1. What is Site Reliability Engineering (SRE)?
So, SRE is like blending software engineering with IT operations. It was originally developed by Google to help manage large systems reliably.Basically, SREs ensure that systems are scalable and available by automating operations, managing incidents, and balancing the fine line between shipping features and keeping systems stable.
2. What is an Error Budget in SRE?
Think of an error budget as a safety net for failure. If your SLO is 99.9% uptime, your error budget is that remaining 0.1% downtime. It helps balance reliability and velocity.If you’re under your error budget, you can take risks like pushing new features. If you’ve burned through it, you focus on stability. It’s like spending time to party but knowing when to get serious.
3. Explain SLIs, SLOs, and SLAs.
Okay, here’s the breakdown: SLIs (Service Level Indicators) are the metrics like latency or uptime.SLOs (Service Level Objectives) are your goals for those metrics, like “99.95% uptime.”
SLAs (Service Level Agreements) are formal agreements with customers that say, “If we don’t hit our SLO, here’s how we’ll make it up to you (like a refund).” Basically, SLIs are what you measure, SLOs are your targets, and SLAs are what you promise.
4. How do you manage incidents in SRE?
It’s firefighting mode! When an incident hits, first you get alerted via monitoring tools like Prometheus, Grafana, or Datadog. Next, you identify the issue, mitigate the impact, and communicate with your team.Once things are stable, you dig deeper to find the root cause. Post-incident, write a blameless postmortem so you can prevent it from happening again — it’s all about learning and improving.
5. What is a blameless postmortem, and why is it important?
A blameless postmortem is like a no-blame breakdown of what went wrong after an incident. It’s important because it focuses on the system failing, not the people.This way, everyone feels safe admitting mistakes, and the focus is on fixing the root causes and improving the process. It helps build a culture of learning, trust, and transparency.
6. What’s the role of monitoring in SRE?
Monitoring is your early warning system. You’re keeping an eye on key metrics like latency, memory, CPU usage, and error rates.Tools like Prometheus, Grafana, and Datadog help visualize these metrics, set alerts, and create dashboards. Monitoring is essential because you need to know when things start to go wrong before users even notice.
7. What is observability in SRE?
Observability is like having a 360-degree view of your system’s health. It goes beyond traditional monitoring by giving you the ability to understand why something went wrong.It’s built on three pillars: logs (events), metrics (measurements), and traces (request flows). Observability helps you ask, “Why is this happening?” and trace the root cause more effectively.
8. What is an SLO, and how do you define it?
An SLO is your goal for a system’s reliability. It’s like saying, “We aim for 99.95% uptime.” You define it based on the service’s needs and user expectations.For example, a banking app might need high availability (like 99.999%), while a personal blog could get by with less. SLOs balance innovation and reliability by giving you a target to hit without obsessing over perfection.
9. How do you scale systems to handle more traffic?
Scaling is like getting more chairs when more guests arrive at a party. You can do it vertically (upgrading a server’s CPU, RAM, etc.) or horizontally (adding more servers or instances).Horizontal scaling with Kubernetes is pretty sweet — you can use Horizontal Pod Autoscaling (HPA) to automatically scale pods based on CPU or memory usage. Load balancers help distribute traffic evenly.
10. How do you manage toil in SRE?
Toil is that repetitive, boring work that doesn’t add long-term value. Think of it like doing laundry — you’ve got to do it, but it’s not really making you any smarter. As an SRE, you want to automate toil away.Write scripts, build tools, or introduce processes to make repetitive tasks disappear. The less toil, the more time you’ve got for high-value tasks, like scaling systems or improving reliability.
11. What is chaos engineering, and why is it important?
Chaos engineering is like breaking stuff on purpose to see how resilient your system is. You introduce controlled failures (like shutting down servers or pods) and see how your system responds.The goal is to uncover weaknesses before they become real problems. Think of it as stress-testing your infrastructure to make sure it can handle unexpected failures.
12. What’s a golden signal in SRE?
Golden signals are like your top-tier vitals in monitoring. There are four key golden signals: latency (response time), traffic (requests per second), errors (failure rate), and saturation (how full your resources are).These metrics give you a high-level overview of your system’s health and help you identify where things might be breaking down.
