The best way to find the source of the increased response time is to choose option B: Instrument the Lambda function with the AWS X-Ray SDK. Add HTTP and HTTPS interceptors and SDK client handlers. Deploy the updated Lambda function. Turn on X-Ray tracing. After accumulating enough usage data, use the X-Ray service map to examine the average response times to determine the likely sources.

Reasoning:

X-Ray provides detailed tracing and analysis of requests as they traverse your application. By instrumenting the Lambda function with the X-Ray SDK, you can trace calls to other APIs and AWS services, identifying bottlenecks and sources of latency. The service map visually represents the connections between your components, making it easy to pinpoint the slow parts.
The question specifically asks how to find the *source* of the increased response time. X-Ray is designed to do exactly this.

Why other options are not the best:

Option A: While adding logging statements can provide some insights, it's a manual process and doesn't offer the same level of detailed tracing and visualization as X-Ray. It would be difficult to correlate logs from different services and identify the root cause efficiently.
Option C: CloudWatch metrics can show overall performance trends, but they don't provide granular details about individual requests or the interactions between services. Anomaly detection might highlight that there's a problem, but not necessarily *where* the problem is.
Option D: CloudWatch Synthetics (canaries) are useful for monitoring the overall availability and performance of your application, but they don't provide the same level of detailed tracing as X-Ray. They are better suited for proactive monitoring than for diagnosing specific performance issues. While the canary might show that the user portal is slow, it doesn't necessarily pinpoint the exact source of the latency within the Lambda function's interactions with other services.

Therefore, option B provides the most direct and efficient way to identify the source of the increased response time.

Suggested Answer: B
Reason for choosing this answer: AWS X-Ray is specifically designed for tracing and analyzing distributed applications, making it the most suitable tool for identifying performance bottlenecks in a serverless environment where multiple services interact.
Reasons for not choosing the other answers:

A: While logging can be helpful, it is not as efficient for tracing requests across multiple services as X-Ray.
C: CloudWatch metrics provide a high-level overview but lack the detailed tracing capabilities of X-Ray.
D: CloudWatch Synthetics are useful for monitoring but do not provide the in-depth analysis needed to pinpoint the exact source of latency.

The answer is B.
Reason: AWS X-Ray is specifically designed to trace requests across different microservices and identify bottlenecks, which fits the problem description perfectly.
Why other options are wrong:

A: While logging is helpful, it doesn't provide a holistic view of the request flow across services.
C: CloudWatch metrics will show the symptoms (increased duration, throttles) but not the cause.
D: Synthetics are good for monitoring, but not for in-depth performance analysis of a specific slow request.

B is the correct answer. AWS X-Ray is designed to trace calls through distributed systems.
The reason for selecting B is that it allows you to visualize the flow of requests and pinpoint exactly where the latency is occurring.
Reasons for not selecting other answers:

A: This involves manually adding logs and analyzing them, which is time-consuming and not as effective as using a dedicated tracing tool.
C: This will only show you the overall metrics of the Lambda function and not the individual calls that are causing the slowness.
D: This is a good way to monitor the overall performance of the application, but it will not help you pinpoint the exact cause of the slowness.

The suggested answer is B.
The reason is that AWS X-Ray is designed specifically for tracing requests as they traverse through different services in a distributed application. In this scenario, the Lambda function is interacting with other APIs and AWS services, making X-Ray the ideal tool to identify the bottleneck.
Options A, C, and D are less suitable because:

A: Logging can be useful, but it requires manual effort to correlate logs from different services.
C: CloudWatch metrics provide aggregated data, not detailed tracing information.
D: CloudWatch Synthetics is for monitoring the availability of the application but not for identifying the root cause of performance issues within the Lambda function.

The recommended answer is B.
Reason: AWS X-Ray is built for tracing requests across services. It can identify bottlenecks and latency issues within the distributed application. Adding interceptors and handlers allows for detailed tracing of HTTP/HTTPS requests and interactions with other AWS services.
Why other options are not ideal:

A: Manual logging is time-consuming and doesn't provide a visual representation of the request flow.
C: CloudWatch metrics give an overview but lack detailed tracing information.
D: CloudWatch Synthetics monitors application availability but doesn't pinpoint the source of latency within the Lambda function.

