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Site Reliability Engineering (SRE): Error Budgets and SLOs

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SRE: Reliability as a Feature

SRE is what happens when you ask a software engineer to design an operations team. It is the discipline of treating operations as a Software Problem.

1. SLI vs SLO vs SLA

  • SLI (Indicator): What we measure (e.g., Latency).
  • SLO (Objective): Our target (e.g., "99.9% of requests < 100ms").
  • SLA (Agreement): The legal contract with the user (e.g., "If we miss our SLO, we refund your money").

2. The Error Budget

If your SLO is 99.9%, you have 0.1% of "Permitted Failure" per month. This is your **Error Budget**. - If you have budget left: You can deploy risky new features. - If you are out of budget: You must STOP all new features and focus 100% on reliability until the budget refills.

4. Interview Mastery

Q: "How do you handle 'On-call' fatigue in SRE?"

Architect Answer: "We use **Toil Reduction**. Toil is manual, repetitive work (e.g., restarting a crashed server). If an engineer spends >50% of their time on toil, they aren't 'Engineering.' We use automation to handle routine failures and ensure that every on-call alert is 'Actionable.' If an alert doesn't require immediate human intervention, it shouldn't wake someone up at 3 AM."

DevOps & Cloud Architect Mastery
Course syllabus
1. Containerization with Docker Docker Internals: Namespaces, Cgroups, and UnionFS Optimizing Dockerfiles: Multi-stage builds and layer caching Docker Compose: Managing multi-container localized environments Security in Containers: Rootless mode and Image scanning
2. Orchestration with Kubernetes (K8s) K8s Architecture: Control Plane, Nodes, and Kubelet Pods, Deployments, and Services: The core building blocks Ingress Controllers & Service Mesh (Istio) integration Helm Charts: Package management for Kubernetes
3. CI/CD Pipelines GitHub Actions: Automating build, test, and deploy Jenkins Architecture: Master-Agent distributed builds Deployment Strategies: Blue-Green vs Canary vs Rolling The 'Shift Left' Philosophy: Integrating security and testing early
4. Infrastructure as Code (IaC) Terraform: Declarative infrastructure on any cloud Terraform State Management: S3 backends and State locks Ansible: Configuration management vs Infrastructure provision Pulumi: IaC using real programming languages (TS, Python)
5. Cloud Platforms Deep Dive (Azure/AWS) Virtual Networks (VPC): Subnets, Gateways, and Peering Identity & Access Management (IAM): The principle of least privilege Cloud Databases: Managed SQL vs Cosmos DB vs DynamoDB Cost Optimization: Savings Plans, Spot Instances, and FinOps
6. Serverless & Scaling AWS Lambda / Azure Functions: Event-driven scaling API Gateways: Exposing serverless functions securely Cold Starts: Understanding and mitigating latency Serverless Orchestration: Step Functions and Logic Apps
7. Security & Reliability (DevSecOps) Secrets Management: Azure Key Vault vs HashiCorp Vault Compliance as Code: Policy engines (OPA) and Audit logs Site Reliability Engineering (SRE): Error Budgets and SLOs Logs & Metrics: Setting up ELK and Prometheus in the cloud
8. FAANG Cloud Architect Interview Case Study: Migrating a Monolith to Cloud-Native Microservices Case Study: Designing a Global, Multi-Region Cloud Infrastructure
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