13. How do you handle on-call duties in SRE?
Being on-call is like being a firefighter on standby. You’ll get alerts when something goes wrong, and you need to respond quickly. Tools like PagerDuty or Opsgenie are common.When you’re on-call, your job is to mitigate the issue first — keep the system running. Once things are under control, dig into the root cause and document what happened so it doesn’t bite you again.
14. What is the role of automation in SRE?
Automation is your best friend in SRE. It helps you eliminate manual, repetitive tasks (toil) and makes your systems more reliable and scalable.Whether it’s automating deployments, setting up self-healing systems, or automating incident response, the goal is to do more with less manual intervention. Automation is what allows SREs to focus on solving bigger problems instead of putting out fires all day.
15. How do you manage configurations in SRE?
Managing configuration is like organizing a closet — you want things where they belong, whether it’s sensitive info like secrets or just environment variables.In Kubernetes, you’ve got ConfigMaps for non-sensitive data and Secrets for sensitive stuff. The key is to keep configurations separate from code, so you can change things like environment settings without having to redeploy.
16. How do you set up alerting thresholds in SRE?
Setting up alerting thresholds is a balance — you don’t want too many false alarms, but you also don’t want to miss critical issues. Start by identifying your key metrics (like CPU, latency, and error rates).Then, set your alert to trigger when the metric exceeds a certain value over a specific time window. And remember, you can use multi-step alerts (warn first, then critical) to prevent alert fatigue.
17. What are some common metrics you monitor in SRE?
Some of the go-to metrics include CPU usage, memory usage, disk I/O, network traffic, and error rates. But it depends on the service. For web apps, you’d also monitor request latency, throughput, and database query times. The idea is to keep track of anything that can affect your system’s performance or reliability.18. How do you handle performance bottlenecks in a system?
First, you need to identify where the bottleneck is — could be CPU, memory, network, or storage. Use monitoring tools like Grafana, Prometheus, or Datadog to pinpoint the issue.Once you’ve found it, you can either optimize code (like database queries), scale up the infrastructure, or cache frequently accessed data. If all else fails, throw in more hardware or optimize your scaling strategies.
19. What’s the difference between vertical and horizontal scaling?
Vertical scaling is like upgrading a single machine — adding more CPU, RAM, or storage. It’s simple but has limits (you can’t upgrade forever). Horizontal scaling is like adding more machines or instances.It’s more flexible because you can keep adding instances as demand grows. Kubernetes makes horizontal scaling easier with things like autoscaling pods.
20. What is load balancing, and why is it important?
Load balancing is like distributing the weight of tasks so no single machine gets overwhelmed. It ensures that traffic is spread evenly across multiple servers or instances, preventing overloads and improving availability.With a load balancer in place, you also get failover, so if one instance goes down, the traffic is redirected to the healthy ones, keeping your system running smoothly.
21. What’s the purpose of a Service Level Agreement (SLA)?
An SLA is like a contract between a service provider and its customers. It lays out the expectations for service availability and performance (like 99.9% uptime).If the provider doesn’t meet those expectations, there are penalties, like refunds or service credits. It keeps everyone on the same page regarding what “good” service looks like.
22. How do you optimize database performance in SRE?
To optimize databases, you can index your tables, cache frequently used queries, and make sure your queries are optimized (avoid SELECT * when you don’t need it).You can also shard your database (splitting data across multiple servers) or use replication to balance read and write loads. Monitoring query performance is key — tools like EXPLAIN in SQL can help you optimize those long-running queries.
23. How do you manage failures in a distributed system?
Failures in a distributed system are inevitable, so the goal is to handle them gracefully. Use retries with exponential backoff, implement circuit breakers, and set timeouts to avoid cascading failures.Monitoring and alerting are crucial so you can react quickly. And don’t forget about redundancy — spread your system across multiple availability zones or regions to avoid single points of failure.
24. What is a circuit breaker pattern in SRE?
The circuit breaker pattern is like a fuse for your system. If one part of your system is struggling (e.g., a service keeps failing), the circuit breaker “trips” and prevents further requests from reaching that service.This stops the whole system from going down due to a single failing component. Once the failing service recovers, the circuit breaker allows traffic to flow again.
25. How do you ensure high availability in a cloud-native environment?
High availability is all about making sure your system stays up, even when things go wrong.You can spread resources across multiple availability zones or regions, implement automatic failover for critical components, and use load balancers to distribute traffic. Scaling policies (autoscaling) and redundancy are key parts of maintaining high availability in the cloud.
