What gives best performance for running PostgreSQL on EC2? EBS in RAID? PGData on /mnt?
Do you have any preferences or experiences? Main "plus" for running PostgreSQL on EBS is switching from one to another instance. Can this be the reason to be slower than using the /mnt partition?
PS: I'm running PostgreSQL 8.4 with datas/size about 50G, Amazon EC2 xlarge(64) instance.
Here there is some linked info. The main take-away is this post from Bryan Murphy:
Been running a very busy 170+ gb OLTP postgres database on Amazon for
1.5 years now. I can't say I'm "happy" but I've made it work and still prefer it to running downtown to a colo at 3am when something
goes wrong.
There are two main things to be wary of:
1) Physical I/O is not very good, thus how that first system used a RAID0.
Let's be clear here, physical I/O is at times terrible. :)
If you have a larger database, the EBS volumes are going to become a
real bottleneck. Our primary database needs 8 EBS volumes in a RAID
drive and we use slony to offload requests to two slave machines and
it still can't really keep up.
There's no way we could run this database on a single EBS volume.
I also recommend you use RAID10, not RAID0. EBS volumes fail. More
frequently, single volumes will experience very long periods of poor
performance. The more drives you have in your raid, the more you'll
smooth things out. However, there have been occasions where we've had
to swap out a poor performing volume for a new one and rebuild the
RAID to get things back up to speed. You can't do that with a RAID0
array.
2) Reliability of EBS is terrible by database standards; I commented on this
a bit already at
http://archives.postgresql.org/pgsql-general/2009-06/msg00762.php The end
result is that you must be careful about how you back your data up, with a
continuous streaming backup via WAL shipping being the recommended approach.
I wouldn't deploy into this environment in a situation where losing a
minute or two of transactions in the case of a EC2/EBS failure would be
unacceptable, because that's something that's a bit more likely to hapen
here than on most database hardware.
Agreed. We have three WAL-shipped spares. One streams our WAL files
to a single EBS volume which we use for worst case scenario snapshot
backups. The other two are exact replicas of our primary database
(one in the west coast data center, and the other in an east coast
data center) which we have for failover.
If we ever have to worst-case-scenario restore from one of our EBS
snapshots, we're down for six hours because we'll have to stream the
data from our EBS snapshot back over to an EBS raid array. 170gb at
20mb/sec (if you're lucky) takes a LONG time. It takes 30 to 60
minutes for one of those snapshots to become "usable" once we create a
drive from it, and then we still have to bring up the database and
wait an agonizingly long time for hot data to stream back into memory.
We had to fail over to one of our spares twice in the last 1.5 years.
Not fun. Both times were due to instance failure.
It's possible to run a larger database on EC2, but it takes a lot of
work, careful planning and a thick skin.
Bryan
Related
In AWS, can I get disk (volume) images sent to me on DVD?
This would be in preparation to save costs by eliminating the instances and volumes. It took a year to get everything created, the right instances and structure hierarchy. And experimentation to select the right combinations of instances and volume types.
My company wants to save the monthly costs (for a year or so) but also wants the option and ability to restart everything when they want.
Is it possible to be able to save the whole set-up, remove all the instances and volumes (to eliminate costs), and re-institute it back when needed?
Depending on your instance operating system (RedHat, Windows, etc.) you might not be able to get images of the EC2 instance in any form other than AMIs or snaphots stored at Amazon. The reason is Amazon's license does not permit this.
I have not heard of AWS offering a service to back up your data to DVDs. If your goal is to save money, think of the cost per hour that AWS would charge you to manually create DVDs. The DVD write process is slow ....
Instead approach the situation of either creating Amazon Machine Images (AMIs) of your instances or creating snapshots of your instances. You would need to pay the cost of data storage which is about $.05 per GB. 100 GB of data would cost $60.00 per year. 100 GB on DVDs that AWS generated would be significantly higher if offered.
You only can export an image if you import in the first place (https://docs.aws.amazon.com/vm-import/latest/userguide/vmexport.html)
I recommend just creating snapshots, it won't bring the cost to zero but it's cheaper than having stopped instances with unused volumes. If volumes are General Purpose SSD (gp2), snapshots will be half of the price ($0.05 per GB-month)
I definitely don't recommend storing data on DVDs, take advantage of the cloud and the resilience it provides. I'm sure these DVDs won't work when you try to use them after a year if you can even find them, that will cost more than staying on the cloud. :)
At the end of last month, I started experimenting with Amazon EC2. I launched one or two t2 micro instances, to experiment for free under the free tier.
