In our tests, seems that memUsageLimit is fixed in function of installed RAM and platform. For smartphones (mostly ARM processors) the limits are
185 MB for 512 MB RAM device
390 MB for 1GB RAM device
900 MB for 2GB RAM device
For regular Windows + Intel platforms, we found the limit is about 20% more than physical available RAM, perhaps due to the ability of paging to disk.
My question is regarding the first group of devices (phones): is it possible to change the memory limit for a given application? We need to process a JSON document received via oData V4, and when processing with NewtonSoft, the memory consumption is very significant: for every MB of pure JSON data, the app process is increased about 9MB in a very linear fashion.
Win10 1.586 does provide a new API, TrySetAppMemoryUsageLimit, to set the app's memory limitation. However, based on internal discussion, this API only works for very limited scenario right now, such as VOIP application on mobile device. And the sample code and document for this API are not quite ready.
I have tested this API on the UWP VOIP sample and it does work(we need to set the sample project's target to 10586). The code looks like below:
var y = MemoryManager.AppMemoryUsageLimit;
bool result = MemoryManager.TrySetAppMemoryUsageLimit(y+10000);
As for your requirement, we will keep collecting the feedback about this feature. If there is any strong requirement, we will communicate with internal team. However, my personal suggestion for you is that: win store app has very strong safety policy for the apps. It is really not recommended for APP to exceed memory limitation.
Related
Looks like the most powerful instance type you can have in Google App Engine is one with 2G memory. One of our Rails application reaches the memory limit quickly on higher load. Autoscaling helps but wondering if there is a way to add more power instances in GAE?
If not, how have you solved this problem?
yes, in App Engine Standard the higher tier is F4_HIGHMEM with 2048 MB of memory. You have 3 ways to scale up with standard:
Automatic: based on request rate, response latencies, and other application metrics.
Basic: creates dynamic instances when your application receives requests.
Manual: uses resident instances that continuously run the specified number of instances regardless of the load level.
Therefore, the question here would be how are you reaching this limit? How are you managing your memory? Take a look into your console metrics: memoryusage. A ladder graphs shown a bad usage of the memory. When deploying apps in the Cloud, you must have in mind that the usage of the resources bust be more accurate.
You can analyze and check if choosing an automatic scale based on Max concurrent Requests would be a good option for you to mitigate your issue with the memory.
This is for Standard, Flexible is managed different. You can specify from 0.9 to 6.5 GB per CPU core.
I have some cryptography code that has multiple implementations, selecting which implementation at runtime based on the features of the CPU it is running on. Porting this has been straightforward so far, with Windows, Linux and Android being easy.
But in iOS it does not seem easy. While x86 CPUs have the cpuid instruction to detect features, even from user mode, the ARM equivalent is privileged. It is not possible to detect CPU features on ARM without OS cooperation.
In Windows, IsProcessorFeaturePresent works for detecting ARM CPU features. On Linux, /proc/cpuinfo is the way to go. Android has a cpufeatures library (and /proc/cpuinfo still works anyway). Mac OS has sysctlbyname with hw.optional.*.
But what about iOS? The iOS kernel has hw.optional.* like Mac OS, but it is locked down in iOS 10. (Thus, my question is not a duplicate of this one, as circumstances have since changed.) Also, getting a list of those seems difficult - Apple's open source web site runs an automated process to scrub all ARM-specific code from the OS source they give out publicly in order to make jailbreakers work harder.
You may take a look on the iOS Security Guide for business
Apparently, if you can get the CPU series name, you may also deduce which cryptographic component and how it works from the documentation.
You may note that some devices have a Security Enclave:
The Secure Enclave is a coprocessor fabricated in the Apple T1, Apple
S2, Apple S3, Apple A7, or later A-series processors.
Page 6
And you may deduce that any older CPU version has not.
Every iOS device has a dedicated AES-256 crypto engine built into the
DMA path between the flash storage and main system memory
[...]
On T1, S2, S3, and A9 or later A-series processors, each Secure Enclave
generates its own UID (Unique ID).
Page 12
Method to access cryptographic components will depend of which kind of data or storage you would to get an access ( local data storage / sync / home data / app / siri / icloud / secure note / keybag / payment / applepay / vpn / wifi password / SSO / airdrop / etc...)
Could you precise which part of the cryptographic part you need to access in your use case?
You may also take a look here and here to get additional information relative to iOS native security and cryptography API.
The reason behind iOS blocking certain hardware information is very simple. Please read about Apple A11 processor. There is so much stuff in it, also stuff, which will never be documented.
Apple simply does not want developers to be aware of it and use it. I would not expect any progress on this topic.
The only way forward at this moment is to bypass the OS and talk directly to the hardware. You would be amazed what is inside and how quickly it responds!
