There are 20 issues with different impacts like 10 - blocker, 5 - critical, 3 - serious and 2 - moderate. Each impacts has default weights like blocker: 50, critical: 25, Serious: 15, Moderate: 10 which is the sum of 100 (equivalent to 100%). Now I want to calculate the scores likes
What is the overall pass percentage out of 100%
What is the fail percent of blocker out of 100%
What is the fail percent of critical out of 100%
What is the fail percent of Serious out of 100%
What is the fail percent of moderate out of 100%
**Note: ** Score need to be prioritise based on the default values.
Can someone help me in sharing the formula
Related
Calculate project work risk completion rate (in excel) based on
Deadline
Work effort/work-effort weight
of tasks completed
Given
Project Unit: Milestone-1 - Milestone-4, MVP-1 (includes All milestones)
Work effort for each milestone (e.g. Milestone-1 = 3 points or small work effort, Milestone-2 = 5 or medium, Milestone-3 = 8 or large)
Work-effort weight for each Milestone (in %)
% or # of Completed tasks per a Milestone
How do I include the time in the equation? Say we have a start date and projected due date or duration (e.g. x weeks or days or months), I need to calculate the risk of completing a task (milestone and the entire MVP) on time based on the current # of tasks completed.
In other words, what is the risk (small/medium/large) that a Milestone/Milestones/MVP will be completed on time (say, Mar-31, 2023) based on the number of tasks completed (15 of 40)?
Please let me know if I need to clarify
I really appreciate any help you can provide.
The image is missing the time/deadline value so the risk is inaccurate current view
I currently have an alert that triggers on average cpu over 80% over the last 15 minutes. However, we have instances that stay over 100% for hours or days while others are very look leaving the average under 80%. I want to find those instances that are higher than 80% for an extended period of time. But what I don't want is a spike and using the max seems only do just that, spend out alerts for spikes and not constants. Anyway I can get such an alert configured?
The graph shows cpu's max > 96%, but cpu's avg < 10%
How can this be the case? (I mean, shouldn't cpu's avg > 40, or at least >30?)
Not really, I estimated some of the values from the Graph, and put them in a spreadsheet and calculated a 5 Min Average, as well as calculated the Max CPU and the Average of the 5 Min Average. Below is what it looks like. When you are doing an Average over a time, it smooths out all the peaks and lows.
Max 5 Min Avg
85
40
20
5
25 35
40 26
5 19
10 17
99 35.8
Max Average
99 26.56
If it is continually at high CPU, then your overall average will start growing.
However that average does look rather low on your graph, but you aren't showing the Min CPU either, so it may be short burst where it is high, but more often low CPU usage, you should graph that as well.
Are you trying to configure alerts or scaling? Then you should be looking at the average over a small period e.g. 5 minutes, and if that exceeds a threshold (usually 75-80%) then you send the alert and or scale out.
I asked Microsoft Azure support about this. The answer I received was not great and essentially amounts to "Yes, it does that." They suggested only using the average statistic since (as we've noticed) "max" doesn't work. This is due to the way data gets aggregated internally. The Microsoft Product engineering team has a request (ID: 9900425) in their large list to get this fixed, so it may happen someday.
I did not find any documentation on how that aggregation works, nor would Microsoft provide any.
Existing somewhat useful docs:
Data sources: https://learn.microsoft.com/en-us/azure/azure-monitor/agents/data-sources#azure-resources
Metrics and data collection: https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/data-platform-metrics#data-collection
I am using SQL Azure SQL Server for my App. My app was in was working perfectly till recently and the MAX dtu usage has been 100% but the AVG DTU usage ois around 50%.
Which value should i monitor to scale the services, MAX or AVG?
I found on the net after lots of searching:
CPU max/min and average within that 1 minute. As 1 minute (60 seconds) is the finest granularity, if you chose for example max, if the CPU has touched 100% even for 1 second, it will be shown 100% for that entire minute. Perhaps the best is to use the Average. In this case the average CPU utilization from 60 seconds will be shown under that 1 minute metric.
which sorta helped me with what it all meant, but thanks to bradbury9 too for your input.
I'm working on a project in Tableau (which uses functions very similar to Excel, if that helps) where I need a single measurement derived from two different measurements, one of which is a low decimal number (2.95 on the high end, 0.00667 on the low) and the other is a percentage (ranging from 29.8 to 100 percent).
Put another way, I have two tables detailing bus punctuality -- one is for high frequency routes and measured in Excess Waiting Time (EWT, in minutes), the other for low frequency routes and measured in terms of percent on time. I have a map of all the routes, and want to colour the lines based on how punctual that route is (thinner lines for routes with a low EWT or a high percentage on time; thicker lines for routes with high EWT or low percentage on time). In preparation for this, I've combined both tables and zero'd out the non-existent value.
I thought I'd do something like log(EWT + PercentOnTime), but am realizing that might not give the value I'm wanting (especially because I ultimately need an inverse of one or the other, since low EWT is favourable and high % on time favourable).
Any idea how I'd do this? Thanks!
If you are combining/comparing the metrics in an even manner and the data is relatively linear then all you need to do is normalise them.
If you have the EWT expected ranges (eg. 0.00667 to 2.95). Then a 2 would be
(2 - 0.00667)/(2.95 - 0.00667) = 0.67723 but because EWT is the inverse semantically to punctuality we need to use 1-0.67723 = 0.32277.
If you do the same for the Punctuality percentage range:
Eg. 80%
(80 - 29.8)/(100-29.8) = 0.7169
You can compare these metrics because they are normalised (between 0-1 : multiply by 100 to get percentages) if you are assuming the underlying metrics (1-EWT) and on time percentage (OTP) are analogous.
Thus you can combine these into a single table. You will want to ignore all zero'd values as this is actually an indication you have no data at these points.
you'll have to use an if statement to say something like :
if OTP > 0 then ([OTP-29.8])/(100-29.8) else (1-(([EWT]-0.00667)/(2.95-0.00667)))
Hope this helps.