Compare the time difference between two time servers - windows

I'm trying to determine if there is any difference in time between two time servers in Windows. For example, I have time.windows.com and time.nist.gov. Is there a simple way to compare the time difference?

From windows you can compare both time sources to your own machine and approximate the difference.
w32tm /monitor /computers:time.windows.com,time.nist.gov
time.windows.com[52.179.17.38:123]:
ICMP: error IP_REQ_TIMED_OUT - no response in 1000ms
NTP: -0.0528936s offset from local clock
RefID: utcnist2.colorado.edu [128.138.141.172]
Stratum: 2
time.nist.gov[132.163.97.1:123]:
ICMP: error IP_REQ_TIMED_OUT - no response in 1000ms
NTP: -0.0476330s offset from local clock
RefID: 'NIST' [0x5453494E]
Stratum: 1
Warning:
Reverse name resolution is best effort. It may not be
correct since RefID field in time packets differs across
NTP implementations and may not be using IP addresses.
Good Luck!
Shane

Related

Time drift between processes on the same virtual guest (VMWare host and windows guest)

I'm struggling a bit with time drift between processes on the same virtual guest
In real life - we have around 50 processes sending messages to each other and the drift
makes reading logs hard.
To illustrate my problem I am running two processes I wrote on a Windows server 2019.
Process 1 (time_client - tc ) finds out what time it is,
and then send a string representing the current time to
process 2 (server TS) via a named pipe.
The string sent looks like '23-May-2022 14:26:55.608'
printout from TS looks like
23-May-2022 13:03:29.344 -
23-May-2022 14:39:57.396 -
23-May-2022 14:39:57.492
diff is 00000:00:00:00.096
server is ahead FALSE
where diff is days:hours:minutes:seconds.milliseconds
TS - the server - does the following:
save the time when process is started
then, upon arrival of time_string from TC
get time from os
print starttime, time from os, time from TC, and diff time_from_os - time_String from TC
tc send a new time_string every minute. The TC is started at every invokation and runs to completion, so every time it is a new instance running
I notice this after ca 2 hrs
win server 2019 on VMWare
diff grows to ca 150 ms after 1 hour
win server 2016 on VMWare
diff grows to ca 50 ms after 1 hour
Linux Rocky 8.6 on VirtualBox - Host Win 10
diff grows to ca 0 ms after 2 hours
The drift between the two processes on windows is very annoying since it messes up log completely.
One process is creating an event, and send a message to another process, which treats is several seconds earlier - according to the logs.
The process are usually up for months - but for some communications processes that are restarted due to lost communication at least daily
So - it is not that the guest is out of synch - that would be ok.
It is that the processes get a different value of 'now' depending on how long they have been running.
Is this a well known problem ? Having a hard time googling it
The problem could be within VMWare or within Windows.

Latency shown in JMETER is much less when I use faster internet connection & run my Test. Is it due to faster internet or some other factors too?

I created a test in JMETER
Add > Sampler > HTTP Request = Get
Server Name = dainikbhaskar.com
No. of threads(users) = 1
Ramp-up period (seconds) = 1,
Loop Count = 1
(My internet connection is a broadband one with the speed 50 MBPS)
I ran the test, ran successful, latency comes as 127 & sometimes less than 100 in subsequent executions.
I switched off my Wi-Fi, connected my laptop with mobile hotspot & executed the same test.
Now the latency is 607, 932, 373, 542, 915
I believe it's happening due to INTERNET CONNECTION SPEED as rest of the inputs are same.
Please confirm whether my perception is correct ? :)
It is correct.
You can also get network latency from https://www.speedtest.net/ or https://fast.com/
Latency is the time from sending the request until first byte of response arrives, so called "Time to first byte"
In JMeter's world:
Latency is Connect Time + Time to send the request + time to get the first byte of response
Elapsed time is Latency + time to get the last byte of the response.
More information:
JMeter Glossary
Understanding Your Reports: Part 1 - What are KPIs?
If you get 5x times higher latency for other connection it means that the majority of time is spend for the packets to travel back and forth. You can see the more precise picture by looking at Network tab of your browser developer tools or using a special solution like Lighthouse

Socket Exception while running load test with Self Provisioned test rig

I am getting the Socket Exception while running load test on self-provisioned test rig.
I am trigger those load tests in agent machine(self-provisioned test rig) from my local machine.
Note : For first 2 to 3 minutes test iterations are passing , after that we are getting the Socket Exception.
Below is the error message :
A connection attempt failed because the connected party did not
properly respond after a period of time, or established connection
failed because connected host has failed to respond.
Below are the stack trace details :
at System.Net.Sockets.Socket.EndConnect(IAsyncResult asyncResult) at
System.Net.ServicePoint.ConnectSocketInternal(Boolean connectFailure,
Socket s4, Socket s6, Socket& socket, IPAddress& address,
ConnectSocketState state, IAsyncResult asyncResult, Exception&
exception)
Run Time - 20min
Sample rate - 10sec
warm up duration 10sec
number of agents used - 2
Load pattern :
initial load - 10user
max user count - 300
step duration - 10sec
step user count - 10
Although, by Changing above values I am still getting the exception in the same way.
I am using Visual studio 2015 enterprise.
The question states: start with 10 users, every 10 seconds add 10 users to a maximum of 300. Thus after 29 increments there will be 300 users and that will take 29*10 seconds which is 4m50s. The test will thus (attempt to) run with the maximum load of 300 users for the remaining 15m10s.
Given that all tests pass for the first 2 or 3 minutes plus the the error message, that suggests that you are overloading some part of the network. It might be the agents, it might be the servers or it might be on the connections between them. Some network components have a maximum number of active connections and the 300 users might be too many.
Increasing the load so rapidly means you do not clearly know what the limiting value. The sampling rate (at 10 seconds) seems high. At each sampling interval a lot of data is transferred (i.e. the sample data) and that can swamp parts of the network. You should look at the network counters for the agents and controller, also the servers if available.
I recommend changing the load test steps to add 10 users every 30 seconds, so it takes about 15 minutes to reach 300 users. It may also be worth reducing the sample rate to every 20 seconds.

