Announcing Beta For Local SSD
Posted:
Wednesday, October 29, 2014
At Google I/O in June, we announced a trusted tester program for the local SSD product for Google Compute Engine. Today, we’re taking the next step and bringing local SSD to open beta. Now all Compute Engine customers will have a cost effective way to serve massive amounts of IO, making the platform an ideal place to run:
The local SSD feature lets customers attach from 1 to 4 x 375 GB SSD partitions to any full core VM and have dedicated use of those partitions. It provides higher IO than Persistent Disk but does not have any redundancy. This is ideal for highly demanding applications that provide their own replication such as many modern databases and Hadoop, as well as for scratch space for intense computational applications.
The local SSD feature has five key characteristics:
High performance and low latency
Performance scales linearly from 1 to 4 partitions. The full 4 partitions can execute up to 680,000 random 4K read IOPS and 360,000 random 4K write IOPS. This is 8x more write IOPS/GB and 15x more read IOPS/GB than SSD Persistent Disk.
Competitive pricing
At $0.218/GB/month, local SSD is very competitively priced. For those used to buying local SSD attached to VMs, this comes to $0.0003/GB/hour.
No planned downtime
Local SSD data will not be lost when Google does datacenter maintenance, even without replication or redundancy. We will use our live migration technology to move your VMs along with their local SSD to a new machine in advance of any planned maintenance, so your applications are not disrupted and your data is not lost.
Configuration flexibility
There are no special instance types needed to use local SSD. You can attach 1 to 4 local SSD partitions to any full core VM. You can scale up and down CPU/memory and CPU as you need and are not locked into predefined ratios.
Encryption
Local SSD is always encrypted for your protection.
There is product documentation available so you can learn more about local SSD. We love hearing from you, so let us know how things are working either through our technical support, the Google Compute Engine Discussion mailing list or the Google Compute Engine Stack Overflow forum. Happy computing!
-Posted by Jay Judkowitz, Senior Product Manager
- Large databases backing internet-scale applications
- Intensive data processing applications
The local SSD feature lets customers attach from 1 to 4 x 375 GB SSD partitions to any full core VM and have dedicated use of those partitions. It provides higher IO than Persistent Disk but does not have any redundancy. This is ideal for highly demanding applications that provide their own replication such as many modern databases and Hadoop, as well as for scratch space for intense computational applications.
The local SSD feature has five key characteristics:
High performance and low latency
Performance scales linearly from 1 to 4 partitions. The full 4 partitions can execute up to 680,000 random 4K read IOPS and 360,000 random 4K write IOPS. This is 8x more write IOPS/GB and 15x more read IOPS/GB than SSD Persistent Disk.
Competitive pricing
At $0.218/GB/month, local SSD is very competitively priced. For those used to buying local SSD attached to VMs, this comes to $0.0003/GB/hour.
No planned downtime
Local SSD data will not be lost when Google does datacenter maintenance, even without replication or redundancy. We will use our live migration technology to move your VMs along with their local SSD to a new machine in advance of any planned maintenance, so your applications are not disrupted and your data is not lost.
Configuration flexibility
There are no special instance types needed to use local SSD. You can attach 1 to 4 local SSD partitions to any full core VM. You can scale up and down CPU/memory and CPU as you need and are not locked into predefined ratios.
Encryption
Local SSD is always encrypted for your protection.
There is product documentation available so you can learn more about local SSD. We love hearing from you, so let us know how things are working either through our technical support, the Google Compute Engine Discussion mailing list or the Google Compute Engine Stack Overflow forum. Happy computing!
-Posted by Jay Judkowitz, Senior Product Manager