There are no as such specific pre-requisites but IT experience/Operations experience/DevOps knowledge is recommended

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Introduction

• The Sysadmin Approach to Service Management
• Google’s Approach to Service Management: Site Reliability Engineering
• Tenets of SRE
• Demand Forecasting and Capacity Planning
• Efficiency and Performance

The Production Environment at Google, from the Viewpoint of an SRE

• Hardware
• System Software That “Organizes” the Hardware
• Storage
• Networking
• Monitoring and Alerting

Principles

• Embracing Risk
• Managing Risk
• Motivation for Error Budgets
• Benefits

Service Level Objectives

• Service Level Terminology
• Indicators in Practice
• What Do You and Your Users Care About?
• Agreements in Practice

Eliminating Toil

Monitoring Distributed Systems

• Why Monitor?
• Setting Reasonable Expectations for Monitoring
• Symptoms Versus Causes
• Black-Box Versus White-Box
• As Simple as Possible, No Simpler
• Bigtable SRE: A Tale of Over-Alerting
• Gmail: Predictable, Scriptable Responses from Humans

The Evolution of Automation at Google

• The Value of Automation
• A Platform
• Faster Repairs
• Faster Action
• Automate Yourself Out of a Job: Automate ALL the Things!
• Resolving Inconsistencies Idempotently
• Borg: Birth of the Warehouse-Scale Computer

Release Engineering

• The Role of a Release Engineer
• Philosophy
• Self-Service Model
• Testing
• Packaging
• Configuration Management

Simplicity

• System Stability Versus Agility
• The Virtue of Boring
• Minimal APIs
• Modularity
• Release Simplicity

Practical Alerting from Time-Series Data

• Instrumentation of Applications
• Collection of Exported Data
• Storage in the Time-Series Arena
• Labels and Vectors
• Alerting

Being On-Call

• Life of an On-Call Engineer
• Balanced On-Call
• Balance in Quantity
• Balance in Quality

Effective Troubleshooting

• Theory
• In Practice
• Problem Report
• Triage

Emergency Response

• What to Do When Systems Break
• Test-Induced Emergency
• Response
• Keep a History of Outages

Managing Incidents

• Unmanaged Incidents
• Poor Communication
• Freelancing
• Live Incident State Document
• Clear, Live Handoff
• A Managed Incident

Postmortem Culture: Learning from Failure

• Google’s Postmortem Philosophy
• Collaborate and Share Knowledge

Tracking Outages

• Escalator
• Outalator
• Aggregation
• Tagging
• Analysis

Testing for Reliability

• Types of Software Testing
• Traditional Tests
• Production Tests
• Testing at Scale

Software Engineering in SRE

• Why Is Software Engineering Within SRE Important?
• Traditional Capacity Planning
• Intent-Based Capacity Planning
• Fostering Software Engineering in SRE

Load Balancing at the Frontend

• Power Isn’t the Answer
• Load Balancing Using DNS
• Load Balancing at the Virtual IP Address

Load Balancing in the Datacenter

• The Ideal Case
• Identifying Bad Tasks: Flow Control and Lame Ducks
• A Simple Approach to Unhealthy Tasks: Flow Control
• A Robust Approach to Unhealthy Tasks: Lame Duck State

Handling Overload

• The Pitfalls of “Queries per Second”
• Per-Customer Limits
• Client-Side Throttling
• Criticality
• Handling Overload Errors
• Deciding to Retry
• Load from Connections

Addressing Cascading Failures

• Causes of Cascading Failures and Designing to Avoid Them
• Server Overload
• Resource Exhaustion
• Service Unavailability
• Preventing Server Overload
• Queue Management
• Planned Changes, Drains, or Turndowns
• Testing for Cascading Failures

Managing Critical State: Distributed Consensus for Reliability

• Motivating the Use of Consensus: Distributed Systems Coordination Failure
• Case Study 1: The Split-Brain Problem
• Case Study 2: Failover Requires Human Intervention
• Case Study 3: Faulty Group-Membership Algorithms
• How Distributed Consensus Works
• Paxos Overview: An Example Protocol
• System Architecture Patterns for Distributed Consensus
• Reliable Replicated State Machines
• Reliable Replicated Datastores and Configuration Stores

Distributed Periodic Scheduling with Cron

• Cron
• Reliability Perspective
• Cron Jobs and Idempotency

Data Processing Pipelines

• Origin of the Pipeline Design Pattern
• Initial Effect of Big Data on the Simple Pipeline Pattern
• Challenges with the Periodic Pipeline Pattern

Data Integrity: What You Read Is What You Wrote

• Data Integrity’s Strict Requirements
• Choosing a Strategy for Superior Data Integrity
• Data Integrity Is the Means; Data Availability Is the Goal
• The 24 Combinations of Data Integrity Failure Modes
• First Layer: Soft Deletion
• Second Layer: Backups and Their Related Recovery Methods
• Overarching Layer: Replication
• Third Layer: Early Detection
• Trust but Verify
• Hope Is Not a Strategy

Reliable Product Launches at Scale

• Launch Coordination Engineering
• The Role of the Launch Coordination Engineer
• Setting Up a Launch Process
• Capacity Planning
• Failure Modes

Accelerating SREs to On-Call and Beyond

• You’ve Hired Your Next SRE(s), Now What?
• Initial Learning Experiences: The Case for Structure Over Chaos
• Learning Paths That Are Cumulative and Orderly

Dealing with Interrupts

• Add your content…o Managing Operational Load
• Factors in Determining How Interrupts Are Handled
• Imperfect Machines
• Cognitive Flow State

Embedding an SRE to Recover from Operational Overload

• Phase 1: Learn the Service and Get Context
• Identify the Largest Sources of Stress
• Identify Kindling
• Phase 2: Sharing Context
• Write a Good Postmortem for the Team
• Sort Fires According to Type
• Phase 3: Driving Change
• Start with the Basics *. Communication and Collaboration in SRE
• Communications: Production Meetings
• Collaboration within SRE
• Team Composition

The Evolving SRE Engagement Model

• SRE Engagement: What, How, and Why
• The PRR Model
• The SRE Engagement Model
• Alternative Support
• Production Readiness Reviews: Simple PRR Model
• Engagement
• Analysis

Lessons Learned from Other Industries

• Meet Our Industry Veterans
• Preparedness and Disaster Testing
• Relentless Organizational Focus on Safety