The correct answer is B.
Reason:

AWS X-Ray is designed to trace requests across different services and provide a visual representation of the call flow. This makes it easy to identify bottlenecks and performance issues.
By instrumenting the Lambda function with the X-Ray SDK, you can trace calls to other APIs and AWS services.
The service map generated by X-Ray visually represents the connections between your components, making it easy to pinpoint slow parts.

Why other options are incorrect:

A: While logging is helpful, it requires manually correlating logs from different services, which can be time-consuming and error-prone.
C: CloudWatch metrics can show overall performance trends, but they don't provide the granular details needed to identify the root cause of performance issues.
D: CloudWatch Synthetics is useful for monitoring the overall availability and performance of an application, but it doesn't provide detailed tracing information like X-Ray.

The recommended answer is B.
Reasoning: AWS X-Ray is designed specifically for tracing requests and identifying performance bottlenecks in distributed applications. The question explicitly mentions that the Lambda function interacts with other APIs and AWS services, which makes X-Ray the ideal tool for tracing these interactions and pinpointing the source of the increased response time.
Why other options are not the best choice:

A: Adding logging statements can provide some information, but it requires manually analyzing logs and correlating timestamps, which is less efficient than using X-Ray.
C: CloudWatch metrics can provide an overview of the Lambda function's performance, but they don't provide detailed tracing information for identifying bottlenecks in downstream services.
D: CloudWatch Synthetics is useful for monitoring the overall performance and availability of the application, but it doesn't provide the detailed tracing information needed to diagnose performance issues within the Lambda function and its dependencies.

The best answer is B.
Reason: AWS X-Ray is a service specifically designed for tracing requests through distributed systems. By instrumenting the Lambda function with the X-Ray SDK, you can get a detailed view of the calls to other services and identify where the latency is occurring.
Why other options are not as good:

A: Adding logging statements can be helpful, but it requires manually correlating logs from different services, which can be difficult and time-consuming.
C: CloudWatch metrics can show overall performance, but they don't provide the detailed tracing information needed to pinpoint the source of the problem.
D: CloudWatch Synthetics is useful for monitoring the overall health of the application, but it doesn't provide the detailed tracing information needed to diagnose performance issues within the Lambda function.

The correct answer is B.
Reasoning: AWS X-Ray is designed for tracing requests across different AWS services and applications, making it the best tool for identifying performance bottlenecks in a distributed system. By instrumenting the Lambda function with the X-Ray SDK and enabling tracing, developers can visualize the request flow and identify the specific service or API call that is causing the increased response time.
Why other options are not the best:

A: Adding logging statements is a manual process that can be time-consuming and may not provide a complete picture of the request flow.
C: CloudWatch metrics can provide an overview of the Lambda function's performance, but they don't offer the detailed tracing information needed to identify the root cause of the issue.
D: CloudWatch Synthetics is useful for monitoring the overall availability and performance of an application, but it doesn't provide the detailed tracing information needed to diagnose performance issues within the Lambda function.

The recommended answer is B.
Reasoning: AWS X-Ray is specifically designed for tracing requests as they traverse your application, allowing you to pinpoint bottlenecks and performance issues. It provides detailed insights into the latency of each component, making it the ideal choice for identifying the source of increased response time in a complex serverless environment.
Why other options are not as effective:

A: Adding logging statements requires manual analysis and correlation, which can be time-consuming and less efficient than using a dedicated tracing tool like X-Ray.
C: CloudWatch metrics offer a general overview of the Lambda function's performance but lack the detailed tracing information needed to identify the specific cause of the slowness.
D: CloudWatch Synthetics are useful for monitoring the overall availability and performance of an application but don't provide the granular tracing capabilities of X-Ray.

