I'm missing metrics like [Billed] Volume Read IOPS (Count), [Billed] Volume Read IOPS (Count) in CloudWatch.
Although these metrics are visible in RDS -> CloudWatch.
RDS CloudWatch metrics
Is it possible the find these metrics in CloudWatch so I can create alarm for them?
Update:
it turns out that these metrics are available as:
VolumeBytesUsed -> [Billed] Volume bytes used
VolumeReadIOPs -> [Billed] Volume read IOPs
VolumeWriteIOPs -> [Billed] Volume write IOPs
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Monitoring.Metrics.RDSAvailability.html
These metrics are available as VolumeBytesUsed, VolumeReadIOPs, VolumeWriteIOPs (note the "Volume" prefix).
I will take the opportunity to point out that "IOPS" is a misnomer for these metrics; they are really "IOP5M" or "IOs per 5 minutes." (Thanks, AWS.)
Therefore there is a ~300x difference between ReadIOPs and VolumeReadIOPs.
There is not a linear relationship between WriteIOPs and VolumeWriteIOPs because the latter is boxcared into 8KB(?) chunks and the former is not.
Very confusing, but I hope that helps.
Related
when use scylla_setup, iotune study my reuslt is:
Measuring sequential write bandwidth: 473 MB/s
Measuring sequential read bandwidth: 499 MB/s
Measuring random write IOPS: 1902 IOPS
Measuring random read IOPS: 1999 IOPS
iops is 1900-2000,
when use fio,
fio --randrepeat=1 --ioengine=libaio --direct=1 --gtod_reduce=1 --name=test --filename=/dev/sdc1 --bs=4k --iodepth=64 --size=4G --readwrite=randrw --rwmixread=75
the result is
test: (groupid=0, jobs=1): err= 0: pid=11697: Wed Jun 26 08:58:13 2019
read: IOPS=47.6k, BW=186MiB/s (195MB/s)(3070MiB/16521msec)
bw ( KiB/s): min=187240, max=192136, per=100.00%, avg=190278.42, stdev=985.15, samples=33
iops : min=46810, max=48034, avg=47569.61, stdev=246.38, samples=33
write: IOPS=15.9k, BW=62.1MiB/s (65.1MB/s)(1026MiB/16521msec)
bw ( KiB/s): min=62656, max=65072, per=100.00%, avg=63591.52, stdev=590.96, samples=33
iops : min=15664, max=16268, avg=15897.88, stdev=147.74, samples=33
cpu : usr=4.82%, sys=12.81%, ctx=164053, majf=0, minf=23
IO depths : 1=0.1%, 2=0.1%, 4=0.1%, 8=0.1%, 16=0.1%, 32=0.1%, >=64=100.0%
submit : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0%
complete : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.1%, >=64=0.0%
issued rwt: total=785920,262656,0, short=0,0,0, dropped=0,0,0
latency : target=0, window=0, percentile=100.00%, depth=64
Run status group 0 (all jobs):
READ: bw=186MiB/s (195MB/s), 186MiB/s-186MiB/s (195MB/s-195MB/s), io=3070MiB (3219MB), run=16521-16521msec
WRITE: bw=62.1MiB/s (65.1MB/s), 62.1MiB/s-62.1MiB/s (65.1MB/s-65.1MB/s), io=1026MiB (1076MB), run=16521-16521msec
Disk stats (read/write):
sdc: ios=780115/260679, merge=0/0, ticks=792798/230409, in_queue=1023170, util=99.47%
read iops is 46000 - 48000,write iops is 15000-16000
(NB: It looks like the questioner filed this as a Scylla Github issue too - https://github.com/scylladb/scylla/issues/4604 )
[Why is] the disk iops from scylla_setup iotune [...] different from fio test data
Different benchmarks, different results:
Scylla may have been using a much bigger block size (e.g. 64k) per I/O (this is likely the biggest factor). As you make the block size bigger (up to some maximum due to diminishing returns) the bandwidth (i.e. total amount of data you can send in say a second) achieved with that block size goes up but the IOPS you get will typically down (you are sending more data per I/O after all). This is normal!
