SRE Interview Prep Plan (Week 3)

• Week 1: Fundamentals of SRE

• Week 2: Automation & Scripting

• Week 3: Monitoring, Logging, and Alerting (This post)

• Week 4: Incident Management Lifecycle

• Week 5: Scalability, Performance, & System Design

• Week 6: Mock Interviews and Revision

Welcome back to our six-week journey to prepare for your Site Reliability Engineering (SRE) interview! By now, you've covered the fundamentals of SRE in Week 1 and grasped automation and scripting in Week 2. If you've been following along, you're well on your way to covering all the essential skills required for a successful SRE career.

This week, we're taking another significant step forward as we get into the critical stack of monitoring and alerting. Now, it's time to equip yourself with the knowledge and tools needed to keep an eye on systems, analyze performance, and respond quickly to any issues that may come up.

Monitoring and alerting are at the core of Site Reliability Engineering. They enable you to maintain the reliability and availability of complex systems, and Week 3 is all about cracking these concepts. Throughout this week, we'll explore the key elements of monitoring, logging, and alerting, and we'll introduce you to powerful tools like Prometheus and Grafana.

Days 1-3: Monitoring, Logging, and Alerting

Monitoring, logging, and alerting are the backbone of Site Reliability Engineering (SRE) because they provide real-time visibility into system performance, identify potential issues, and enable quick response to incidents. Monitoring helps track system health and performance metrics, while logging captures essential data for troubleshooting and forensic analysis. Alerts act as early warning systems, ensuring that problems are addressed proactively, minimizing downtime, and enhancing the overall reliability of digital services.

Monitoring is the continuous process of observing and collecting data about the performance, behavior, and health of computer systems, networks, applications, or other components of an IT infrastructure. This data is used to assess the state of these systems, identify potential issues, and ensure they operate optimally. Monitoring can involve tracking various metrics, logs, and events, allowing for proactive maintenance and timely response to anomalies or failures.

Logging is the practice of recording and storing structured or unstructured data, typically in the form of textual messages or events, generated by computer systems, applications, or services. These logs capture valuable information about the execution, behavior, and events within a software system. Logging is crucial for troubleshooting, debugging, auditing, and analyzing the performance and security of applications and systems.

Alerting is a system or process of issuing notifications or warnings in response to predefined conditions, events, or thresholds being met or exceeded within a computer system, application, or network. These alerts are designed to draw immediate attention to potential issues or anomalies, allowing system administrators, operators, or relevant personnel to take timely corrective actions. Alerting systems are crucial for maintaining the reliability and availability of IT infrastructure, as they enable rapid response to problems and help prevent service disruptions.

Resources:

• Monitoring Distributed System

• Practical Alerting

• Monitoring (The Site Reliability Workbook)

• Alerting On Slos

• Set up monitoring, alerting, & logging

• Monitoring production services at Amazon

• Observability Engineering: Achieving Production Excellence (Book)

Questions:

1. What is the difference between monitoring and logging? How do they complement each other in an SRE context?

2. Explain the importance of setting up effective alerting thresholds. What factors should you consider when defining these thresholds?

3. Can you describe the key metrics that should be monitored for a web application to ensure its reliability and performance?

4. What is the purpose of centralized logging, and how does it benefit an SRE team in incident response and troubleshooting?

5. What are some common challenges in managing log data at scale, and how can they be addressed?

6. How do you handle alert fatigue in an SRE environment, and what strategies can be used to reduce unnecessary alerts?

7. Can you explain the concept of "observability" and its significance in SRE practices? How does it relate to monitoring and alerting?

8. Describe the process of setting up automated alerts for a critical service. What considerations should be made to avoid false positives or negatives?

9. What are some best practices for designing effective dashboards in monitoring and alerting tools? How can they improve incident response?

10. How would you approach post-incident analysis using log data and alerting information to identify the root cause of a system outage or performance degradation?

Days 4-5: Exploring Observability Stacks

We'll introduce you to some of the key observability stacks and tools that SRE professionals rely on to gain deep insights into system performance and behavior. These stacks typically encompass a combination of monitoring, logging, tracing, and visualization tools.