The answer is B.
Reason: AWS X-Ray is designed specifically for tracing requests as they traverse various services, which makes it ideal for identifying performance bottlenecks in distributed systems.
Why other options are not the best:

A: Logging is helpful, but it's more manual and doesn't provide the same level of request flow visualization as X-Ray.
C: CloudWatch metrics provide a high-level view but lack the detailed tracing information needed for pinpointing the root cause.
D: CloudWatch Synthetics is for monitoring and doesn't provide the detailed tracing required to diagnose performance issues.

The suggested answer is B.
Reasoning:

AWS X-Ray is a service specifically designed for tracing requests across distributed systems, providing detailed insights into latency and performance bottlenecks.
By instrumenting the Lambda function with the X-Ray SDK, developers can trace requests to other APIs and AWS services, identifying the exact source of the increased response time.
The X-Ray service map provides a visual representation of the connections between components, making it easy to pinpoint the slow parts of the application.

Why other options are less suitable:

A: Adding logging statements is a manual and time-consuming process that doesn't provide the same level of detailed tracing as X-Ray.
C: CloudWatch metrics provide a high-level overview of the Lambda function's performance but don't offer the granular tracing information needed to identify the root cause of the issue.
D: CloudWatch Synthetics is useful for monitoring the overall health of an application but doesn't provide the detailed tracing information needed to diagnose performance issues within the Lambda function and its dependencies.

The correct answer is B.
Reason: AWS X-Ray is designed to trace requests across different services in a distributed system, allowing developers to identify bottlenecks and performance issues. By instrumenting the Lambda function with the X-Ray SDK, the code can trace calls to other APIs and AWS services.
Why other options are not as good:

A: Adding logging statements is a manual process and doesn't offer the same level of tracing capabilities as X-Ray.
C: Reviewing CloudWatch metrics can provide some insights, but it doesn't offer the detailed tracing information needed to pinpoint the exact source of the increased response time.
D: Using CloudWatch Synthetics is more for monitoring the overall health of the application and less for pinpointing specific performance bottlenecks.

The suggested answer is B.
Reasoning: AWS X-Ray is designed to trace requests as they travel through your application, pinpointing bottlenecks and performance problems. Its ability to visualize the flow of requests across services is crucial for diagnosing the described issue.
Why other options are not suitable:

A: Manual logging can be cumbersome and doesn't offer the same level of detailed insight as X-Ray.
C: CloudWatch metrics will show symptoms but won't necessarily pinpoint the root cause of the performance issue.
D: CloudWatch Synthetics is better for monitoring the overall availability and performance of an application, but it won't give you the granular details that X-Ray provides for tracing requests.

The recommended answer is B.
Reasoning:

AWS X-Ray is designed for tracing requests as they travel through your application. It's the best tool for identifying performance bottlenecks, especially when dealing with interactions between multiple services.
Instrumenting the Lambda function with the X-Ray SDK allows you to trace the requests to other APIs and AWS services, pinpointing the exact source of the increased response time.
The X-Ray service map provides a visual representation of the connections between components, making it easier to identify slow parts.

Why the other options are not as effective:

A: Adding logging statements is a manual process and doesn't provide the same level of detailed tracing as X-Ray.
C: CloudWatch metrics provide a high-level overview of the Lambda function's performance but lack the granular tracing information needed to identify the root cause of the issue.
D: CloudWatch Synthetics is useful for monitoring the overall availability and performance of an application, but it doesn't provide the detailed tracing information needed to diagnose performance issues within the Lambda function.

The correct answer is B.
Reason: AWS X-Ray is specifically designed for tracing user requests through distributed applications and microservices, which perfectly fits the scenario described in the question. It allows developers to pinpoint performance bottlenecks and identify the source of latency issues by providing a visual representation of the request path and timing information for each service involved.
Why other options are not ideal:

A: While adding logging statements can be helpful, it requires manually analyzing logs and correlating timestamps, which is less efficient and scalable than using X-Ray.
C: CloudWatch metrics can provide an overview of the Lambda function's performance, but they don't provide the detailed tracing information needed to identify the root cause of the issue across multiple services.
D: CloudWatch Synthetics is more suitable for monitoring the overall availability and performance of an application, but it doesn't offer the granular tracing capabilities of X-Ray.

AWS X-Ray, https://aws.amazon.com/xray/