I saw the tool has median session length, but does it allow me to see total time spent per user?
Yes this is possible, if you go to the active users section e.g. https://www.facebook.com/analytics/your-app-id/?section=active_users. You can click the carrot next to "Median Session Length" and change to "Median Time Spent per User"
Facebook Analytics for Apps Time Spent Chart
Related
I have a website and would be good if we could track the average session time within a certain page. This metric is relevant because each subset of pages has different content and we need to track the time spent at each page.
The relevant metrics:
- average session time
- average number of sessions by day
I read the heap documentation and I didn't find a clear way to do this. Also, I didn't find something telling that this is impossible.
Any help will be good.
While working on the SharePoint app, I noticed that it takes more than 10 seconds to load the app first time. so, I was thinking that how much ramp-up period will be idle for running 1000 users on JMeter?
Not sure about the "idle", do you mean "ideal" ramp-up?
I believe the slow initial load can be explained by how IIS internally works:
https://social.technet.microsoft.com/Forums/ie/en-US/297fb51b-b7b4-4b7b-a898-f6c91efd994e/sharepoint-2013-first-load-takes-long-time?forum=sharepointadmin
Taking all that the information into account, we can predict that high response times due to the long initial load will occur for at most several minutes in the beginning of your test and affect the users which are started during this period.
Finding out the "ideal" ramp-up time can be a little bit tricky.
I would address the problem like that:
Add the Response Times Over Time (https://jmeter-plugins.org/wiki/ResponseTimesOverTime/) graph.
Set the ramp-up time to 10 seconds per user and, using the graph added above, find out when the response times will settle down. This will mean that the initial load of the application is completed. Don't forget to exclude this period from the report.
Now you should observe that the response times are slowly growing with the addition of new users.
After the addition of all of the users, if everything went well, you can try to lower your ramp-up time to, say, 3600 seconds for all of the users.
If you see that the response times skyrocketed and/or exceeded the SLA, than you either are adding the users too fast, or the application is already saturated.
I am analyzing a web application and want to predict the maximum users that application can support. Now i have the below numbers out of my load test execution
1. Response Time
2. Throughput
3. CPU
I have the application use case SLA
Response Time - 4 Secs
CPU - 65%
When i execute load test of 10 concurrent users (without Think Time) for a particular use case the average response time reaches 3.5 Seconds and CPU touches 50%. Next I execute load test of 20 concurrent users and response time reaches 6 seconds and CPU 70% thus surpassing the SLA.
The application server configuration is 4 core 7 GB RAM.
Going by the data does this suggests that the web application can support only 10 user at a time? Is there any formula or procedure which can suggest what is the maximum users the application can support.
TIA
"Concurrent users" is not a meaningful measurement, unless you also model "think time" and a couple of other things.
Think about the case of people reading books on a Kindle. An average reader will turn the page every 60 seconds, sending a little ping to a central server. If the system can support 10,000 of those pings per second, how many "concurrent users" is that? About 10,000 * 60, or 600,000. Now imagine that people read faster, turning pages every 30 seconds. The same system will only be able to support half as many "concurrent users". Now imagine a game like Halo online. Each user will be emitting multiple transactions / requests per second. In other words, user behavior matters a lot, and you can't control it. You can only model it.
So, for your application, you have to make a reasonable guess at the "think time" between requests, and add that to your benchmark. Only then will you start to approach a reasonable simulation. Other things to think about are session time, variability, time of day, etc.
Chapter 4 of the "Mature Optimization Handbook" discusses a lot of these issues: http://carlos.bueno.org/optimization/mature-optimization.pdf
Parse now allows us to send 30 requests/second, but it is not straightforward to me.
Quoting some info gathered:
Here they say
At 30 requests/sec, an app can send us 77.76 million API requests in
a month before needing to pay a dime.
So I suppose he meant
send up to 77.76 million
Here, they suggest the rate of requests/second is calculated in a small window, generally a minute. This was answered about 2 years ago.
On their pricing faq page they give an example:
if an app is set to 30 requests/second, your app will hit its request
limit once it makes more than 1,800 requests over a 60 second period.
Suggesting that the window is one minute, even though they didn't clearly state it.
What intrigues me is that they say:
Pricing is pro-rated by the hour.
What does it mean? (sorry if it's obvious, English is not my first language)
Has anyone actually used parse and kept track of those request/second and burst/limits?
The only resource I found was a guy saying he had a web application with 10,000 users/day staying in the website around 4min, and he had under 12r/s.
Moreover, if my app logs users' activities, would that be a good practice to cache this info then send it in random times like between from 3am-7am?
Any help is very appreciated. My company is deciding whether go forward with Parse or not, so it's very important.
They could have worded it better but it basically means the same as "We'll charge you for a minimum of 1 hour based on the request limit you have set".
Here's an example. Assume you are using a 40 rps settings ($100/month which is $100/720 hours). If you keep this for 1 minute, you'll be charged for 1 hour, roughly $1.40.
You can change the request limit as often as you want. So if your app/site receives peak traffic for only 12 hours/day, you can increase the limit just for those 12 hours and end up paying just for those 12 hours.
Check the third question (How frequently can I increase/decrease my request limit?) on the FAQ page at https://parse.com/plans/faq
How frequently can I increase/decrease my request limit?
You can increase/decrease your request/limit as frequently as you would like
within a given month. We will prorate your charges on an hourly basis.
Not really clear what the pro rating means as I understand the setting to be an explicit limit that you pay for. If your limit is exceeded then the requests fail. I don't think there's an option to allow for payment on demand when the limit is exceeded but pro rating would do that.
The one minute is accurate and that is the current limit management.
The point of the pricing model is that your service should be making money before you reach any of the limits. If you have enough users to hit the limits and you aren't making money then you need to reconsider your business plan. As such you shouldn't need to upload at random times of day as your users should naturally spread out a bit.
Here is something that can help you understand Parse's users request per second.
Parse estimates that the average app's active user will issue 10 requests. Thus, if you had a million users on a particular day, and their traffic was evenly spread throughout the day, you could estimate your app would need about 10,000,000 total API requests, or about 120 requests per second. Every app is different, therefore Parse encourages you to measure how many requests your users send.
You can read more this question answered directly from Parse staff here on Parse/F&A link
Hope this helps
I'm looking for a tool that will send me an alert for page load time.
Think of a downtime alert, eg: Pingdom, but one that sends alerts once a page load time increases above a certain threshold. Eg: Alert that X page has taken greater than 7 seconds consistently for 30 minutes.
I know of a lot of tools that give you historical records and page speed metrics after the fact, or give you Apdex scores, but nothing that alerts around speed thresholds.
Does anyone know of such a tool?
Almost all website monitoring services have alerts when the response time is above certain threshold. Your question however is bit more specific since you have a time frame (30 min). Depending on the service used and the monitoring frequency, during a 30 min period you might have between 1 and 30 tests. Do you want an alert if all of those tests are above 7 seconds or if the average response time is above 7 seconds?
I can speak of WebSitePulse where you can receive an alert if 1 or more tests in a row have detected a problem or if the page-load time is within certain limits.
GTmetrix.com Offers Daily alerts for Yslow and PageSpeed scores, as well as great breakdowns and grades for specific ticket items. Great freemium business model as well, free for 3 sites.
Upgraded versions include loading videos of your site.
Source: Just used it for my company's site.