We have an ASP.NET project (40 or so Web forms, 50 tables, pretty standard IO stuff with care taken to minimize when possible) that will soon need to be deployed. There will be about 100 concurrent users on the system, but only about 20 at any one time will be pounding on it it. We'll be deploying it on Windows Server 2008, 32-bit initially.
When considering production server spec which should we worry more about, getting more cores and less memory (4 cores and 4mb, for example) or more memory and less cores (2 cores and 8mb)?
Would bumping up to Windows Server 64-bit help with memory utilization?
32-bit Windows Server can only address ~3gb of memory. Get 64-bit, 2 cores and 4gb. Or if money isn't an issue, get 8 cores and 24gb. The point is to never guess. If you guess you will be wrong. Monitor the memory pressure and cpu load, and buy more/upgrade as necessary. It's impossible, and foolish, to try to guess what will be the performance bottleneck. The only way is to measure, measure, measure and respond according to that.
One important piece of information that is not included is how much data the databases are going to be holding and how much each user will be utilizing. That will determine how much cache you're going to want, and whether it will all fit in cache or if you're going to be hitting disk a lot more.
Utilization? Only if you're shooting for >3.5GB of ram. And with 20 simultaneous active users, you're going to want all 4 cores and a sizable cache, because the last thing you want is one active users data being flushed from cache to load another active users data, only to have to hit the disk to get the first users data when they take their next action, sending another active users data from cache... (read: thrashing).
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I have a single page Angular app that makes request to a Rails API service. Both are running on a t2xlarge Ubuntu instance. I am using a Postgres database.
We had increase in traffic, and my Rails API became slow. Sometimes, I get an error saying Passenger queue full for rails application.
Auto scaling on the server is working; three more instances are created. But I cannot trace this issue. I need root access to upgrade, which I do not have. Please help me with this.
As you mentioned that you are using T2.2xlarge instance type. Firstly I want to tell you should not use T2 instance type for production environment. Cause of T2 instance uses CPU Credit. Lets take a look on this
What happens if I use all of my credits?
If your instance uses all of its CPU credit balance, performance
remains at the baseline performance level. If your instance is running
low on credits, your instance’s CPU credit consumption (and therefore
CPU performance) is gradually lowered to the base performance level
over a 15-minute interval, so you will not experience a sharp
performance drop-off when your CPU credits are depleted. If your
instance consistently uses all of its CPU credit balance, we recommend
a larger T2 size or a fixed performance instance type such as M3 or
C3.
Im not sure you won't face to the out of CPU Credit problem because you are using Xlarge type but I think you should use other fixed performance instance types. So instance's performace maybe one part of your problem. You should use cloudwatch to monitor on 2 metrics: CPUCreditUsage and CPUCreditBalance to make sure the problem.
Secondly, how about your ASG? After scale-out, did your service become stable? If so, I think you do not care about this problem any more because ASG did what it's reponsibility.
Please check the following
If you are opening a connection to Database, make sure you close it.
If you are using jquery, bootstrap, datatables, or other css libraries, use the CDN links like
<link rel="stylesheet" ref="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-select/1.12.4/css/bootstrap-select.min.css">
it will reduce a great amount of load on your server. do not copy the jquery or other external libraries on your own server when you can directly fetch it from other servers.
There are a number of factors that can cause an EC2 instance (or any system) to appear to run slowly.
CPU Usage. The higher the CPU usage the longer to process new threads and processes.
Free Memory. Your system needs free memory to process threads, create new processes, etc. How much free memory do you have?
Free Disk Space. Operating systems tend to thrash when the file systems on system drives run low on free disk space. How much free disk space do you have?
Network Bandwidth. What is the average bytes in / out for your
instance?
Database. Monitor connections, free memory, disk bandwidth, etc.
Amazon has CloudWatch which can provide you with monitoring for everything except for free disk space (you can add an agent to your instance for this metric). This will also help you quickly see what is happening with your instances.
Monitor your EC2 instances and your database.
You mention T2 instances. These are burstable CPUs which means that if you have consistenly higher CPU usage, then you will want to switch to fixed performance EC2 instances. CloudWatch should help you figure out what you need (CPU or Memory or Disk or Network performance).
This is totally independent of AWS Server. Looks like your software needs more juice (RAM, StorageIO, Network) and it is not sufficient with one machine. You need to evaluate the metric using cloudwatch and adjust software needs based on what is required for the software.
It could be memory leaks or processing leaks that may lead to this as well. You need to create clusters or server farm to handle the load.
Hope it helps.
I am learning the concept of virtual memory, but this question has been confusing me for a while. Since most modern computers use virtual memory, when a program is in execution, the os is supposed to page data in and out between RAM and disk. But why do we still encounter "out of memory" issue? Could you please correct me if I misunderstood the concept? I really appreciate your explanation.
PS: For example, I was analyzing a large amount of data (>100G) output from simulation on a computing cluster, and read in the data to an C array. Very often the system crashed and complained a memory error.
First: Modern computer do indeed use virtual memory, however there is no magic here. Memory is not created out of nothing. Virtual memory schemes typically allow a portion of the mass storage sub-system (aka hard disk) to be used to hold portions of the process that are (hopefully) less frequently used.
This technique allows processes to use more memory than is available as RAM. However nothing is infinite. Eventually all RAM and Hard Drive resources will be used up and the process will get an out of memory error.