MongoDB-Java performance with rebuilt Sync driver vs Async

I have been testing MongoDB 2.6.7 for the last couple of months using YCSB 0.1.4. I have captured good data comparing SSD to HDD and am producing engineering reports.
After my testing was completed, I wanted to explore the allanbank async driver. When I got it up and running (I am not a developer, so it was a challenge for me), I first wanted to try the rebuilt sync driver. I found performance improvements of 30-100%, depending on the workload, and was very happy with it.
Next, I tried the async driver. I was not able to see much difference between it and my results with the native driver.
The command I'm running is:
./bin/ycsb run mongodb -s -P workloads/workloadb -p mongodb.url=mongodb://192.168.0.13:27017/ycsb -p mongodb.writeConcern=strict -threads 96
Over the course of my testing (mostly with the native driver), I have experimented with more and less threads than 96; turned on "noatime"; tried both xfs and ext4; disabled hyperthreading; disabled half my 12 cores; put the journal on a different drive; changed sync from 60 seconds to 1 second; and checked the network bandwidth between the client and server to ensure its not oversubscribed (10GbE).
Any feedback or suggestions welcome.
The Async move exceeded my expectations. My experience is with the Python Sync (pymongo) and Async driver (motor) and the Async driver achieved greater than 10x the throughput. further, motor is still using pymongo under the hoods but adds the async ability. that could easily be the case with your allanbank driver.
Often the dramatic changes come from threading policies and OS configurations.
Async needn't and shouldn't use any more threads than cores on the VM or machine. For example, if you're server code is spawning a new thread per incoming conn -- then all bets are off. start by looking at the way the driver is being utilized. A 4 core machine uses <= 4 incoming threads.
On the OS level, you may have to fine-tune parameters like net.core.somaxconn, net.core.netdev_max_backlog, sys.fs.file_max, /etc/security/limits.conf nofile and the best place to start is looking at nginx related performance guides including this one. nginx is the server that spearheaded or at least caught the attention of many linux sysadmin enthusiasts. Contrary to popular lore one should reduce your keepalive timeout opposed to lengthen it. The default keep-alive timeout is some absurd (4 hours) number of seconds. you might want to cut the cord in 1 minute. basically, think a short sweet relationship with your clients connections.
Bear in mind that Mongo is not Async so you can use a Mongo driver pool. nevertheless, don't let the driver get stalled on slow queries. cut it off in 5 to 10 seconds using the following equivalents in Java. I'm just cutting and pasting here with no recommendations.
# Specifies a time limit for a query operation. If the specified time is exceeded, the operation will be aborted and ExecutionTimeout is raised. If max_time_ms is None no limit is applied.
# Raises TypeError if max_time_ms is not an integer or None. Raises InvalidOperation if this Cursor has already been used.
CONN_MAX_TIME_MS = None
# socketTimeoutMS: (integer) How long (in milliseconds) a send or receive on a socket can take before timing out. Defaults to None (no timeout).
CLIENT_SOCKET_TIMEOUT_MS=None
# connectTimeoutMS: (integer) How long (in milliseconds) a connection can take to be opened before timing out. Defaults to 20000.
CLIENT_CONNECT_TIMEOUT_MS=20000
# waitQueueTimeoutMS: (integer) How long (in milliseconds) a thread will wait for a socket from the pool if the pool has no free sockets. Defaults to None (no timeout).
CLIENT_WAIT_QUEUE_TIMEOUT_MS=None
# waitQueueMultiple: (integer) Multiplied by max_pool_size to give the number of threads allowed to wait for a socket at one time. Defaults to None (no waiters).
CLIENT_WAIT_QUEUE_MULTIPLY=None
Hopefully you will have the same success. I was ready to bail on Python prior to async

Windows Snmp Management Api - Snmp timeout/retry doesn't appear to work

I'm noticing some weird snmp communication behavior when using MS SNMP Mgmt Api in terms of timeout and retries. I was wondering if mgmt api is supported on Win Server 2008 R1 x64. My program is a C++ 64bit snmp extension agent that uses the mgmt api to communicate with other agents as well.
This is my pseudo code:
SnmpMgrOpen(ip address, 150ms timeout, 3 retries)
start = getTickCount()
result = SnmpMgrRequest(get request with 3 or 4 OIDs)
finish = getTickCount()
if (result == some error)
{
log Error including total time (i.e finish - start ticks)
}
SnmpMgrClose()
When the snmpMgrRequest call times out, the total time equals anywhere from 1014ms to 5000ms. If, I set retries to 0, the total time is still 1014ms to 5000ms.
I would expect, with retries to 0 that the SnmpMgrRequest would timeout within 150ms. The documentation seems to imply this. Am I missing something is there a minimum timeout period of at least a second? What could be causing this behavior?
Any help would be greatly appreciated. I'm at a lost here.
ballerstyle_98#hotmail.com
From my experience with SNMP on Windows platforms the minimum timeout value is 1 second. So even if you set it to any value lower than that, it will default to 1 second.
Also the timeout value used is doubled for every retry. So with a 150ms 3 retry configuration in the worst case you will have a failed response to a request in 1+2+2+2 =7 seconds.
I hope this helps.

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