However, I have quickly noticed on my billing dashboard that my services usage was increasing fast, and after a few dayswas forecast to exceed the free tier limitations by the end of the month. Since I don't need to maintain an 24/7 online presence at the moment and mostly use my instances to experiment, I have terminated one and stopped another. I have even detached the volume of the stopped instance.
All I have left are:
One stopped micro instance
One detached volume
Two snapshots of that volume
One AMI that I had used to move my instance from one region to another in the beginning
As far as I understand it, those more or less "idle" resources, at least not highly active ones. And yet, in my billing dashboard, in the row EC2 - Linux, the month-to-date usage keeps increasing, at the rate of more than one hour of usage per real-time hour.
Before I detached the volume, the usage would increase by 14 hours in only 3 hours. Now that I have detached it, it slowed down a bit, but still increased by 16 hours in the last 13 hours. All that, again, without actively running anything!
I am aware that the tally of the usage isn't strictly limited to running instances, but to associated resources as well. But still, it seems very high to me. I don't even dare to test my app anymore.
I would like to know if such an increase is normal, or if there may be something wrong with my account and how I configured my instances. If it is normal, any indications as to what actions I could take to reduce this increase would be very welcome!
Note that I did contact the Amazon support several days ago and didn't get a single reply, this is why I'm turning to here.
Thanks in advance!
Edit: Solved. I did have an instance running in another region, probably by mistake because I had never interacted directly with that region. See comments for a script to systematically check all regions and avoid this kind of stupid mistake.
As I understand it, RDS Provisioned IOPS is quite expensive compared to standard I/O rate.
In Tokyo region, P-IOPS rate is 0.15$/GB, 0.12$/IOP for standard deployment. (Double the price for Multi-AZ deployment...)
For P-IOPS, the minimum required storage is 100GB, IOP is 1000.
Therefore, starting cost for P-IOPS is 135$ excluding instance pricing.
For my case, using P-IOPS costs about 100X more than using standard I/O rate.
This may be a very subjective question, but please give some opinion.
In the most optimized database for RDS P-IOPS, would the performance be worth the price?
or
The AWS site gives some insights on how P-IOPS can benefit the performance. Is there any actual benchmark?
SELF ANSWER
In addition to the answer that zeroSkillz wrote, I did some more research. However, please note that I am not an expert on reading database benchmarks. Also, the benchmark and the answer was based on EBS.
According to an article written by "Rodrigo Campos", the performance does actually improve significantly.
From 1000 IOPS to 2000 IOPS, the read/write(including random read/write) performance doubles. From what zeroSkillz said, the standard EBS block provices about 100 IOPS. Imagine the improvement on performance when 100 IOPS goes up to 1000 IOPS(which is the minimum IOPS for P-IOPS deployment).
Conclusion
According to the benchmark, the performance/price seems reasonable. For performance critical situations, I guess some people or companies should choose P-IOPS even when they are charged 100X more.
However, if I were a financial consultant in a small or medium business, I would just scale-up(as in CPU, memory) on my RDS instances gradually until the performance/price matches P-IOPS.
Ok. This is a bad question because it doesn't mention the size of the allocated storage or any other details of the setup. We use RDS and it has its pluses and minuses. First- you can't use an ephemeral storage device with RDS. You cant even access the storage device directly when using the RDS service.
That being said - the storage medium for RDS is presumed to be based on a variant of EBS from amazon. Performance for standard IOPS depends on the size of the volume and there are many sources stating that above 100GB storage they start to "stripe" EBS volumes. This provides better average case data access both on read and write.
We run currently about 300GB of storage allocation and can get 2k write IOP and 1k IOP about 85% of the time over a several hour time period. We use datadog to log this so we can actually see. We've seen bursts of up to 4k write IOPs, but nothing sustained like that.
The main symptom we see from an application side is lock contention if the IOPS for writing is not enough. The number and frequency you get of these in your application logs will give you symptoms for exhausting the IOPS of standard RDS. You can also use a service like datadog to monitor the IOPS.
The problem with provisioned IOPS is they assume steady state volumes of writes / reads in order to be cost effective. This is almost never a realistic use case and is the reason Amazon started cloud services to fix. The only assurance you get with P-IOPS is that you'll get a max throughput capability reserved. If don't use it, you pay for it still.
If you're ok with running replicas, we recommend running a read-only replica as a NON-RDS instance, and putting it on a regular EC2 instance. You can get better read-IOPS at a much cheaper price by managing the replica yourself. We even setup replicas outside AWS using stunnel and put SSD drives as the primary block device and we get ridiculous read speeds for our reporting systems - literally 100 times faster than we get from RDS.