Scylla could be using buffered I/O (rather than direct I/O)
Scylla may have been benchmarking reads and writes separately
Scylla may have been using a bigger queue depth
Scylla may have been batching its submissions differently
Scylla may be writing a different type of data
And so on...
In general, it's very difficult to take benchmarks done with different tools and compare them directly to each other - you would need to know what they are doing under the hood for any comparison to be meaningful. Trying to look at IOPS or bandwidth in isolation without more context is meaningless as you typically trade one off against the other. It's better to use the same benchmark tool with identical options to compare two different machines changes or to measure the impact of tuning on the same machine.
TLDR; This is likely an apples to oranges comparison where the tools are measuring different contexts.
PS: gtod_reduce is a go faster stripe that very few people actually need. If your hardware isn't capable of doing gigabytes per second and you're not seeing your CPU maxed out it's unlikely reducing gettimeofday calls is going to nudge the result very much.
(This question might be more appropriate for Server Fault (and thus get better replies there) because it's not directly about programming)
Is there a way to set the CPU Resource Limit on the BigQuery with Python and GUI?
I'm getting an error of:
Query exceeded resource limits. 2147706.163729571 CPU seconds were used, and this query must use less than 46300.0 CPU seconds.
Looking at the BigQuery's Python reference page: http://google-cloud-python.readthedocs.io/en/latest/bigquery/reference.html
It looks like there's:
1. maximum_billing_tier
2. maximum_bytes_billed
That can be set, but there is no CPU second options.
You cannot set anymore maximum_billing_tier - it is obsolete and as soon as you are lower than tier 100 you are billed as if it were 1. if you exceed 100 - query just failes.
As of CPU - check concept of slots
Maximum concurrent slots per project for on-demand pricing — 2,000
The default number of slots for on-demand queries is shared among all queries in a single project. As a rule, if you're processing less than 100 GB of queries at once, you're unlikely to be using all 2,000 slots.
To check how many slots you're using, see Monitoring BigQuery Using Stackdriver. If you need more than 2,000 slots, contact your sales representative to discuss whether flat-rate pricing meets your needs.
See more at https://cloud.google.com/bigquery/quotas#query_jobs
I want to monitor my redis cache cluster on ElastiCache. From AWS/Elasticache i am able to get metrics like FreeableMemory and BytesUsedForCache. If i am not wrong BytesUsedForCache is the memory used by cluster(assuming there is only one node in cluster). I want to calculate percentage uses of memory. Can any one help me to get percentage of Memory uses in Redis.
We had the same issue since we wanted to monitor the percentage of ElastiCache Redis memory that is consumed by our data.
As you wrote correctly, you need to look at BytesUsedForCache - that is the amount of memory (in bytes) consumed by the data you've stored in Redis.
The other two important numbers are
The available RAM of the AWS instance type you use for your ElastiCache node, see https://aws.amazon.com/elasticache/pricing/
Your value for parameter reserved-memory-percent (check your ElastiCache parameter group). That's the percentage of RAM that is reserved for "nondata purposes", i.e. for the OS and whatever AWS needs to run there to manage your ElastiCache node. By default this is 25 %. See https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/redis-memory-management.html#redis-memory-management-parameters
So the total available memory for your data in ElastiCache is
(100 - reserved-memory-percent) * instance-RAM-size
(In our case, we use instance type cache.r5.2xlarge with 52,82 GB RAM, and we have the default setting of reserved-memory-percent = 25%.
Checking with the info command in Redis I see that maxmemory_human = 39.61 GB, which is equal to 75 % of 52,82 GB.)
So the ratio of used memory to available memory is
BytesUsedForCache / ((100 - reserved-memory-percent) * instance-RAM-size)
By comparing the freeableMemory and bytesUsedForCache metrics, you will have the available memory for the Elasticache non-cluster mode (not sure if it applies to cluster-mode too).
