s.r.e - create ultra-scalable and highly reliable systems

S.R.E. create ultra-scalable and highly

reliable systemsRicardo Amaro

DevOps - https://events.drupal.org/node/13519

Who am I?@Drupal

@ricardoamaro

Portugal

Lisbon

Drupal Community

Family

+8 years Drupal

90’s Linux Adopter

5 years at Acquia

Site Reliability Engineer,Senior Tier2 Ops

https://drup

al.org/user/66

6176

About Acquia Metrics

￮ Acquia Cloud:○ # of Instances (17,200+)○ # of Production Sites (54,000+)○ # API Calls (3,000 + per sec)○ # Of Availability Zones (20+)○ # Of Regions (8)

We will talk aboutA brief summary inspired on Google’s S.R.E. book

￮ What is S.R.E?￮ Tenets of S.R.E.￮ Reliability & Toil￮ Error budget - keeping the Service Level Objective (SLO)￮ Development & Operations￮ Monitoring and Being On-Call￮ Release Engineering￮ Postmortem culture - Learning from failure

What is S.R.E.?

➔ Term crafted by Google in 2003.

➔ When Ben Treynor was hired to run “production” and ended up

“applying software engineering to an operations function”

➔ Motivation: “as a software engineer, how would I want to invest my time to accomplish a set of repetitive tasks?”

Site Reliability Engineering

➔ SRE is taken seriously by major companies

Site Reliability Engineering

Microsoft

Apple

Amazon

SRE’s are engineers that...

➔ Apply the principles of computer science and engineering to

design and develop large, distributed computing systems.

➔ Write software for those systems alongside product developers.

➔ Build all additional pieces those systems need, like backups and

load balancing.

➔ Reuse old solutions for new problems.

Site Reliability Engineering

DevOps & S.R.E.

DevOps is a practice, which was coined around 2008, that encompasses automation of manual tasks, continuous integration and continuous delivery. It applies to a wide audience of companies whereas SRE might be considered a subset of DevOps that possesses additional skill sets.

Source: https://en.wikipedia.org/wiki/Site_reliability_engineering

Tenets of S.R.E.

Tenets of SRE

1. Ensuring a Durable Focus on Engineering2. Pursuing Maximum Change Velocity 3. Monitoring4. Emergency Response5. Change Management6. Demand Forecasting and Capacity Planning7. Provisioning8. Efficiency and Performance

➔ Hire only coders➔ Have Service Level Objectives (SLOs) for your service➔ Measure and report performance against SLOs➔ Use Error Budgets and gate launches on them➔ Have a Common staffing pool for SRE and DEV➔ Excess Ops work overflows to DEV team➔ Cap SRE operational load at 50% and share 5% with the DEV team➔ On-call teams at least 8 or 6 people in rotation, per product➔ Maximum of 2 events per on-call shift➔ Post mortem for every event➔ Post mortems are BLAMELESS and focus on process and technology, not people

How to achieve S.R.E.Treynor’s Action items

IMPORTANT

IMPORTANT

Reliability & Toil

The latest feature or

That the product works?

What is most the important Feature of a product?

How about the “503” feature ?

...most important thing is that the product works!

“Reliability is the most fundamental feature of any product.”Ben Treynor, Google’s VP for 24/7 Operations

The 80’s Waterfall software delivery model

Operations @customer ➔ *Provisioning➔ *Installing➔ *Upgrading➔ *Maintaining➔ *Backups/Restore➔ *Scaling

Source: wikipedia

Then came the web...

● Software as a Service● Platform as a Service● Cloud computing ● ...

➔ Operations overhead not on the customer side➔ Features could now be delivered faster➔ Customer feedback important for product improvements

Product

DevelopmentShip Features

OperationsUsers

Opposite rewarding conflicts

Objectives:➔ Ship new features➔ Launch new products

Objectives:➔ Reliability & Availability➔ Provision & Scale

Dev Ops

The problem: Toil**exhausting labour

➔ Manual➔ Repetitive➔ Automatable➔ Tactical (Unplanned work)

➔ No enduring value➔ O(n) with service growth

(not just “work I don’t like to do.”)

An Old Solution to Toil

Caption goes here

● Scale with bodiesIn the old operations model, you throw people at a reliability problem and keep pushing (sometimes for a year or more) until the problem either goes away or blows up in your face.

Has your business succeeds workload tends to infinity

(x) time

● Cap Ops WorkloadBecause if you are successful and your business grows you need to reduce errors and toil. Put a 50% cap on Ops work and leave most of the SRE team time for writing code and reduce Toil.

(y) c

usto

mer

s/tr

affic

Workload/Toil over time

➔ Keep operational work (i.e., toil) below 50% of each SREs time➔ More than 50% of each SREs time is spent on:

◆ Engineering project work to reduce toil ◆ Add service features - improving reliability, performance,

utilization➔ Improves career planning for the SRE➔ Improves morale on the organization➔ An SRE team can easily devolve into an Ops team if the 50% target

is broken

Why less Toil is Better?S.R.E. - A modern solution

not bad...

S.R.E. - A modern solutionDEV + OPS

➔ This conflict is not inevitable➔ The solution is: Error Budgets!➔ Everyone agrees on an Error Budget (as we will explain next)➔ SRE only prevents releases or Launches if the Error Budget is exceeded.

Dev Ops

error budgetkeeping the SLO

➔ SLO - Service level objective is agreed as a means of measuring the performance of the

Service Provider.

➔ SLA - Service Level Agreement specifies what service is to be provided, how it is

supported, times, locations, costs, performance, and responsibilities of the parties

involved. SLOs are specific measurable characteristics of the SLA such as availability,

throughput, frequency, response time, or quality.