I hope this helps give some real world details. In short, in my opinion - unless you must ensure a certain level of throughput capability (or your application will fail) on a constant basis (or at any given point) there are better alternatives to provisioned-IOPS including read-write splitting with read-replicas memcache etc.
So, I just got off of a call with an Amazon System Engineer, and he had some interesting insights related to this question. (ie. this is 2nd hand knowledge.)
standard EBS blocks can handle bursty traffic well, but eventually it will taper off to about 100 iops. There were several alternatives that this engineer suggested.
some customers use multiple small EBS blocks and stripe them. This will improve IOPS, and be the most cost effective. You don't need to worry about mirroring because EBS is mirrored behind the scenes.
some customers use the ephemeral storage on the EC2 instance. (or RDS instance) and have multiple slaves to "ensure" durabilty. The ephemeral storage is local storage and much faster than EBS. You can even use SSD provisioned EC2 instances.
some customers will configure the master to use provisioned IOPS, or SSD ephemeral storage, then use standard EBS storage for the slave(s). Expected performance is good, but failover performance is degraded (but still available)
anyway, If you decide to use any of these strategies, I would recheck with amazon to make sure I haven't forgotten any important steps. As I said before, this is 2nd hand knowledge.
I'm considering using EBS for a very large collection of maildirs. Lots of little files spread over lots of directories. Would sharding my EBS storage into multiple smaller containers yield performance gains in reading/writing versus one large EBS volume?
Maybe you can explain what exactly you mean by sharding. Otherwise, as performance of EBS is concerned, there are a few drawbacks:
It's network-bound (e.g. on a smaller instance, where more instances share one host, network performance is sub-stellar).
It's multi-tenant (again, multiple people on the host affect EBS)
Its performance varies (performance is never stable)
It's not SAN!
To mitigate some of these issues, a lot of people suggest to create a raid from multiple EBS volumes, I suggest the following articles:
http://www.mysqlperformanceblog.com/2009/08/06/ec2ebs-single-and-raid-volumes-io-bencmark/
http://orion.heroku.com/past/2009/7/29/io_performance_on_ebs/
Bottomline, for a maildir, I'd probably look into real hardware. It doesn't sound like that you need to scale up/down from one minute to another. I'd probably get a setup in place and if necessary use a cloud-solution in addition to temporarily handle spikes (before you get more hardware in place).
Let me know if this helps!
I understand that when upgrading to a Multi-AZ rds from a Single-AZ, there occurs a "breef i/o freeze". What exactly does that mean?
When an upgrade is made to a Multi-AZ deployment, say from small to large, will the production database be impacted at all? Will it be able to use the backup databse, then failover?
Answers to your questions are written down :
When you choose to move from Single AZ to Multi AZ, brief I/O freeze happens. It means that for some duration database won't be accessible. No read,write operations will be performed on the database. Mostly, the duration for this is around 3-4 minutes.
Yeah, production database will be affected when you resize the compute(from small to large). The best idea to perform resize operation is during scheduled maintenance window. If select Apply Immediately option, for sometime the database won't be accessible(time to switch control to backup server).
Regards,
Sanket Dangi
the downtime when converting from single-AZ to multi-AZ is essentially the time it takes for a new instance to launch and become fully functional as sanket said, it may take a few mins.
scaling up a multi-AZ deployment first scales up the slave instance, then performs a failover. the downtime is the time it takes to do the actual failover - usually closer to a minute.
scaling out a multi-AZ deployment is done by adding additional read-replicas (sourced off of the standby) which incurs no interruption. keep in mind that adding read-replicas creates an eventually consistent system which may or may not be desirable.
it's also worth nothing that you should use the same instance types across all multi-AZ instances, otherwise the imbalance may incur replica lag.
as you're probably realizing, it's best to start with a multi-AZ configuration from the beginning. it makes scaling up and scaling out a lot easier and with less downtime.
Is question 1 still valid? According to AWS documentation (2022) there is no downtime, but there is a small decrease in performance.
Quoting AWS documentation:
When converting a DB instance from Single-AZ to Multi-AZ, Amazon RDS
creates a snapshot of the database volumes and restores these to new
volumes in a different Availability Zone. Although the newly restored
volumes are available almost immediately, they don’t reach their
specified performance until the underlying storage blocks are copied
from the snapshot.
Therefore, during the conversion from Single-AZ to Multi-AZ, you can
experience elevated latency and performance impacts. This impact is a
function of volume type, your workload, instance, and volume size, and
can be significant and may impact large write-intensive DB instances
during peak hour of operations.