for helping you measure cloud performance are benchmarks of all the new C3 instance types and compared to some bare metal systems running locally.

The on-demand prices are indeed quite linear within each instance family, so if your workload works equally well on multiple classes (i.e., no single task requires a particularly large amount of memory) then there may not be a significant difference... the network I/O capacity also scales up, along with memory and ECU... and the under-appreciated ephemeral storage space, which incurs no I/O-based charges.

However, prices on the spot market are not quite so linear. My internal systems collect spot market pricing history (available in the console and via the API) that identifies the minimum bid that would have historically been necessary to keep a given instance running at a given percentage of uptime in a given availability zone.

I have a computation/IO heavy backend service (image processing) that I run on EC2 instance (c3.large). As I need to scale this service I consider allocating tens of c3.large instances or fewer of the larger c3 instances.

Coming out of Phoronix today for helping you measure cloud performance are benchmarks of all the new C3 instance types and compared to some bare metal systems running locally.

If you want to spend a little more, the current gen c3.large instances look enticing. They offer good computing power, decent memory, and SSD storage!

EC2 instances are priced according to instance type, regardless of the number of CPUs enabled. Disabling vCPUs does not change the cost of the instance type.