➔ SLI - Service Level Indicator is a measure of the service level provided by a service

provider to a customer. SLIs form the basis of Service Level Objectives (SLOs), which in

turn form the basis of Service Level Agreements (SLAs).

SLO, SLA & SLI Terminology

What is an Error Budget?

The business or the product establishes Service Level Objectives (SLOs) for the system, based on Service Level indicators such as error rate, availability or latency...

Error Budget

Example: A 99.9% availability SLO means that the service can be 0.1% unavailable, which is the error budget.

100% - 99.9% = 0.1%

➔ 100% is the wrong reliability target for basically everything.➔ Set a goal that acknowledges the trade-off and leaves an error budget➔ Error budget can be spent on anything: launching features, etc.➔ Error budget allows for discussion about how phased rollouts and 1%

experiments can maintain tolerable levels of errors.➔ Goal of SRE team isn’t “zero outages” – SRE and product devs are incentive

aligned to spend the error budget to get maximum feature velocity.

➔ Out of Budget? No problems. Do more testing between releases.

How to obtain the Error Budget

➔ This puts an incentive to developers that drives them to value stability (not just change)

➔ And gives control that drives SREs to permit change (not just stability)

➔ It forces decisions based on metrics, not politics- nor feelings, just data

Error Budget A Self-regulating mechanism

Development & Operations

➔ Development and SRE teams share a

single staffing pool◆ If all is Reliable Devs are

rewarded with teammates

◆ If Ops is overloaded, SREs are

contracted to support code

How are Development & Operations teams organized?

Now tell me… Why should I hire you?

Systems, code… Are you able to cook also?

➔ SREs are developer/sys-admin

hybrids

◆ They perform more Dev work as

things become stable

Development & Operations

Systems, code… Are you able to cook also?

➔ SRE can only spend up to 50% of their

time on ops work

➔ If operational load exceeds 50%, the ops

work overflows to Dev

➔ Allow SRE to move to other projects

Highly motivated and effective teamwork

Monitoring and Being On-Call

➔ Three valid kinds of monitoring output◆ Alerts: human needs to take action immediately

● If you get a huge volume of critical email alerts disable them and stick with paging

◆ Tickets: human needs to take action eventually● On-call engineers can actually accomplish work when they aren’t being kept

up by pages at all hours. Ultimately, temporarily backing off on our alerts will allow you to make faster progress toward a better service

◆ Logging: no action needed

Monitoring and taking action

➔ Maximum of 2 events per 8–12hour on-call shift➔ Handle the event accurately and quickly, clean up and restore

normal service➔ Conducting postmortems➔ If more than 2 events occur regularly per on-call shift,

problems can’t be investigated➔ Pager fatigue also won’t improve with scale➔ If they receive fewer than one event per shift, keeping them

on point is a waste of their time

Being On-Call

➔ Monitoring should never require a human to interpret any part of the alerting domain

➔ The four golden signals of monitoring are latency, traffic, errors, and saturation. Start to focus on these four

“Don’t suggest, expose!”

Dashboards

➔ An engineer can only react with urgency a

few times a day before they get fatigued

➔ Every page should be actionable

➔ Every page response should require

intelligence

➔ Pages should be about a new problem or

an event that hasn’t been seen before

Pager fatigueA serious a problem to be addressed

Root Cause Analysis: The Core of Problem

Solving and Corrective

by Duke Okes

https://www.amazon.com/Root-Cause-Analysis-Problem-Corrective/

dp/0873897641

Find and eliminate all root causes

➔ When humans are really necessary, thinking and recording the best practices ahead of time in a playbook or runbook improves 3x in the Mean Time To Repair (MTTR)

➔ SRE’s write and rely on on-call playbooks/runbooks

Example: http://docs.ansible.com/ansible/playbooks_intro.html

Playbooks/Runbooks

A healthy monitoring and alerting pipeline should be simple and easy to reason about

Monitoring Conclusion

What do i do with this?

➔ Try always to have a high level stack overview

➔ Despite performance of services like databases often must be performed on the system itself

➔ A dashboard might also be paired with a log, in order to analyze historical correlations rapidly

Release Engineering

➔ All activities in between regular development and delivery of a software product to the end user: ◆ i.e., integration, build, test execution, packaging and delivery of software

➔ “Accelerating the path from development to operations”➔ A part of the SRE team where some more seasoned members are transitioned

there to conduct this highly important task➔ Is an internal service

What is Release Engineering?

1. Use version control2. Use the right building tool(s) for the job 3. Write simple and portable build files 4. Use a release process that is reproducible (CI process)5. Use a package manager6. Define upgrade process before reaching 1.0 7. Create detailed logs of changes made 8. Do “Canary”9. Keep the big picture in mind

10. Apply these commands to yourself

10 Commandments of Release Engineering

Collaboration

developers, SRE’s and release engineers work together

Postmortem cultureLearning from failure

➔ Document written for ALL significant incidents ➔ Non-paged incidents are even more valuable -

monitoring gaps➔ Explain what happened in detail ➔ Find all root causes of the event➔ Assign actions to correct the problem or improve how it

is addressed next time

What are Postmortems?

Postmortems?!

Postmortems Are Blameless!

➔ Use a blame free postmortem culture, with the goal of exposing faults◆ Apply engineering to fix these faults ◆ Try not just avoid or minimize them

Learn and teach with postmortems

Source: http://www.xkcd.com/1495/

SERIOUSLY: BLAMELESS!

The Field Guide to Understanding Human Error

by Sidney Dekker

https://www.amazon.com/Field-Guide-Understanding-Human-Error/dp/0754648265

Conclusions

The S.R.E. Google Book and more resources

● https://g.co/SREBook

● There is now #SRE on @hangops Slack. https://t.co/btPgSGkGNz to join.

QUESTIONS!

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THANK YOU!

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