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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design Resilient Architectures | 26% | - Highly available architectures
|
| Topic 2: Design Secure Architectures | 30% | - Data protection and encryption
|
| Topic 3: Design Cost-Optimized Architectures | 20% | - Cost optimization strategies
|
| Topic 4: Design High-Performing Architectures | 24% | - Storage and database performance
|
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NEW QUESTION # 143
A manufacturing company develops an application to give a small team of executives the ability to track sales performance globally. The application provides a real-time simulator in a popular programming language.
The company uses AWS Lambda functions to support the simulator. The simulator is an algorithm that predicts sales performance based on specific variables.
Although the solution works well initially, the company notices that the time required to complete simulations is increasing exponentially. A solutions architect needs to improve the response time of the simulator.
Which solution will meet this requirement in the MOST cost-effective way?
Answer: A
Explanation:
When an AWS Lambda function is invoked, especially after periods of inactivity, it may experience cold starts that delay execution. As demand increases, the scaling behavior and latency of Lambda can affect performance. Provisioned Concurrency is an AWS feature designed specifically to solve this issue.
From AWS Documentation:
"Provisioned Concurrency keeps functions initialized and hyper-ready to respond in double-digit milliseconds." (Source: AWS Lambda Developer Guide - Managing Concurrency) Why Option D is correct:
Provisioned Concurrency ensures that a specified number of Lambda function instances are always warm and ready to serve requests, eliminating cold start latency.
It's cost-effective for workloads with consistent usage patterns, like real-time simulations for a small user group.
Maintains scalability and low overhead of Lambda without moving to managed container or EC2 platforms.
Why the other options are less optimal:
Option A (Fargate) and Option B (EC2): Introduce more infrastructure and higher ongoing costs for a small team with likely intermittent usage.
Option C (AWS Batch): Ideal for batch jobs, not real-time simulations; also incurs higher latency due to job queuing.
References:
AWS Lambda Developer Guide - "Concurrency and Scaling"
AWS Well-Architected Framework - Performance Efficiency Pillar
AWS Compute Services Comparison - Lambda vs EC2 vs Fargate
NEW QUESTION # 144
Every user you create in the lAM system starts with ___ _
Answer: B
NEW QUESTION # 145
A company has established a new AWS account. The account is newly provisioned and no changes have been made to the default settings The company is concerned about the security of the AWS account root user What should be done to secure the root user?
Answer: B
NEW QUESTION # 146
A company's web application is using multiple Linux Amazon EC2 instances and storing data on Amazon EBS volumes. The company is looking for a solution to increase the resiliency of the application in case of a failure and to provide storage that complies with atomicity, consistency, isolation, and durability (ACID).
What should a solutions architect do to meet these requirements?
Answer: D
Explanation:
Explanation
How Amazon EFS Works with Amazon EC2
The following illustration shows an example VPC accessing an Amazon EFS file system. Here, EC2 instances in the VPC have file systems mounted.
In this illustration, the VPC has three Availability Zones, and each has one mount target created in it. We recommend that you access the file system from a mount target within the same Availability Zone. One of the Availability Zones has two subnets. However, a mount target is created in only one of the subnets.
Benefits of Auto Scaling
Better fault tolerance. Amazon EC2 Auto Scaling can detect when an instance is unhealthy, terminate it, and launch an instance to replace it. You can also configure Amazon EC2 Auto Scaling to use multiple Availability Zones. If one Availability Zone becomes unavailable, Amazon EC2 Auto Scaling can launch instances in another one to compensate.
Better availability. Amazon EC2 Auto Scaling helps ensure that your application always has the right amount of capacity to handle the current traffic demand.
Better cost management. Amazon EC2 Auto Scaling can dynamically increase and decrease capacity as needed. Because you pay for the EC2 instances you use, you save money by launching instances when they are needed and terminating them when they aren't.
https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html#how-it-works-ec2
https://docs.aws.amazon.com/autoscaling/ec2/userguide/auto-scaling-benefits.html
NEW QUESTION # 147
A newspaper organization has a on-premises application which allows the public to search its back catalogue and retrieve individual newspaper pages via a website written in Java They have scanned the old newspapers into JPEGs (approx 17TB) and used Optical Character Recognition (OCR) to populate a commercial search product. The hosting platform and software are now end of life and the organization wants to migrate Its archive to AW5 and produce a cost efficient architecture and still be designed for availability and durability. Which is the most appropriate?
