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NEW QUESTION: 1
You are planning to deploy an application named App1 that will run in containers on Azure Kubernetes Service (AKS) clusters. The AKS clusters will be distributed across four Azure regions.
You need to recommend a storage solution for App1. Updated container images must be replicated automatically to all the AKS clusters.
Which storage solution should you recommend?
A. Premium SKU Azure Container Registry
B. Azure Cache for Redis
C. Azure Content Delivery Network (CDN)
D. geo redundant storage (GRS) accounts
Answer: A
Explanation:
Explanation
Enable geo-replication for container images.
Best practice: Store your container images in Azure Container Registry and geo-replicate the registry to each AKS region.
To deploy and run your applications in AKS, you need a way to store and pull the container images. Container Registry integrates with AKS, so it can securely store your container images or Helm charts. Container Registry supports multimaster geo-replication to automatically replicate your images to Azure regions around the world.
Geo-replication is a feature of Premium SKU container registries.
Note:
When you use Container Registry geo-replication to pull images from the same region, the results are:
Faster: You pull images from high-speed, low-latency network connections within the same Azure region.
More reliable: If a region is unavailable, your AKS cluster pulls the images from an available container registry.
Cheaper: There's no network egress charge between datacenters.
Reference:
https://docs.microsoft.com/en-us/azure/aks/operator-best-practices-multi-region
NEW QUESTION: 2
A. Option B
B. Option D
C. Option A
D. Option C
Answer: D
NEW QUESTION: 3
For a given mean, which distribution would you prefer for frequency modeling where operational risk events are considered dependent, or in other words are seen as clustering together (as opposed to being independent)?
A. Poisson
B. Gamma
C. Negative binomial
D. Binomial
Answer: C
Explanation:
Explanation
An interesting property that distinguishes the three most used distributions for modeling event frequency is that for a given mean, their variances differ. The ratio of variance to mean (the variance-mean ratio, calculated as variance/mean) can then be used to decide the kind of distribution to use. Both the variance and the mean can be estimated from available data points from the internal or external loss databases, or the scenario exercise.
The variance-mean ratio reflects how dispersed a distribution is. (In the PRMIA handbook, the variance to mean ratio has been described as the "Q-Factor".) The Poisson distribution has its mean equal to its variance, and therefore the variance to mean ratio is 1. For the negative binomial distribution, this ratio is always greater than 1, which means there is greater dispersion compared to the mean - or more intervals with low counts as well as more intervals with high counts. For the binomial distribution, the variance to mean ratio is less than one, which means it is less dispersed than the Poisson distribution with values closer to the mean.
In a situation where operational risk events are seen as clustering together, or dependent, the variance will be higher and it would be more appropriate to use the negative binomial distribution.
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