exam questions

Exam AZ-104 All Questions

View all questions & answers for the AZ-104 exam

Exam AZ-104 topic 6 question 15 discussion

Actual exam question from Microsoft's AZ-104
Question #: 15
Topic #: 6
[All AZ-104 Questions]

HOTSPOT -
You have an Azure App Service plan named ASP1.
CPU usage for ASP1 is shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Hot Area:

Show Suggested Answer Hide Answer
Suggested Answer:
Box 1: four times -
From the exhibit we see that the time granularity is 6 hours: Last 30 days (Automatic - 6 hours).
CPU Percentage Last days Automatic - hours

Box 2: scaled up -
Scale up when:
* You see that your workloads are hitting some performance limit such as CPU or I/O limits.
* You need to quickly react to fix performance issues that can't be solved with classic database optimization.
* You need a solution that allows you to change service tiers to adapt to changing latency requirements.
Reference:
https://docs.microsoft.com/en-us/azure/azure-monitor/essentials/metrics-troubleshoot https://azure.microsoft.com/en-us/overview/scaling-out-vs-scaling-up

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
awssecuritynewbie
Highly Voted 2 years, 1 month ago
so to just explain a bit better hopefully :) look at the top right you can see it is auto updated every 6 hours so within 24hours it is checked 4 times (4*6=24h) . It would need to scale up to have a bigger CPU to support the load that is getting as it is currently 100%
upvoted 74 times
DeBoer
1 year, 10 months ago
Agree with the first answer, disgress on the second. Scaling up will incur the new, higher, cost at all times. You can alsow get more power into the app by scaling OUT; if you automate with autoscaling you can get the costs much lower. The AVERAGE usage is pretty low - so this app should scale out/in pretty well https://learn.microsoft.com/en-us/azure/architecture/best-practices/auto-scaling
upvoted 11 times
Batiste2023
1 year ago
As for the second question: this is about an app plan and the only scaling that can be done here is scale up (or down).
upvoted 3 times
Batiste2023
1 year ago
Also, given the fact, that the average CPU usage is creeping somewhere between 0-10% all the time, scaling down seems the much more appropriate choice here!
upvoted 5 times
Watcharin_start
9 months, 1 week ago
In this graph, it was shown for the CPU percentage(also meant CPU usage in percent). The calculation for maximum used is hitting to 100% but you could be seen AVG is low cause it has a shot time peak not all-time peak. This answer should be scaling up.
upvoted 1 times
...
...
...
...
...
Mohaamed
Highly Voted 1 year, 12 months ago
Answer is correct Box 1 : look at the top right of the picture it says 6 hours so 24hours/6hours = 4 times box2: this is app plan and VM so you scale up only
upvoted 17 times
...
GuessWhoops
Most Recent 1 month, 3 weeks ago
Once more, our ambiguous Microsoft question that is not objective whatsoever and leave open to interpretation. First choice is 4, there is no doubt on that, we all agree, ok. Second is... What "optimize" even means here? Its the idea of improve this application regardless of other factors, in this case Scale Up. But the average of CPU is low, so optimize in my opinion, turning optimal and appropriate that is, I would scale down. And yes, both scale up and scale out are options in an App Service Plan, just create one and you will see. Cool thing about Scale Out is the autoscaling that can happen depending on your plan choose whereas Scale Up and Down would be manual only.
upvoted 2 times
...
SeMo0o0o0o
2 months ago
CORRECT..
upvoted 2 times
...
23169fd
6 months ago
4 times Scale out: This means adding more instances to distribute the load Scale up :This means increasing the resources (CPU, memory) of the existing instances. => Scale out will be a better option
upvoted 4 times
...
bombat27
7 months ago
I don't see why people are saying scale up/out. It's averaging 3% cpu usage.
upvoted 3 times
...
[Removed]
11 months ago
In real life, seeing the usage report, I would honestly scale the app down. It's barely using its CPU resources except the occasional spikes - probably because some job is running at that time. To save on costs and have better resource optimisation, I would scale it down. The exception to this rule would be that if during peak times, when the CPU is at 100%, the application is having performance issues that affect end users or causes whatever job runs on it to fail. If not, then I don't really care if the CPU peaks 100% and it would be better to have constant usage, let's say in the 50-60% on average with the occasional 100% spikes than just keeping the CPU almost idle for the majority of the time. If this comes in my exam I will answer 4 times and scale down.
upvoted 6 times
[Removed]
11 months ago
Sorry I mean 6 times and scale down.
upvoted 2 times
...
...
Exams_Prep_2021
11 months, 2 weeks ago
in exam 26/12/2023
upvoted 3 times
...
AliNadheer
11 months, 3 weeks ago