Answer: C
Explanation:
There is no such thing as "Most appropriate" without knowing all your goals. I find your scenarios very fuzzy, since you can obviously mix-n-match between them. I think you should decide by layers instead:
Load Balancer Layer: ELB or just DNS, or roll-your-own. (Using DNS+EIPs is slightly cheaper, but less reliable than ELB.)
Storage Layer for 17TB of Images: This is the perfect use case for 53. Off-load all the web requests directly to the relevant JPEGs in 53. Your EC2 boxes just generate links to them.
If your app already serves it's own images (not links to images), you might start with EFS. But more than likely, you can just setup a web server to re-write or re-direct all JPEG links to 53 pretty easily.
If you use 53, don't serve directly from the bucket- Serve via a CNAME in domain you control. That way, you can switch in CloudFront easily.
EBS will be way more expensive, and you'll need 2x the drives if you need 2 boxes. Yuck. Consider a smaller storage format. For example, JPEG200 or WebP or other tools might make for smaller images.
There is also the DejaVu format from a while back.
Cache Layer: Adding Cloud Front in front of 53 will help people on the other side of the world-- well, possibly. Typical archives follow a power law. The long tail of requests means that most JPEGs won't be requested enough to be in the cache. So you are only speeding up the most popular objects. You can always wait, and switch in CF later after you know your costs better. (In some cases, it can actually lower costs.)
You can also put CloudFront in front of your app, since your archive search results should be fairly static.
This will also allow you to run with a smaller instance type, since CF will handle much of the load if you do it right.
Database Layer: A few options:
Use whatever your current server does for now, and replace with something else down the road.
Don't under-estimate this approach, sometimes it's better to start now and optimize later.
Use RDS to run MySQL/ Postgres
I'm not as familiar with ElasticSearch I Cloudsearch, but obviously Cloudsearch will be less maintenance+setup.
App Layer:
When creating the app layer from scratch, consider Cloud Formation and/or OpsWorks. It's extra stuff to learn, but helps down the road.
Java+ Tomcat is right up the alley of ElasticBeanstalk. (Basically EC2 + Autoscale + ELB).
Preventing Abuse: When you put something in a public 53 bucket, people will hot-link it from their web pages. If you want to prevent that, your app on the EC2 box can generate signed links to 53 that expire in a few hours. Now everyone will be forced to go thru the app, and the app can apply rate limiting, etc.
Saving money: If you don't mind having downtime:
run everything in one AZ (both DBs and EC2s). You can always add servers and AZs down the road, as long as it's architected to be stateless. In fact, you should use multiple regions if you want it to be really robust.
use Reduced Redundancy in 53 to save a few hundred bucks per month (Someone will have to "go fix it" every time it breaks, including having an off-line copy to repair 53.)
Buy Reserved Instances on your EC2 boxes to make them cheaper. (Start with the Rl market and buy a partially used one to get started.) It's just a coupon saying "if you run this type of box in this AZ, you will save on the per-hour costs." You can get 1/2 to 1/3 off easily.
Rewrite the application to use less memory and CPU -that way you can run on fewer/ smaller boxes.
(May or may not be worth the investment.)
If your app will be used very infrequently, you will save a lot of money by using Lambda. I'd be worried that it would be quite slow if you tried to run a Java application on it though ..
We're missing some information like load, latency expectations from search, indexing speed, size of the search index, etc. But with what you've given us, I would go with 53 as the storage for the files (53 rocks. It is really, really awesome). If you're stuck with the commercial search application, then on EC2 instances with autoscaling and an ELB. If you are allowed an alternative search engine, Elasticsearch is probably your best bet. I'd run it on EC2 instead of the AWS Elasticsearch service, as IMHO it's not ready yet. Don't autoscale Elasticsearch automatically though, it'll cause all sorts of issues. I have zero experience with
CloudSearch so I can't comment on that. Regardless of which option, I'd use Cloud Formation for all of it.
NEW QUESTION # 148
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