Second: It is not unheard of for operating systems to place a cap on the memory that a process may use. Hit that cap and again, the process gets an out of memory error.
Even with virtual memory the memory available is not unlimited.
Limit 1) Architectural limits. The processor and operating system will place some maximum virtual memory limit.
Limit 2) System Parameters. Many operating systems configure the maximum virtual memory size.
Limit 3) Process quotas. Many operating system have process quotas that limit the maximum virtual memory size.
Limit 4) System resources. Notably page file space.
We're planning to evaluate and eventually potentially purchase perfino. I went quickly through the docs and cannot find the system requirements for the installation. Also I cannot find it's compatibility with JBoss 7.1. Can you provide details please?
There are no hard system requirements for disk space, it depends on the amount of business transactions that you're recording. All data will be consolidated, so the database reaches a maximum size after a while, but it's not possible to say what that size will be. Consolidation times can be configured in the general settings.
There are also no hard system requirements for CPU and physical memory. A low-end machine will have no problems monitoring 100 JVMs, but the exact details again depend on the amount of monitored business transactions.
JBoss 7.1 is supported. "Supported" means that web service and EJB calls can be tracked between JVMs, otherwise all application servers work with perfino.
I haven't found any official system requirements, but this is what we figured out experimentally.
We collect about 10,000 transactions a minute from 8 JVMs. We have a lot of distinct and long SQL queries. We use AWS machine with 2 VCPUs and 8GB RAM.
When the Perfino GUI is not being used, the CPU load is low. However, for the GUI to work properly, we had to modify perfino_service.vmoptions:
-Xmx6000m. Before that we had experienced multiple OutOfMemoryError in Perfino when filtering in the transactions view. After changing the memory settings, the GUI is running fine.
This means that you need a machine with about 8GB RAM. I guess this depends on the number of distinct transactions you collect. Our limit is high, at 30,000.
After 6 weeks of usage, there's 7GB of files in the perfino directory. Perfino can clear old recordings after a configurable time.
I went through documentation of Passenger to find out how many application instances it can run with respect to hardware configuration. Documentation only talks about RAM
The optimal value depends on your system’s hardware and the server’s average load. You should experiment with different values. But generally speaking, the value should be at least equal to the number of CPUs (or CPU cores) that you have. If your system has 2 GB of RAM, then we recommend a value of 30. If your system is a Virtual Private Server (VPS) and has about 256 MB RAM, and is also running other services such as MySQL, then we recommend a value of 2.
It says minimum value can be number of CPU/CPU Cores we have. I have a VPS with one VCPU & 1GB RAM & my service provider has an option to just upgrade the RAM. I'm wondering how far I can just keep upgrading only RAM? How important it is to upgrade number of CPUs?
Quick Answer
Depends on what resources are the bottleneck for your app.
Long answer
You'll need to factor in a few things:
How much CPU time does your app need?
How much RAM does any given instance of your app use at peak load?
Does your app spend a lot of time doing IO intensive tasks? (ie: db and file reads/writes, network communication)
There can be other things to factor in, but your bottlenecks will probably be one of the above. If RAM is your main bottleneck, by all means use your newly available RAM. However, if it turns out that your app is being slowed down by CPU availability or flooded IO, no amount of RAM is going to speed things up.
On the topic of CPU cores; my understanding is that the main Apache process that runs Passenger is a single threaded process. Apache spawns new threads to handle concurrency on an as-needed basis. Each additional CPU core theoretically allows you to spawn x*n threads, where x is the number of threads you can optimally run under a single CPU core and n is the number of CPU cores available to Apache.
Disclaimer: I'm not very well read on Passenger internals; though this logic usually holds true for other kinds of Apache configurations.
Can I set up a replica set in MongoDB 1.8 using servers with different amounts of RAM?
server1: 5gb
server2: 2gb
server3: 4gb
If yes, what are the pros and cons?
No, you do not need equal RAM. (Yes, you could set up a replica set as described.)
MongoDB uses memory-mapped files for all caching, which means that cache paging is handled by the operating system. The replicas with more memory will keep more of the database in memory; those with less will page more to disk.
MongoDB will eventually bring the entire database into memory if it can. If you're using two replicas for reads and one for writes, you might want to use the 5gb and 4gb machines for reads, so they are more likely to be hitting RAM.
Yes, you can configure a replica set this way.
If yes, what are the pros and cons?
Here's a doc explaining the major features of replica sets. Let's take a look at these in light of the RAM differences.
Pros:
More computers means better data redundancy. Having that 2GB node at least means that you have one more copy of the data.
Having a full 3 nodes on a replica set makes it easier to take one down for maintenance.
Cons:
Having servers of different sizes isn't great for automated failover. Let's say that your 5GB server is the primary. What happens when it goes down and the 2GB server wins the election? You still have automated fail-over, but your performance has probably dropped dramatically.
Read scaling may not work very well. Depending on your read patterns, sending reads to the 2GB server may result in lots of extra disk hits and slower performance.
So, the big problem here, is really one of performance. If you're just doing this for a dev setup, then it will basically work. But in production you run the risk of completely tanking your app. If your app is used to living on 4GB+ of RAM and then suddenly drops to 2GB, it may become unusable.
Most production setups want to fail over to another "equally-powered" computer.