Exam AWS Certified DevOps Engineer - Professional DOP-C02 topic 1 question 73 discussion

Option A is the most cost-effective solution. By configuring a warm pool of EC2 instances in the Stopped state, the company can reduce the time it takes for new instances to be ready to serve requests. When the Auto Scaling group launches a new instance, it can attach the stopped EC2 instance from the warm pool. The instance can then be started up immediately, rather than having to wait for the data to be downloaded and processed. This reduces the overall startup time for the application. Option C is also a solution that involves a warm pool of EC2 instances, but the instances are in the Running state. This means that they are already running and incurring costs, even though they are not currently serving requests. This is not a cost-effective solution.

keywords: MOST cost-effective way to reduce the application startup time

C " The company must reduce the time that elapses before new EC2 instances are ready to serve requests."!!!!!!!!!! this cannot happen with a stopped instance as it will still need to read the data from S3 upon startup,

A for warm pool in the hibernated or stop status we will pay only for the attached EBS volume, therefore its much cost effective rather than running instance

Warm Pool allows instances to be set to a stopped state after performing any process (e.g., running initialization scripts, warm-up tasks, etc.).

A is correct: the question says <the application needs to process data from an Amazon S3 bucket before the application can start to serve requests> but <The size of the data that is stored in the S3 bucket is growing>. This means we should maintain a warm pool for EC2 so that they are always ready to process data (reduce the time that elapses before new EC2 instances are ready) B and D: no mention of warmpool C: If the instance is up and running, no need to configure warm pool

Answer is A, the question is cost-effective, and even with A you will have less wait time to download the S3 data, it will download the delta from the warm up process to ready to join to ASG

excerpt from the url: https://aws.amazon.com/blogs/compute/scaling-your-applications-faster-with-ec2-auto-scaling-warm-pools/ EC2 Auto Scaling Warm Pools works by launching a configured number of EC2 instances in the background, allowing any lengthy application initialization processes to run as necessary, and then stopping those instances until they are needed

A is the most cost-effective solution. Besides, when the warm EC2 was created, it already downloaded the contents from S3 so the next time when it started, it would just download any new files from S3. ( e.g s3 sync )

C is right. please carefully check the question: The company must reduce the time that elapses before new EC2 instances are ready to serve requests. When the application starts up. the application needs to process data from an Amazon S3 bucket before the application can start to serve requests.

I understand the question is asking for the most cost-effective. keeping it stopped state is most cost efficient but it would not work because in the question it also states that, "When the application starts up. the application needs to process data" and to process that data takes time. If the Ec2 instance is stopped then started at the time of need, then again it will take time to process the data, right? so in this scenario, the EC2 instance need to be running.

I think it should be C, as the A option would not be effective. Coming from the instance stop state the application will start up again and need to process the data from S3 bucket.

Warm pool with stopped state is most cost efficient option

A - Keep it stopped until you need it to save money

While A can also be a cost-effective solution, C is the MOST cost-effective solution because it utilizes Amazon S3 Transfer Acceleration, which is a feature that enables fast, easy, and secure transfers of files over the internet between Amazon S3 buckets and EC2 instances located in different regions or across the internet. By using S3 Transfer Acceleration, the data transfer speed can be increased significantly, which can reduce the time that elapses before new EC2 instances are ready to serve requests. In contrast, A suggests using a larger instance size with more CPU and network capacity, which can be more expensive than the current instance size. Moreover, this approach may not be scalable in the long run since as the data in the S3 bucket continues to grow, the instance size may need to be further increased, which can incur more costs. Therefore, while A can also be a viable solution, C is the most cost-effective and scalable solution.

https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-warm-pools.html Keeping instances in a Stopped state is an effective way to minimize costs.

A for me to decrease costs