SRE classroom: How to design a reliable application in three hours (sponsored by Google)
Who is this presentation for?
- Site reliability engineers, engineering managers, and technical program managers
Goals and expectations
- We have a problem. Let’s solve it with software
- The initial problem statement
- The service-level objective (SLO)
- Terminology and concepts
- Hardware (memory, processor)
- Software (libraries, invariants)
- Hardware (data center, network)
- Software (algorithms, failures)
- What is distributed consensus? Why is it important?
- Hands-on exercise: Identify the components necessary to build a working system in a single location and produce a sketch of this working system (UML not required)
The solution has limitations: Let’s improve it
- We have identified single points of failure…because things failed. The system failed. And we lost users.
- Let’s replicate this thing.
- What parts are useful to duplicate? Replicate? How do we arrange this so that we make the computers do all the work?
- How do we know that these systems are doing what we expect?
- We have performance bottlenecks
- How do we identify bottlenecks?
- Conversely, how do we know that we have removed these bottlenecks?
- How can we apply these concepts to a real piece of software?
- What limitations does this introduce?
- Hands-on exercise: Identify which components can usefully run in multiple locations; evaluate how to write an SLO (and how to apply it) and produce a system that runs in multiple data centers
Discussion and conclusions
- Present an example solution
- Discuss commonly encountered limitations
- What key points have we learned?
- How does it apply beyond this workshop?
- Assessing and evaluating third-party (i.e., cloud) systems integrating these into your design
- Hands-on exercises
For each exercise, you’ll work in small groups to apply the concepts to the problem. As Jesus Climent discusses additional aspects of distributed-systems design, you’ll apply these concepts to your in-progress solutions.
This tutorial is sponsored by Google.
Prerequisite knowledgeSuggested readings:
- Service Level Objectives
- Load Balancing at the Frontend
- Load Balancing in the Datacenter
- Managing Critical State: Distributed Consensus for Reliability
- Data Integrity: What You Read Is What You Wrote
Distributed systems in production environments
- The Google File System
- The Chubby Lock Service for Loosely-Coupled Distributed Systems
- Familiarity with order-of-magnitude comparisons
What you'll learn
- Learn how to evaluate distributed systems using techniques of quantitative analysis, incrementally improve a system, identify single points of failure in a large software system, make required resource estimations to create a bill of materials
- See how a SLO fits into system design, will be able to incrementally improve a system
System Administrator and Architecture Engineer during his 8 year tenure at Nokia. He is now Sr. SRE at Google, where he has been working since 2008, as a member of Google’s CRE team, helping companies meet their reliability requirements.
Akshay is a Senior SRE on Cloud Bigtable, Google’s petabyte-scale NoSQL database. Before this, he’s worked as an engineer on Google Search and as an options trader at JPMorgan. He enjoys learning new things and scaling himself sub-linearly.
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