Improve Debugging Skills

As a programmer, I want to improve my debugging skill.

Great, focusing on enhancing your debugging skills as a programmer is an excellent choice for ShadowBox training. Let's begin with a scenario:

Scenario: You're a senior developer working on a large, complex web application. Recently, the application has been experiencing intermittent issues where certain pages load extremely slowly or fail to load at all. This issue is sporadic and doesn't seem to follow a clear pattern. You've been tasked with identifying and fixing the problem.

The application is built using a modern tech stack: React for the frontend, Node.js for the backend, and it's hosted on a cloud platform. The application also heavily relies on third-party APIs for various functionalities.

You've already checked the basics: server health metrics are normal, and there are no obvious errors in the application logs.

Decision Point: How would you proceed to debug this issue? Remember to consider the specifics of the scenario and provide your reasoning for your chosen approach. Feel free to ask additional questions before making your decision.

Do we collect browser-side JS errors?

Yes, the application does collect browser-side JavaScript errors. These are logged into a centralized logging system that aggregates errors from both the frontend and backend. The logging system categorizes errors, providing information such as the type of error, the time it occurred, and the user's browser information.

Now, considering this information, how would you proceed with debugging the issue? Remember to detail your reasoning behind your decision.

Do server health metrics contain performance related metrics and are these metrics all normal?

Yes, the server health metrics do include performance-related metrics such as CPU usage, memory usage, response times, and network activity. These metrics are all within normal ranges, indicating no apparent stress or overload on the server itself.

With this information, how would you approach the debugging process? Please share your decision and the rationale behind it.

Tell me about browser-side JS errors. What do we have?

Upon reviewing the centralized logging system, you find a variety of browser-side JavaScript errors. However, a specific error stands out due to its higher frequency during the times users reported the page loading issues. The error is a "TimeoutError" related to API requests made from the frontend. It appears intermittently and seems to affect various pages that rely heavily on data fetched from third-party APIs.

Given this information, how would you proceed with your debugging strategy? Please explain your decision-making process.

Are the API requests headed to our own API or to 3rd parties?

The "TimeoutError" is occurring in API requests headed to third-party services. These services provide essential data that the application needs for various features on different pages. The error is not associated with the API requests to your own backend.

Considering this new information, what would be your next step in debugging the issue? Please share your approach and the reasoning behind it.

How urgent is the situation, according to business perspective?

From a business perspective, the situation is quite urgent. The intermittent failure of pages to load is impacting user experience and has started to generate complaints from several key users. Additionally, it's causing concern among the stakeholders, as it might affect the reliability and reputation of the application if not resolved promptly.

With this urgency in mind, how would you address the debugging of this issue? Please explain your strategy and the rationale behind it.

Since the error is likely due to 3rd party API, it could take considerable time to fix it. The first thing to do is to check if the other clients using the same API are also experiencing the problem. If so, communicate with the API provider to understand the situation. If not, read the recent commit log to check if the related code has been changed from our side, and then read the changelog of the 3rd party API to check if something relevant has been changed recently. At the same time, tell a customer support team about the situation so they can communicate to the users accordingly.

While doing so, check for another API you can use instead. If there isn't, consider how you can make the rest of the feature continue to work, i.e., graceful degradation, rather than breaking the entire page when that API doesn't work.

Your decision and the rationale behind it are well-considered. Here's my expert feedback:

Questions I Would Have Asked:

1. Is there a pattern to the API failures, such as specific endpoints or times of day?
2. Has there been any recent scaling in the user base or changes in usage patterns that might affect API load?
3. Are there fallback or caching mechanisms in place for API failure scenarios?

Decision I Would Have Made:

1. Firstly, I would analyze the pattern of the TimeoutError in correlation with the API usage. Understanding whether the errors align with peak usage times or specific API endpoints could provide critical insight.
2. Concurrently, I would review recent changes in our codebase and the third-party API's changelog for any updates or modifications that could have impacted the integration.
3. I would also initiate communication with the third-party API provider to report the issue and seek insights or alerts on their end.
4. In parallel, I'd work on implementing a strategy for graceful degradation to maintain functionality of the application even when the API fails, and enhance user communication about the issue.

Rationale Behind the Decision:

• Understanding the error pattern can reveal if the issue is load-related or specific to certain API endpoints.
• Reviewing changes helps in identifying if the issue was introduced by a recent update.
• Communication with the API provider is crucial for a faster resolution and understanding if the issue is on their end.
• Implementing graceful degradation maintains user experience and trust, reducing the impact of the issue.

Now, based on your decision, let's unfold the scenario: You find that other clients using the same API are experiencing similar issues. The API provider acknowledges a recent surge in demand causing sporadic timeouts. Your team communicates the situation to users and starts exploring alternative APIs and implementing graceful degradation for the affected features.

Next Step: How would you proceed further in this situation?

