Are there any performance counters for an AD LDS instance? I have searched for them without success. I know that there are performance counters for AD DS, but that is not what I need.
I looked around in Windows Server 2012 R2 and found that there is an object called DirectoryServices which is available for AD LDS instances. I verified a few of the counters, for example LDAP Client Sessions.
There seems to be no documentation about this in AD LDS sections of Windows Server.
Related
We have been using IMX6ULL processors along with a Quectel 4G module in our custom made boards. The 4G module can be initialised, brought up and the PPP0 interface can also be initialised which in-turn does provide us with internet connectivity too but, when we start downloading files (of about 10 MB - 200 MB), we have observed that the download begins to stall at irregular intervals. While the download does stall, the PPP0 interface is still up but we lose internet connectivity hence, we have to kill PPPD and re-initialise PPP0.
We have tried using different variations of PPP0 initialisation scripts that we could get our hands on but the issue still persisted however, recently when we wanted to dump the traffic on the PPP0 interface using TCPDUMP in-order to analyse the same, we observed that the download does not stall anymore and we also observed a much better 4G throughput too. We have still not been able to figure out why this is indeed the case. Any inputs or guidance on the same would be of great help.
P.S: The kernel version we have been using is 4.1.15 but, we have observed a similar behavior with the 5.4.70 kernel too.
Thanks in advance
Regards
Nitin
Check the 4G network first with AT+COPS? and AT+CSQ
Does the Module disconnect from the base station?
Do not try kill pppd and restart setting up ppp0, and try AT+CFUN=0 \ AT+CFUN=1 to restart the network registration first.
And for 4G module, the Quectel provide a tool named quectel-CM to setup internet connection, it is of better performance than ppp.
btw, have you check the the memory used and the CPU status?
We had a custom spring boot starter based on rsocket-rpc and we used FragmentationDuplexConnection. After upgrading to Rsocket 1.1.0 and rsocket-rpc 0.3.0, it seems that FragmentationDuplexConnection no longer exists in the code. What replaced it?
We used it because we had problems using RSocket through websocket through load balancer/proxy and had to set the MTU to 65K.
#Mavo with RSocket-Java 1.1 we revised internals and moved that logic to dedicated reactive-streams operators. The reason for that is Head-Of-Line Blocking problem pretended to be solved with fragmentation is not solved in reality given RSocket-Java 1.0 design (within a duplex connection we have only a single thread consuming data, hence fragmentation done on the DuplexConnection level will block other frames from fragmentation until the currently fragmented one will not be fully delivered).
To resolve the mentioned design problem, we moved fragmentation and reassembly to a level above. Now every responder side operator has a reassembly logic in it (e.g -> https://github.com/rsocket/rsocket-java/blob/master/rsocket-core/src/main/java/io/rsocket/core/RequestStreamResponderSubscriber.java#L315), as well as every requester operator, do fragmentation before sending frames to duplex connection and do this operation independently from the other requests and can do it on its own thread (https://github.com/rsocket/rsocket-java/blob/master/rsocket-core/src/main/java/io/rsocket/core/FireAndForgetRequesterMono.java#L150)
I have two machines. There are multiple Tesla cards on each machine. There is also an InfiniBand card on each machine. I want to communicate between GPU cards on different machines through InfiniBand. Just point to point unicast would be fine. I surely want to use GPUDirect RDMA so I could spare myself of extra copy operations.
I am aware that there is a driver available now from Mellanox for its InfiniBand cards. But it doesn't offer a detailed development guide. Also I am aware that OpenMPI has support for the feature I am asking. But OpenMPI is too heavy weight for this simple task and it does not support multiple GPUs in a single process.
I wonder if I could get any help with directly using the driver to do the communication. Code sample, tutorial, anything would be good. Also, I would appreciate it if anyone could help me find the code dealing with this in OpenMPI.
For GPUDirect RDMA to work, you need the following installed:
Mellanox OFED installed (from http://www.mellanox.com/page/products_dyn?product_family=26&mtag=linux_sw_drivers )
Recent NVIDIA CUDA suite installed
Mellanox-NVIDIA GPUDirect plugin (from the link you gave above - posting as guest prevents me from posting links :( )
All of the above should be installed (by the order listed above), and the relevant modules loaded.
After that, you should be able to register memory allocated on the GPU video memory for RDMA transactions. Sample code will look like:
void * gpu_buffer;
struct ibv_mr *mr;
const int size = 64*1024;
cudaMalloc(&gpu_buffer,size); // TODO: Check errors
mr = ibv_reg_mr(pd,gpu_buffer,size,IBV_ACCESS_LOCAL_WRITE|IBV_ACCESS_REMOTE_WRITE|IBV_ACCESS_REMOTE_READ);
This will create (on a GPUDirect RDMA enabled system) a memory region, with a valid memory key that you can use for RDMA transactions with our HCA.