question 15 Box1: 4 Box2: scale up app service plan can scale up and scale out depending on the app service tier, i assume this is shared compute tier as there is no mention of it being premium or isolated tier in the question. unless i missed some detail. however based on the exhibit it shows cpu is 100% most of the time, which in my openion we should tier up and scale out.
upvoted 2 times
AliNadheer
11 months, 3 weeks ago
i meant to say: however based on the exhibit it shows cpu is 100% most of the time, which in my opinion we should scale out.
upvoted 1 times
...
AliNadheer
11 months, 3 weeks ago
Shared compute: Free and Shared, the two base tiers, runs an app on the same Azure VM as other App Service apps, including apps of other customers. These tiers allocate CPU quotas to each app that runs on the shared resources, and the resources cannot scale out. These tiers are intended to be used only for development and testing purposes. Dedicated compute: The Basic, Standard, Premium, PremiumV2, and PremiumV3 tiers run apps on dedicated Azure VMs. Only apps in the same App Service plan share the same compute resources. The higher the tier, the more VM instances are available to you for scale-out. Isolated: The Isolated and IsolatedV2 tiers run dedicated Azure VMs on dedicated Azure Virtual Networks. It provides network isolation on top of compute isolation to your apps. It provides the maximum scale-out capabilities. https://learn.microsoft.com/en-us/azure/app-service/overview-hosting-plans
upvoted 1 times
...
...
clg003
1 year ago
I would scale down... maxes only matter if its causing issues and you can tell by the avg it isn't an issue. We do this stuff every single year. I would get no support to scale this app if it was performing as such. This thing could be hitting 100 just on its boot 1x day.
upvoted 2 times
...
AZPRAC
1 year, 1 month ago
Passed my exam on 15 OCT. This question was in the exam. Thanks ET Team.
upvoted 3 times
...
sardonique
1 year, 2 months ago
Mlantonis we desperately need you
upvoted 7 times
...
LemonVine
1 year, 3 months ago
I took the exam around 14th of Aug, this question came out... too bad I did not go thru this question before the exam
upvoted 2 times
...
riccardoto
1 year, 3 months ago
Microsoft will really like your answers on theh second box, but dudes, really, would you really scale up or out an App service that only has less than 4% average CPU utilization ? Sizing resources based on the Max CPU maybe would be OK for a really latency-critical application, but for most "human" scenarios I would actually scale down. Happy to be disrpoved, but maybe I'm just used to work in companies that are more attentive to costs than you guys here ;-)
upvoted 8 times
...
Superego
1 year, 3 months ago
Box 2: Scale Up. https://azure.microsoft.com/en-au/resources/cloud-computing-dictionary/scaling-out-vs-scaling-up/ Scale up when: 1. You see that your workloads are hitting some performance limit such as CPU or I/O limits. 2. You need to quickly react to fix performance issues that can't be solved with classic database optimization. 3. You need a solution that allows you to change service tiers to adapt to changing latency requirements. Scale out when: 1. You have geo-distributed applications where every app should access part of the data in the region. Each app will access only the shard associated to that region without affecting other shards. 2. You have a global sharding scenario—such as load balancing—where you have a large number of geo-distributed clients that insert data in their own dedicated shards. 3. You've maxed out your performance requirements, even in the highest performance tiers of your service, or if your data cannot fit into a single database.
upvoted 1 times
ValB
1 year, 1 month ago
That article is very specific to database scalability. We are talking here of CPU scalability.
upvoted 1 times
...
...
Rams_84zO6n
1 year, 8 months ago
Four times, scaled up - First observation - 30 days - 30 peaks (roughly) in average graph. So focus on a single day - how max cpu graph can be averaged over a time window to get the average graph. A 1 hr window would vary rapidly, a 24 hour window would be smooth as silk - a 6 hr window would give the current smoothness of the average graph - so average CPU calculated 4 times per day. From max graph, it looks like the web app is going through CPU deprivation so a scale up would definitely help alleviate the current issues with performance. Honestly - a 6 hour moving window for average graph would be calculated much more than 4 times a day, but it is the best answer from given data.
upvoted 3 times
...
ChakaZilly
1 year, 9 months ago
The second box, I would say: scale down: Avg CPU is only 4% (occasional spikes of 100% don' t matter that much).
upvoted 9 times
Gzt
1 year, 9 months ago
Agree. Especially who works with SCOM is understanding it ;)
upvoted 1 times
...
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
Loading ...