Since it's sporadic, I want to know if responses from the API could be cached. If so, I would introduce a cache proxy server and route API requests from the browser to our cache server. By doing so, I could reduce considerable amount of client-side errors. It will buy me some time.

Your approach to introduce a caching mechanism is strategic and practical under the given circumstances. Here’s the expert feedback:

Questions I Would Have Asked:

1. What is the typical validity duration of the data received from the API? This influences the caching strategy and the time-to-live (TTL) settings for the cache.
2. How does the API handle data consistency, and would caching impact the freshness of data presented to the users?
3. Are there any API usage limits or cost implications associated with introducing a cache proxy server?

Decision I Would Have Made:

1. I would evaluate the feasibility and impact of implementing a cache proxy server, considering the freshness and validity of data, user experience, and technical constraints.
2. Assuming feasibility, I would proceed to implement a cache with appropriate TTL settings, ensuring a balance between reducing load on the API and maintaining data freshness.
3. I would monitor the performance post-implementation to assess the impact on error reduction and user experience, ready to adjust the strategy as needed.

Rationale Behind the Decision:

• Caching can significantly reduce the load on third-party APIs, especially for data that doesn't change frequently.
• It’s important to consider the balance between reducing API calls and ensuring that users receive up-to-date information.
• Continuous monitoring is crucial to evaluate the effectiveness of the solution and make necessary adjustments.

Next Step in the Scenario: You've implemented a cache proxy server, which has successfully reduced the frequency of client-side errors. The user experience has improved, and the number of complaints has decreased. However, you are still dependent on the third-party API's stability for certain real-time data features.

Further Decision Point: How would you manage the ongoing dependency on the third-party API, especially for real-time data requirements? What would be your strategy moving forward?

Have we found alternative API?

In this scenario, let's assume that your team has identified a potential alternative API that offers similar functionalities. However, this alternative has not yet been fully evaluated for compatibility with your application's requirements, including data consistency, performance, and cost.

Decision Point: Given the availability of a potential alternative API, how would you approach the situation? Consider the steps you would take to evaluate and potentially integrate this new API into your application, and explain your reasoning.

Is it possible to implement our own API? How much cost will it take?

In this scenario, the possibility of implementing your own API as a replacement for the third-party service is feasible. However, several factors need to be considered:

1. Development Time and Resources: Estimating the time and human resources required to develop, test, and deploy the API.
2. Technical Expertise: Assessing whether your team has the necessary expertise or if additional training or hiring is needed.
3. Cost Analysis: Calculating the development and ongoing maintenance costs, including server infrastructure, compared to using third-party APIs.
4. Data Source and Reliability: Identifying reliable data sources if your API is dependent on external data and ensuring consistent data quality and availability.
5. Scalability and Performance: Ensuring the API can handle the expected load and scale as your user base grows.

Decision Point: Given these considerations, would you proceed with developing your own API, continue exploring the alternative third-party API, or pursue another strategy? Please detail your approach and the reasoning behind your decision.

Has the current API provider told me how long it will take to fix the error?

In this scenario, let's assume that the current third-party API provider has communicated that they are actively working on resolving the issue, but they have not provided a definitive timeline for the fix. They've indicated it could be a matter of days or possibly weeks due to the complexity of the problem.

Decision Point: With this uncertainty regarding the timeline for a resolution from the current API provider, how would you plan your next steps? Please consider the options available and explain your decision-making process.

With caching and graceful-degradation in place, how serious is the situation business-wise?

With the implementation of caching and graceful degradation, the immediate business impact of the issue has been significantly mitigated. The frequency of errors that users encounter has reduced, leading to a more stable user experience. This has likely resulted in a decrease in user complaints and a less urgent need for a rapid solution.

However, there are still considerations:

1. Long-term Reliability: Relying on caching and graceful degradation is a temporary fix. The long-term reliability of the application still depends on the stability of the third-party API or finding a more reliable alternative.
2. User Trust and Satisfaction: While the immediate issue is lessened, there's a potential long-term risk to user trust and satisfaction if issues persist or if data freshness is compromised.
3. Business Growth and Scalability: Future growth and scalability could be affected if the API issues aren't fully resolved or if a more reliable solution isn't implemented.

Decision Point: Given this business context, how would you prioritize your next actions in resolving the API issue? Would you focus on expediting an alternative solution, wait for the current API provider to resolve the issue, or take a different approach? Please describe your decision and the reasoning behind it.

Is what the API does relevant enough to our core business that it makes sense for us to implement the API ourselves?

In this scenario, evaluating the relevance of the API's functionality to your core business is crucial. Let's consider that the API provides data or services that are integral to the user experience and overall functionality of your application, but it's not directly related to your primary business operations or unique value proposition.

Decision Point: Given this context, where the API is important but not central to your core business, how would you decide between implementing the API in-house, waiting for the current provider to resolve the issue, or fully integrating an alternative third-party API? Consider factors like resource allocation, expertise, cost, and the potential impact on your core business operations. Please explain your decision-making process.