You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting. What should you do?
Correct Answer: D
Explanation https://cloud.google.com/error-reporting/docs/formatting-error-messages https://cloud.google.com/error-reporting/docs/reference/libraries#client-libraries-install-python no need to install error reporting library on App Engine Flex.
Question 72
Your Cloud Run application writes unstructured logs as text strings to Cloud Logging. You want to convert the unstructured logs to JSON-based structured logs. What should you do?
Correct Answer: D
The correct answer is D, Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPayload field. Cloud Logging SDKs are libraries that allow you to write structured logs from your Cloud Run application. You can use the SDKs to create log entries with a jsonPayload field, which contains a JSON object with the properties of your log entry. The jsonPayload field allows you to use advanced features of Cloud Logging, such as filtering, querying, and exporting logs based on the properties of your log entry1. To use Cloud Logging SDKs, you need to install the SDK for your programming language, and then use the SDK methods to create and send log entries to Cloud Logging. For example, if you are using Node.js, you can use the following code to write a structured log entry with a jsonPayload field2: // Imports the Google Cloud client library const {Logging} = require('@google-cloud/logging'); // Creates a client const logging = new Logging(); // Selects the log to write to const log = logging.log('my-log'); // The data to write to the log const text = 'Hello, world!'; const metadata = { // Set the Cloud Run service name and revision as labels labels: { service_name: process.env.K_SERVICE || 'unknown', revision_name: process.env.K_REVISION || 'unknown', }, // Set the log entry payload type and value jsonPayload: { message: text, timestamp: new Date(), }, }; // Prepares a log entry const entry = log.entry(metadata); // Writes the log entry await log.write(entry); console.log(`Logged: ${text}`); Using Cloud Logging SDKs is the best way to convert unstructured logs to structured logs, as it provides more flexibility and control over the format and content of your log entries. Using a Fluent Bit sidecar container is not a good option, as it adds complexity and overhead to your Cloud Run application. Fluent Bit is a lightweight log processor and forwarder that can be used to collect and parse logs from various sources and send them to different destinations3. However, Cloud Run does not support sidecar containers, so you would need to run Fluent Bit as part of your main container image. This would require modifying your Dockerfile and configuring Fluent Bit to read logs from supported locations and parse them as JSON. This is more cumbersome and less reliable than using Cloud Logging SDKs. Using the log agent in the Cloud Run container image is not possible, as the log agent is not supported on Cloud Run. The log agent is a service that runs on Compute Engine or Google Kubernetes Engine instances and collects logs from various applications and system components. However, Cloud Run does not allow you to install or run any agents on its underlying infrastructure, as it is a fully managed service that abstracts away the details of the underlying platform. Storing the password directly in the code is not a good practice, as it exposes sensitive information and makes it hard to change or rotate the password. It also requires rebuilding and redeploying the application each time the password changes, which adds unnecessary work and downtime. Reference: 1: Writing structured logs | Cloud Run Documentation | Google Cloud 2: Write structured logs | Cloud Run Documentation | Google Cloud 3: Fluent Bit - Fast and Lightweight Log Processor & Forwarder 4: Logging Best Practices for Serverless Applications - Google Codelabs 5: About the logging agent | Cloud Logging Documentation | Google Cloud 6: Cloud Run FAQ | Google Cloud
Question 73
You support a production service that runs on a single Compute Engine instance. You regularly need to spend time on recreating the service by deleting the crashing instance and creating a new instance based on the relevant image. You want to reduce the time spent performing manual operations while following Site Reliability Engineering principles. What should you do?
Correct Answer: C
Question 74
Your organization has a containerized web application that runs on-premises As part of the migration plan to Google Cloud you need to select a deployment strategy and platform that meets the following acceptance criteria 1 The platform must be able to direct traffic from Android devices to an Android-specific microservice 2 The platform must allow for arbitrary percentage-based traffic splitting 3 The deployment strategy must allow for continuous testing of multiple versions of any microservice What should you do?
Correct Answer: D
The best option for deploying a containerized web application to Google Cloud with the given acceptance criteria is to use Google Kubernetes Engine (GKE) with Anthos Service Mesh. GKE is a managed service for running Kubernetes clusters on Google Cloud, and Anthos Service Mesh is a service mesh that provides observability, traffic management, and security features for microservices. With Anthos Service Mesh, you can use traffic splitting to direct traffic from Android devices to an Android-specific microservice by configuring the user-agent header in the virtual service. You can also use traffic splitting to direct arbitrary percentage-based traffic to different versions of any microservice for continuous testing. For example, you can use a canary release strategy to direct 10% of user traffic to a new version of a microservice and monitor its performance and reliability.
Question 75
You need to define SLOs for a high-traffic web application. Customers are currently happy with the application performance and availability. Based on current measurement, the 90th percentile Of latency is 160 ms and the 95th percentile of latency is 300 ms over a 28-day window. What latency SLO should you publish?
Correct Answer: B
a latency SLO is a service level objective that specifies a target level of responsiveness for a web application1. A latency SLO can be expressed as a percentile of latency over a time window, such as the 90th percentile of latency over 28 days2. A percentile of latency is the maximum amount of time that a given percentage of requests take to complete. For example, the 90th percentile of latency is the maximum amount of time that 90% of requests take to complete3. To define a latency SLO, you need to consider the following factors24: The expectations and satisfaction of your customers. You want to set a latency SLO that reflects the level of performance that your customers are happy with and willing to pay for. The current and historical measurements of your latency. You want to set a latency SLO that is based on data and realistic for your web application. The trade-offs and costs of improving your latency. You want to set a latency SLO that balances the benefits of faster response times with the costs of engineering work, infrastructure, and complexity. Based on these factors, the best option for defining a latency SLO for your web application is option B. Option B sets the latency SLO to match the current measurement of your latency, which means that you are meeting the expectations and satisfaction of your customers. Option B also sets a realistic and achievable target for your web application, which means that you do not need to invest extra resources or effort to improve your latency. Option B also aligns with the best practice of setting conservative SLOs, which means that you have some buffer or margin for error in case your latency fluctuates or degrades5.