Some of the most used observability stacks:

1. Prometheus, Alertmanager and Grafana: Widely used for monitoring, alerting, and visualization, these tools provide robust metrics collection, reliable alerting, and customizable dashboards.

2. ELK Stack (Elasticsearch, Logstash, Kibana): Ideal for log collection, storage, and analysis, the ELK Stack is a popular choice for log management.

3. Jaeger and Zipkin: Distributed tracing tools that help you understand the flow of requests across microservices in complex architectures.

4. OpenTelemetry: A set of APIs, libraries, agents, and instrumentation to provide observability across multiple languages and platforms.

5. Datadog: Datadog is a cloud-based observability platform that allows organizations to monitor the performance of their applications, infrastructure, and services. It offers real-time monitoring and alerting, log management, distributed tracing, and APM (Application Performance Monitoring). Datadog is known for its user-friendly interface, extensive integrations, and the ability to provide end-to-end visibility into complex systems.

6. Honeycomb and New Relic: Platforms that offer rich insights into application performance and behavior through tracing and other observability data.

Resources:

• What is ELK stack?

• Prometheus Docs

• Alertmanager Docs

• Complete Guide to ELK Stack

• Prometheus Up & Runing (Book)

• Distributed Tracing In Practice (Book)

Questions:

1. Could you describe the role of Prometheus and Grafana in an observability stack? How do they contribute to monitoring and visualization?

2. Can you explain cardinality of metrics and how it affects prometheus?

3. What are the advantages/disadvantages of using the ELK Stack (Elasticsearch, Logstash, Kibana) for log management in an observability context?

4. How do distributed tracing tools like Jaeger and Zipkin help in understanding the behavior of microservices within a complex architecture?

5. What is OpenTelemetry, and how does it enhance observability across various languages and platforms?

6. Can you discuss the benefits of using Datadog in an observability stack? How does it provide end-to-end visibility into system performance?

7. How do observability stacks aid in incident response and troubleshooting? Could you provide an example of a real-world scenario where observability tools proved invaluable?

Days 6-7: Setting up O11Y for a mock infrastructure.

The importance of hands-on experience cannot be overstated. As an SRE, you'll be tasked with ensuring the reliability and availability of real-world systems, and this exercise will prepare you for the challenges that lie ahead.

These 2 days are about your ability to set up an observability stack for a mock infrastructure. It will rarely be done on a practical real infrastructure, so it will be discussed like a non-abstract large system.

We would advice you to practice building an observability stack and getting familiar with all the of its components.

For example the resources below will help you set up an observability stack on top of kubernetes.

Resources:

• ELK on Kubernetes

• Prometheus Operator

• Jaeger Operator

• Cortex Kubernetes

Questions:

Questions might be deep dives into specific components to discuss things like scale, privacy, resiliency, etc...

1. What are component(s) of prometheus that stop it from scaling linearly with services/data? How can we get around these obstacles?

2. What are the methods of delivering alerts by alertmanager? can any of them be used for remediation/automation?

3. Where does distributed tracing data gets stored?

4. Can you explain the roles of Thanos vs Cortex? and how they help prometheus stack scale?

5. Can you whiteboard a simple observability stack for a microservices architecture?

6. How can you reduce ELK stack cost?

7. What are exemplars? and where they fit in the o11y stack?

8. How can you implement load shedding for your monitoring, logging, alerting, and distributed tracing stack?

Now that we've covered essential concepts in monitoring, logging, alerting, and observability stacks. You've gained insights into the fundamental tools and practices that underlies the reliability and performance of software systems.

This practical exercise will empower you to apply what you've learned, ensuring you're well-prepared for the challenges and opportunities that lie ahead in the world of Site Reliability Engineering.

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On week 4, we will target an important role that SRE plays: Incident Management and troubleshooting. Building upon the strong foundation you've established in the preceding weeks, we'll look into strategies, best practices, and tools used by SREs to efficiently detect, respond to, and mitigate incidents. This critical aspect of SRE ensures that systems remain resilient and available even in the face of unexpected challenges.