For more details about using RDMA and InfiniBand verbs in your code, you can refer to this document.
I'm building a one-off smart-home data collection box. It's expected to run on a raspberry-pi-class machine (~1G RAM), handling about 200K data points per day (each a 64-bit int). We've been working with vanilla MySQL, but performance is starting to crumble, especially for queries on the number of entries in a given time interval.
As I understand it, this is basically exactly what time-series databases are designed for. If anything, the unusual thing about my situation is that the volume is relatively low, and so is the amount of RAM available.
A quick look at Wikipedia suggests OpenTSDB, InfluxDB, and possibly BlueFlood. OpenTSDB suggests 4G of RAM, though that may be for high-volume settings. InfluxDB actually mentions sensor readings, but I can't find a lot of information on what kind of resources are required.
Okay, so here's my actual question: are there obvious red flags that would make any of these systems inappropriate for the project I describe?
I realize that this is an invitation to flame, so I'm counting on folks to keep it on the bright and helpful side. Many thanks in advance!
InfluxDB should be fine with 1 GB RAM at that volume. Embedded sensors and low-power devices like Raspberry Pi's are definitely a core use case, although we haven't done much testing with the latest betas beyond compiling on ARM.
InfluxDB 0.9.0 was just released, and 0.9.x should be available in our Hosted environment in a few weeks. The low end instances have 1 GB RAM and 1 CPU equivalent, so they are a reasonable proxy for your Pi performance, and the free trial lasts two weeks.
If you have more specific questions, please reach out to us at influxdb#googlegroups.com or support#influxdb.com and we'll see hwo we can help.
Try VictoriaMetrics. It should run on systems with low RAM such as Raspberry Pi. See these instructions on how to build it for ARM.
VictoriaMetrics has the following additional benefits for small systems:
It is easy to configure and maintain since it has zero external dependencies and all the configuration is done via a few command-line flags.
It is optimized for low CPU usage and low persistent storage IO usage.
It compresses data well, so it uses small amounts of persistent storage space comparing to other solutions.
Did you try with OpenTSDB. We are using OpenTSDB for almost 150 houses to collect smart meter data where data is collected every 10 minutes. i.e is a lot of data points in one day. But we haven't tested it in Raspberry pi. For Raspberry pi OpenTSDB might be quite heavy since it needs to run webserver, HBase and Java.
Just for suggestions. You can use Raspberry pi as collecting hub for smart home and send the data from Raspberry pi to server and store all the points in the server. Later in the server you can do whatever you want like aggregation, or performing statistical analysis etc. And then you can send results back to the smart hub.
ATSD supports ARM architecture and can be installed on a Raspberry Pi 2 to store sensor data. Currently, Ubuntu or Debian OS is required. Be sure that the device has at least 1 GB of RAM and an SD card with high write speed (60mb/s or more). The size of the SD card depends on how much data you want to store and for how long, we recommend at least 16GB, you should plan ahead. Backup batter power is also recommended, to protect against crashes and ungraceful shutdowns.
Here you can find an in-depth guide on setting up a temperature/humidity sensor paired with an Arduino device. Using the guide you will be able to stream the sensor data into ATSD using MQTT or TCP protocol. Open-source sketches are included.
I've set up a solution that creates rapid fire PDF reports. Currently it seems I can't get Reporting Services to use all the resources it has available to it. The system doesn't appear to be IO bound, CPU bound, or memory bound. Any suggestions on trying to figure out why it's running so?
The application isn't network IO bound, and it is multi-threaded to 2 times the number of processors.
SQL Server Reporting Services limits the number of reports run to 2 simultaneous ad-hoc reports and 2 simultaneous web reports. This is a hard limit imposed by the server.
Robin Day is probably right, however if you are using a processor that supports hyper threading you may get a performance benefit by turning this off in the BIOS. You can try an a A/B performance test.
You could also check the SQL instance (when you say reporting service you mean SSRS right?) has not a got processor affinity set.
Is this a case of not using a multi threaded approach? Is the machine using 100% of one core of a processor and that's the bottleneck?
EDIT: Sorry for stating the obvious, was just an idea before you mentioned that it was already multi threaded. I'm afraid I can't offer any more suggestions.
Any suggestions on trying to figure out why it's running so?
a) There's an API to restrict a whole process to one CPU: test that using GetProcessAffinityMask.
b) 'Thread state' and 'Thread wait reason' are two of the performance counters ... maybe you can read this to see why threads, we you think ought to be running, aren't.
All the threads of your application are fighting for a single lock. Use a profiler to see if there is a congestion somewhere.
If you have four cores, that would explain why you see 25% overall CPU usage.
Maybe the server can't deliver more data over the network (so it's network IO bound)?