26. What’s the difference between active-active and active-passive failover?
Active-active failover means that all instances are running and sharing the load, so if one fails, the others can pick up the slack.Active-passive failover means one instance is actively handling traffic while the other is on standby, ready to take over if the active one fails. Active-active provides more resilience, but active-passive can be easier to manage.
27. How do you handle large-scale migrations in SRE?
Migrations are like moving to a new house — lots of planning, testing, and coordination.You’ll want to break it into phases: plan the migration, test it in a staging environment, and gradually roll it out. During the migration, you monitor for issues and have a rollback plan if things go south. Tools like Kubernetes and Terraform can help automate parts of the process.
28. What is blue-green deployment?
Blue-green deployment is like having two versions of your environment — blue (current) and green (new). You deploy the new version to the green environment, and once it’s stable, you switch traffic from blue to green.If something breaks, you can quickly roll back by switching traffic back to blue. It’s a great way to minimize downtime and reduce deployment risks.
29. How do you perform rolling updates in Kubernetes?
Rolling updates are like swapping out parts of your system without taking the whole thing down. In Kubernetes, you update your deployment with the new version, and Kubernetes gradually replaces the old pods with new ones. If something goes wrong, Kubernetes can roll back to the previous version. It’s all about making updates without causing outages.30. What’s the role of Kubernetes in SRE?
Kubernetes is like the Swiss army knife of orchestration tools. It automates deploying, scaling, and managing containerized applications.For SREs, it’s a game-changer because it simplifies a lot of the heavy lifting around infrastructure management — like scaling pods, load balancing, and self-healing. Plus, it makes it easier to deploy updates without downtime (rolling updates).
31. How do you troubleshoot pod failures in Kubernetes?
Pod failures can be tricky, but you start by running kubectl describe pod <pod-name> to see what’s happening. You’ll get details about events, statuses, and conditions.If that doesn’t help, check the logs with kubectl logs <pod-name>. And if you need to poke around inside the pod, you can use kubectl exec -it <pod-name> -- /bin/sh to open a shell and inspect things manually.
32. What’s a Service in Kubernetes?
A Service in Kubernetes is like a traffic director for your pods. It provides a stable IP and DNS name, even if your pods come and go.There are different types of Services: ClusterIP (for internal traffic), NodePort (exposes your service externally on a specific port), and LoadBalancer (used in cloud environments to route external traffic). It abstracts away pod IPs so you don’t have to worry about tracking them.
33. How do you manage networking in Kubernetes?
Networking in Kubernetes can get wild. Each pod has its own IP, and CNI (Container Network Interface) plugins like Calico or Flannel manage how they communicate.Then you have Services to handle traffic between pods and external users. For external access, you can use NodePort or LoadBalancer. Network Policies help you control traffic between pods, enforcing security rules like, “Who can talk to who?”
34. What’s the difference between synchronous and asynchronous replication?
Synchronous replication means data is written to both the primary and replica at the same time, ensuring strong consistency but at the cost of speed.Asynchronous replication means data is written to the primary first, and the replica catches up later. It’s faster but can lead to data loss if the primary goes down before the replica has synced.
35. What is Infrastructure as Code (IaC), and why is it important?
Infrastructure as Code (IaC) is like writing scripts to manage your infrastructure, rather than doing it manually. Tools like Terraform and Ansible allow you to define infrastructure in code, version it, and automate its deployment.This makes infrastructure management more consistent, scalable, and less prone to human error. Plus, you can treat your infrastructure like any other part of your codebase — test it, review it, and track changes.
36. How do you implement security best practices in SRE?
Security in SRE is like locking down the fort. Start with Role-Based Access Control (RBAC) to ensure only the right people have access to sensitive resources.Use network policies to control which services can communicate. Encrypt data at rest and in transit, and make sure to rotate secrets regularly. And don’t forget about auditing — track who’s doing what in your system to detect any suspicious activity.
37. What’s the role of Prometheus in monitoring?
Prometheus is like the go-to tool for monitoring and alerting in cloud-native environments. It scrapes metrics from your services, stores them in a time-series database, and can trigger alerts based on predefined conditions.It’s widely used because it integrates well with Kubernetes and provides powerful query capabilities using PromQL. You can visualize the data using Grafana for even more insights.