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.
We are deploying a simple REST grails (2.3.7) app to heroku. The application is doing little less than "Hello World", yet we exceed the 1x dyno limit of 512MB (usually going between 600-700MB).
What is the expectation of memory usage of such an application?
Also, is there an official minimum requirements concerning memory?
Currently the minimum for a basic application is around or just above the 512mb amount depending on what the app does. We are aware of the problems this creates for Heroku and currently you need double dynos to run Grails applications on Heroku.
We are working to improve Grails support for micro services and a smaller memory footprint in Grails 3.0.
See this question stackoverflow :
memory usage of grails application
and what i can say is based on
If memory is not a problem on your server then allocate a large amount of memory, such as 512M or more. Also use the server VM option. EG: (-server -Xms512M -Xmx512M). Usually it is better to set both min and max heap size to the same in server applications.
However, if you running on a virtual host with limited memory, Grails 1.0 RC1 has been tested on tomcat 6 with both -Xmx96M and -Xmx128M, it performed well with both settings. I've heard reports of it running on lesser configurations"
And , REST application memory requirement can be high according to the request and how complex query and results involved, And also how you managed to do the coding that you properly cleared out every session , object after use ? But , i guess for REST application one > 512 <= 1GB of memory is good to start. And , use so tweaks for memory as well. it should be fine!
I am trying to find a definitive answer as to what the best setting is for the JVM Heap Size in Domino 8.5.3 FP4 - 64 Bit for Windows.
I know that by default it's set to 1024M. Some web sites have suggested that it's recommended to be 1G / 1024M - but that's the default setting so it that as good as it gets?
Other sites have said 25% of available RAM.
My Domino server has 12GB RAM available. It's currently got HTTPJVMMaxHeapSize = 1024M and Task Manager tells me that around 7GB of RAM is in use and nhttp.exe is using around 1.1GB. I want to increase this Heap to 2GB or 3GB if possible - will there be any issues doing to?
I'm running Windows Server 2008 R2 Standard Edition.
Speaking from an XPages perspective:
1 - Understand the dynamics of the working set and hardware
That is, understand what the application code, server runtime, and hardware profile is doing when processing a given working set (ie: the XPages application(s) within the server). Is the application coded in a non-optimal manner in terms of lifecycle execution and memory usage? Is the application making use of memory or disk persistence for component tree serialization? Is the server assigned an adequate amount of JVM memory? Is the hardware providing enough CPU and memory?
2 - Profile and monitor the working set with upper limit loads
To fully answer some of the questions in #1, detailed performance and scalability profiling must be carried out using tools like the XPages Toolbox and Eclipse Memory Analyzer. Furthermore, test the working set using Rational Performance Tester (or some other performance testing tool) to mimic real life concurrent workloads in a test environment. This allows you to set up a test environment where you can hit your application with (n) number of concurrent users using automation and collect that all invaluable data on health etc.
3 - Analyse the profile information to identify bottlenecks within the working set
Remember your working set can be one or more applications. Each doing something different, and having different load requirements. Be specific about the task at hand - do you want to tune the system more generally for all applications (for an average scale) or do you want the server to be fully optimized for a specific application (for a targeted scale)?
4 - Optimize the working set where applicable
Get in and make changes to the XSP / Java / ServerSide JavaScript code where applicable - use your knowledge of the XPages Request Processing Lifecycle and also look out for those hungry JVM memory consumers under high end load scenarios. Always favor disk persistence (disk storage is cheaper than RAM!) and code your custom Java objects and Managed Beans accordingly to cope with serialization and restoration. And make the trade-offs between function and speed in these scenario's where high scalability ends up burning CPU... a smarter UX with targetted functions / actions etc.
5 - Scale the hardware where applicable
Be prepared to increase cores, clock speeds, RAM, disk storage based on the needs of the working set - a cyclic approach to profiling, monitoring, and optimizing the working set will shed more and more light on the suitability of the hardware as this process evolves.
5 - Repeat from #2 until the working set and hardware performs and scales to the expected requirements / load expectancy of the system
I would recommend to set server's notes.ini param JavaVerboseGC=1 with console output into console.log in IBM_TECHNICAL_SUPPORT directory. After some time, take that log file and use IBM Support Assistant with tool IBM Monitoring and Diagnostic Tools for Java - Garbage Collection and Memory Visualizer (GCMV).
This could help how to interpret collected data: http://www-01.ibm.com/support/docview.wss?uid=swg27013824&aid=1.
You definitely should do that if you get OutOfMemoryException.
Heap size set too high can lead to fewer GC runs but taking longer time - server will periodically "hang" for very short time. So too high setting is not recommended.