On a given volume configuration, certain I/O characteristics drive the performance
behavior for your EBS volumes. SSD-backed volumes—General Purpose SSD (
gp2) and Provisioned IOPS SSD (
consistent performance whether an I/O operation is random or sequential. HDD-backed
volumes—Throughput Optimized HDD (
st1) and Cold HDD (
sc1)—deliver optimal performance only when I/O
operations are large and sequential. To understand how SSD and HDD volumes will perform in
your application, it is important to know the connection between demand on the volume, the
quantity of IOPS available to it, the time it takes for an I/O operation to complete, and the
volume's throughput limits.
IOPS are a unit of measure representing input/output operations per second. The operations are measured in KiB, and the underlying drive technology determines the maximum amount of data that a volume type counts as a single I/O. I/O size is capped at 256 KiB for SSD volumes and 1,024 KiB for HDD volumes because SSD volumes handle small or random I/O much more efficiently than HDD volumes.
When small I/O operations are physically contiguous, Amazon EBS attempts to merge them into a single I/O up to the maximum size. For example, for SSD volumes, a single 1,024 KiB I/O operation would count as 4 operations, while 256 I/O operations at 4 KiB each would count as 256 operations. For HDD-backed volumes, both a single 1,024 KiB I/O operation and 8 sequential 128 KiB operations would count as one operation. However, 8 random 128 KiB I/O operations would count as 8 operations.
Consequently, when you create an SSD-backed volume supporting 3,000 IOPS (either by
io1 volume at 3,000 IOPS or by sizing a
gp2 volume at 1000 GiB), and you
attach it to an EBS-optimized instance that can provide sufficient bandwidth, you can transfer
up to 3,000 I/Os of data per second, with throughput determined by I/O size.
Volume Queue Length and Latency
The volume queue length is the number of pending I/O requests for a device. Latency is the true end-to-end client time of an I/O operation, in other words, the time elapsed between sending an I/O to EBS and receiving an acknowledgement from EBS that the I/O read or write is complete. Queue length must be correctly calibrated with I/O size and latency to avoid creating bottlenecks either on the guest operating system or on the network link to EBS.
Optimal queue length varies for each workload, depending on your particular application's sensitivity to IOPS and latency. If your workload is not delivering enough I/O requests to fully use the performance available to your EBS volume, then your volume might not deliver the IOPS or throughput that you have provisioned.
Transaction-intensive applications are sensitive to increased I/O latency and are
well-suited for SSD-backed
gp2 volumes. You can maintain high IOPS while keeping
latency down by maintaining a low queue length and a high number of IOPS available to the
volume. Consistently driving more IOPS to a volume than it has available can cause increased
Throughput-intensive applications are less sensitive to increased I/O latency, and are
well-suited for HDD-backed
sc1 volumes. You can maintain high throughput to
HDD-backed volumes by maintaining a high queue length when performing large, sequential
I/O size and volume throughput limits
For SSD-backed volumes, if your I/O size is very large, you may experience a smaller
number of IOPS than you provisioned because you are hitting the throughput limit of the
volume. For example, a
gp2 volume under 1000 GiB with burst credits available has an IOPS
limit of 3,000 and a volume throughput limit of 160 MiB/s. If you are using a 256 KiB I/O
size, your volume reaches its throughput limit at 640 IOPS (640 x 256 KiB = 160 MiB). For
smaller I/O sizes (such as 16 KiB), this same volume can sustain 3,000 IOPS because the
throughput is well below 160 MiB/s. (These examples assume that your volume's I/O is not
hitting the throughput limits of the instance.) For more information about the throughput
limits for each EBS volume type, see Amazon EBS Volume Types.
For smaller I/O operations, you may see a higher-than-provisioned IOPS value as measured from inside your instance. This happens when the instance operating system merges small I/O operations into a larger operation before passing them to Amazon EBS.
If your workload uses sequential I/Os on HDD-backed
sc1 volumes, you may
experience a higher than expected number of IOPS as measured from inside your instance. This
happens when the instance operating system merges sequential I/Os and counts them in 1,024
KiB-sized units. If your workload uses small or random I/Os, you may experience a lower
throughput than you expect. This is because we count each random, non-sequential I/O toward
the total IOPS count, which can cause you to hit the volume's IOPS limit sooner than
Whatever your EBS volume type, if you are not experiencing the IOPS or throughput you expect in your configuration, ensure that your EC2 instance bandwidth is not the limiting factor. You should always use a current-generation, EBS-optimized instance (or one that includes 10 Gb/s network connectivity) for optimal performance. For more information, see Amazon EC2 Instance Configuration. Another possible cause for not experiencing the expected IOPS is that you are not driving enough I/O to the EBS volumes.
Monitor I/O Characteristics with CloudWatch
You can monitor these I/O characteristics with each volume's CloudWatch metrics. Important metrics to consider include:
BurstBalance displays the burst bucket balance for HDD-backed volumes as a
percentage. When your burst bucket is depleted, volume throughput is throttled to the
baseline. Check the
BurstBalance value to determine whether your volume is being
throttled for this reason.
sc1 volumes are designed to perform best with workloads that
take advantage of the 1,024 KiB maximum I/O size. To determine your volume's average I/O size,
VolumeWriteOps. The same calculation
applies to read operations. If average I/O size is below 64 KiB, increasing the size of the
I/O operations sent to an
sc1 volume should improve performance.
If average I/O size is at or near 44 KiB, you may be using an instance or kernel without support for indirect descriptors. Any Linux kernel 3.8 and above has this support, as well as any current-generation instance.
If your I/O latency is higher than you require, check
make sure your application is not trying to drive more IOPS than you have provisioned. If your
application requires a greater number of IOPS than your volume can provide, you should
consider using a larger
gp2 volume with a higher base performance level or an
with more provisioned IOPS to achieve faster latencies.
For more information about Amazon EBS I/O characteristics, see the Amazon EBS: Designing for Performance re:Invent presentation on this topic.