38. How do you scale databases in a cloud environment?
Scaling databases in the cloud can be tricky, but you’ve got a few options. Vertical scaling means upgrading the instance size, but that has limits.Horizontal scaling involves techniques like sharding (splitting data across multiple databases) or replication (keeping multiple copies of the data). Using managed database services like Amazon RDS or Google Cloud SQL simplifies the process with built-in autoscaling.
39. What is a microservice architecture?
A microservice architecture is like breaking a big monolithic application into smaller, independent services that communicate over APIs. Each microservice handles a specific function (like user authentication, payments, etc.). It’s great for scalability and flexibility, but it comes with challenges around networking, monitoring, and coordinating between services.40. How do you ensure data consistency in distributed systems?
Data consistency in distributed systems is like making sure all copies of your data stay in sync. Techniques like distributed transactions (two-phase commit), eventual consistency (data syncs eventually), and strong consistency (all nodes agree on the same data) help.Tools like Apache Kafka or databases like Cassandra handle replication and consistency across distributed systems.
41. How do you ensure compliance with Service Level Agreements (SLAs)?
First, define your SLOs based on the SLA commitments. Then, monitor your system’s performance against those SLOs with metrics like uptime, latency, and error rates.If you’re getting close to breaching your error budget (the gap between your SLO and SLA), slow down feature releases and focus on improving reliability. Document and communicate with stakeholders to manage expectations.
42. What is a CDN, and how does it help with scaling?
A Content Delivery Network (CDN) is like a network of servers that deliver content to users based on their geographic location. It helps reduce latency and improves load times by caching content closer to the user.CDNs are commonly used for static assets like images, CSS, and JavaScript files. Tools like Cloudflare or AWS CloudFront help scale web applications globally.
43. What’s the role of distributed tracing in observability?
Distributed tracing is like having a map of how a request flows through a system. It tracks the journey of a request as it moves between microservices, showing you where delays or errors occur.Tools like Jaeger and OpenTelemetry help with distributed tracing. It’s especially useful in microservices environments where it’s hard to pinpoint where a request is bottlenecking.
44. How do you design for zero-downtime deployments?
Zero-downtime deployments are like changing the tires on a moving car — the goal is to avoid any noticeable downtime for users. Techniques like rolling updates (gradually updating instances), blue-green deployments (switching traffic between environments), and canary releases (rolling out to a small subset of users first) help. Automation tools like Kubernetes make this easier by handling the traffic routing and scaling.45. What’s the difference between logs, metrics, and traces?
Logs are like detailed event records that tell you what happened and when (useful for debugging). Metrics are numerical data that give you an overview of system health (like CPU usage or error rates).Traces show how a request flows through the system, letting you see where bottlenecks occur. Together, these three pillars of observability give you full insight into what’s going on in your system.
46. How do you perform capacity planning?
Capacity planning is like making
sure you’ve got enough chairs for everyone at the party. You look at current
usage (CPU, memory, network) and predict future demand based on traffic
patterns and growth trends.
Tools like Prometheus or AWS
CloudWatch can help you analyze trends. The goal is to ensure you don’t run out
of resources or over-provision, which can get expensive.
47. What’s the role of Terraform in Infrastructure as Code (IaC)?
Terraform is like a magic wand for
automating infrastructure. It allows you to define infrastructure (servers,
databases, networking) in code, then deploy that infrastructure consistently
across environments (like dev, staging, and prod).
With Terraform, you can version
your infrastructure, manage it through code reviews, and ensure consistent
configurations across environments. Plus, it works with all major cloud
providers.
48. What is a Runbook in SRE?
A runbook is like a step-by-step
guide for handling incidents or performing operational tasks. It provides
instructions on what to do when something goes wrong, so you’re not scrambling
for answers.
Runbooks are essential for on-call
engineers because they help standardize how incidents are resolved. Think of it
as your SRE survival guide for common issues.
49. What’s the difference between uptime and availability?
Uptime is the total amount of time your system is up and running, while availability refers to how often your system is available for use. They sound similar, but availability takes into account both planned and unplanned downtime.For example, your system could have high uptime but low availability if there’s frequent planned downtime for maintenance.
50. How do you reduce latency in distributed systems?
Reducing latency is all about
minimizing delays. Caching frequently accessed data, optimizing database
queries, and reducing the number of hops between services are good starting
points.
You can also use CDNs to bring
static content closer to users and minimize the distance that data has to
travel. For microservices, batching requests or using asynchronous
communication can help.