Here is the NRQL we're using to monitor the cache:
SELECT Max(`provider.bytesUsedForCache.Sum`) / (Max(`provider.bytesUsedForCache.Sum`) + Min(`provider.freeableMemory.Sum`)) * 100 FROM DatastoreSample WHERE provider = 'ElastiCacheRedisNode'
This is based on the following:
FreeableMemory: The amount of free memory available on the host. This is derived from the RAM, buffers and cache that the OS reports as freeable.AWS CacheMetrics HostLevel
BytesUsedForCache: The total number of bytes allocated by Redis for all purposes, including the dataset, buffers, etc. This is derived from used_memory statistic at Redis INFO.AWS CacheMetrics Redis
So BytesUsedForCache (amount of memory used by Redis) + FreeableMemory (amount of data that Redis can have access to) = total memory that Redis can use.
With the release of the 18 additional CloudWatch metrics, you can now use DatabaseMemoryUsagePercentage and see the percentage of memory utilization in redis.
View more about the metric in the memory section here
You would have to calculate this based on the size of the node you have selected. See these 2 posts for more information.
Pricing doc gives you the size of your setup.
https://aws.amazon.com/elasticache/pricing/
https://forums.aws.amazon.com/thread.jspa?threadID=141154
I am trying to find out the actual space usage in Azure Storage for a Blob with snapshots. As the charges accrued against storing snapshots is dictated by the block-level changes (http://msdn.microsoft.com/en-us/library/azure/hh768807.aspx), what I am trying to find out is "is there an optimization in storage?", if so what is the optimization. Let us suppose the size of the blob is 1 MB and snapshot is also 750 KB. The total size i can fetch is 1 MB + 750 KB, but the charge may accrued for 1 MB assuming that the 750 KB are unchanged between blobs. How do I know the actual size?
There is no easy way of finding this out for a single blob. We provide billable storage size only for the entire storage account through the storage metrics.
Have to come up with a proposal to use Amazon S3 with CloudFront as CDN.
One of the important thing is to do a cost estimate. I read over AWS website and forums, used their calculator, but couldn't come to a conclusion with the final number (approx) that I will be confident of. Honestly, I got confused between terms like "Data Transfer Out", "GET and Other Requests" and whether I need to fill in the details both at Amazon S3 and Amazon CloudFront and then do a sum total.
So need help here to estimate my monthly bill.
I will be using S3 to store files (mostly images)
I will be configuring cloud front with my S3 bucket to deliver the content.
Most of the client base (almost 95%) is in US.
Average file size: 500KB
Average number of files stored on S3 monthly: 80000 (80K)
Approx number of total users requesting for the file monthly or approx number of total requests to fetch the file from CloudFront: 30 Millions monthly
There will be some invalidation requests per month (lets say 1000)
Would be great if I can get more understanding as to how my monthly bill will be calculated and what approximately it will be.
Also, with the above data and estimates, any approx on how much the monthly bill, if I use Akamai or Rackspace.
I'll throw another number into the ring.
Using http://calculator.s3.amazonaws.com/calc5.html
CloudFront
data transfer out
0.5MB x 30 million = ~15,000GB
Average size 500kb
1000 invalidation requests
95% US
S3
Storage
80K x 0.5MB 4GB
requests
30million
My initial result is $1,413. As #user2240751 noted, a factor of safety of 2 isn't unreasonable, so that's in the $1,500 - $3,000/month range.
I'm used to working with smaller numbers, but the final amount is always more than you might expect because of extra requests and data transfer.
Corrections or suggestions for improvements welcome!
Good luck
The S3 put and get request fields (in your case) should be restricted to the number of times you are likely to call / update the files in S3 from your application only.
To calculate the Cloudfront service costs, you should work out the rough outbound bandwidth of your page load (number of objects served from cloudfront per page - then double it - to give yourself some headroom), and fill in the rest of the fields.
Rough calc.
500GB data out (guess)
500k average object size
1000 invalidation requests
95% to US based edge location
5% to Europe based edge location
Comes in at $60.80 + your S3 costs.
I think the maths here is wrong 0.5MB * 30,000,000 is 14503GB NOT 1500GB - thats a factor of 10 out unless I'm missing something
Which means your monthly costs are going to be around $2000 not $200