Dress4Win has asked you to recommend machine types they should deploy their application servers to. How should you proceed?
A.
Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types in the cloud.
B.
Recommend that Dress4Win deploy application servers to machine types that offer the highest RAM to CPU ratio available.
C.
Recommend that Dress4Win deploy into production with the smallest instances available, monitor them over time, and scale the machine type up until the desired performance is reached.
D.
Identify the number of virtual cores and RAM associated with the application server virtual machines align them to a custom machine type in the cloud, monitor performance, and scale the machine types up until the desired performance is reached.
A - not correct. as its talking about Physical server size
B - not correct. as we its talking about Max spec
C - not correct. as its talking about the Smallest spec
D - is CORRECT. as its recommending to map with on premises app VM Size
Agree. Starting with a minimal size at which your application can run efficiently/optimally is the best practice. This would be best estimate from past usage so monitor closely and apply vertical and horizontal scaling.
Agreed, but confused as question states they're moving Test/Dev first and C says "into Production". If they're looking to save money, start small and grow until performance needs are met. Test/Dev is typically tolerant to these incremental changes.
D i think:
Start with the smallest instances and scale up to a larger machine type until the performance is of the desired standard. is the right answer.
In continuation of the above explanation, although you could use a predefined machine type like e2-highmem-4/n2-highmem-4/n2d-highmem-4 etc. if you need 4 VCPUs and 32GB memory, there's no guarantee that it performs similar to the existing VM in the data centre. The networking fabric is different, the disk I/O is different, and the CPUs are different too. We don't know the exact specifications of the data centre CPUs to draw a parallel to the processors offered by GCP. As you can see, the performance can vary a lot depending on the frequency. (remember shelling out additional 500$ for upgrading CPU from 2.6GHz to 2.8GHz when buying your a laptop?). You may realize that you need more vCPUs after migrating to Google Cloud or maybe less, but until you migrate and test it out, there is no way to say which is the best machine type. So the recommendation should be to start small, increase the instance size as needed until the performance is of an acceptable standard, and that is your machine type.
C is correct. In option D, it says No.of virtual cores and RAM associated... Which is not mentioned in Case study as well. This option just trying to confuse that set. So will go with C.
the smallest instance avail is as low as 1CPU with 128MB RAM - Is that sufficient for prod run (assume currently its running with 24CPU with 128GB of ram in on premise)
I thought, only dev and testing environment migrated first and in that case, I prefer to start with smallest instance available. - Dynamic scalability is the reason, we are moving to cloud.
The best solution would be "use a small machine type suitable for the app server, use MIGs and autoscaling" but that's not in the answers.
B - no, the legacy app servers are 4 CPU, 32 GB (1 CPU : 8 GB), high memory machine types are 1 CPU : 30 GB (e.g. m3-ultramem-32)
C - no, the smallest instance available is too small for an app server
A or D - It depends on "is the on perm env virtualized?". In "Storage appliances" the case study mentions "iSCSI for VM hosts". If that applies to the app servers, the correct answer is D.
Application servers as mentioned in the study, doesn't mean VMs, nothing is mentioning VMs on prem, besides custom types on GCP cost more than predefined types, I'll map their physical servers to the nearest machine type.
since they have VM's in current environment, I'll choose D. This lets you like for like replace the on prem footprint and scale from there.
I originally thought A, however, using custom machine image will prevent you from paying for running a larger machine image than necessary.
By identifying the number of virtual cores and RAM associated with the application server virtual machines and aligning them to custom machine types in the cloud, you can create an environment tailored to Dress4Win's specific needs. Monitoring performance and adjusting the machine types accordingly ensures that the infrastructure is optimized for both performance and cost.
I'll be truly surprised if the correct answer is C.
Deploying the smallest instances into production will likely trigger a ton of error messages in real life.
If you're oversizing the VMs, just simply scale it down.
IMPORTANT: Dress4Win is not anymore part of the officially listed case studies: https://cloud.google.com/certification/guides/professional-cloud-architect
https://cloud.google.com/migrate/compute-engine/docs/4.9/concepts/planning-a-migration/cloud-instance-rightsizing
1. Performance-based recommendations: Recommends Compute Engine instances based on the CPU and RAM currently allocated to the on-premises VM. This recommendation is the default.
Wow, these answers are so dumb I'm compelled to comment so new people don't mistakenly think this is how it works in the real world. You're not supposed to map sizes one-to-one OR start with the smallest instance sizes available. The industry best practice is to right-size based on actual utilization. I guess I'll pick C if this question comes up, because at least it will be cheaper than starting with big instances (but it could cause production operational issues if the instances are undersized!).
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