Continuous Delivery for "Mature" Codebases by Melisa Benua

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When starting up a greenfield project, it’s easy to take advantage of the most modern development practices. But what about the rest of us, who are working on codebases greater than five minutes old? How do you take code that’s four years and hundreds of thousands of SLOC, and turn that into a lean, mean, continuous-deploying machine? In this SauceCon 2019 presentation, Melissa Benua walks through what continuous integration and deployment means for teams working on mature code bases, and what the roadmap looks like to get from a release cycle that may take weeks or months to one that deploys on-demand.

Software

5/7/2019
1
Continuous Delivery
for ‘Mature’ Code
#SauceCon 2019Melissa Benua
about
me
Melissa Benua
Senior Engineering Manager
mParticle
mbenua@gmail.com
@queenofcode
1
2

5/7/2019
2
what is continuous delivery?
Source
Control
Code
Review
Build +
Test
Deploy
+
Monitor
@queenofcode #SauceCon 2019
why continuous delivery?
+50% market cap growth over time
-50% time remediating security issues
+2x likely to be recommended as a great place to work
@queenofcode #SauceCon 2019
3
4

5/7/2019
3
what is a cd roadmap?
Where
you are
Where you
want to go
Reasonable path
between the two
@queenofcode #SauceCon 2019
pillars of concern
01 Source
Control
02 Quality 03 Deployment 04 Monitoring
@queenofcode #SauceCon 2019
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6

5/7/2019
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source control practices
Level1
A source
control
system might
exist!
Level2
Inefficient
use of
branches –
either too
many levels,
or too few Level3
GitHub Flow
Level4
Main
trunkline
development
with
frequent
(daily)
commits to
master
@queenofcode #SauceCon 2019
quality practices
Level1
Few tests
No auto test
runs
Don’t all
pass
‘It works on
my machine’
Level2
Unit tests
auto run
Test suites
are reliable
Manual
integration
tests
Level3
>60% unit
test
coverage
Automatic
int tests
Manual
specialty
tests
Level4
Fully auto
regr tests
Specialty
test runs
(perf,
security, UI,
etc)
@queenofcode #SauceCon 2019
7
8

5/7/2019
5
deployment practices
Level1
Builds
sometimes
deployed
from a
developer’s
machine
Level2
Builds
created from
an auto
build system
Level3
Components
are able to
deploy
independent
from the
whole
Level4
Infrastructure
as code
(containers)
@queenofcode #SauceCon 2019
monitoring practices
Level1
Logs exist on
individual
servers
Level2
Centralized,
searchable
logs
Level3
Some
metrics
collected,
but adhoc
per-
developer
Level4
Standard
metrics,
alerts,
structured
log data
@queenofcode #SauceCon 2019
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10

5/7/2019
6
continuous delivery stages
STAGE 4
Full Automation
STAGE 3
Significant Automation
STAGE 2
Early Automation
STAGE 1
Very Manual
Automated Builds
Automated Staging
Manual Deployments
Automated-ish Builds
Manual Staging
Manual Deployments
Automated Builds
Containerized Staging
Push-Button
Deployments
Automated Builds
Automated Staging
Automated Deployments
@queenofcode #SauceCon 2019
step 1: self assessment
Source
Control
1 - None
2 - Inefficient
3 - GitHub
Flow
4 - Trunkline
Quality
1 - None
2 - Unit Tests
3 - Integration
Tests
4 - Specialty
Tests
Deployment
1- Manual
2 - Auto
Builds
3 - Service
Builds
4 - Container
Builds
Monitoring
1 - Server
Logs
2 - Central
Logs
3 - Metrics
4 - Structured
Tracing
Delivery Stage
4 - Manual
8 - Early Auto
12 - Semi Auto
16 - Full Auto
@queenofcode #SauceCon 2019
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12

5/7/2019
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step 2: goal assessment
What’s the standard in
our industry?
Do we have any internal
blockers?
Do we have any external
or regulatory blockers?
Do we have customer
blockers?
@queenofcode #SauceCon 2019
step 3: plot your map
Are all four tires in
the same condition?
Do we have enough
fuel in the tank?
Do we have the necessary
licensing and authorization?
Do we have the
correct size engine?
@queenofcode #SauceCon 2019
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14

5/7/2019
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Key Takeaways
Don’t let the tail wag the
dog – capabilities beget
behavior
Know the pillars, and
where your team is on
them; stay balanced
Be honest about the
investment your team can
make
Make the ‘right’ thing
easy, and success will
follow
@queenofcode #SauceCon 2019
thank you!
@queenofcode #SauceCon 2019
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In this SauceCon 2019 presentation, Mario describes the practices that ABN AMRO adopted in mobile teams when it comes to testing native applications on real devices. Since using Espresso and XCUITest is still relatively uncommon for large apps and there are various unique challenges due to being in an EU-regulated industry with various security restrictions, Mario will share the ABN AMRO team’s experiences, including: - A brief architectural overview of the Mobile Banking app: why it is all native (Objective-C/Swift and Java/Kotlin), how it communicates with other apps and websites - Why ABN AMRO choose to adopt Espresso and XCUITest: the advantages and the limitations of this choice - How ABN AMRO runs their test pipelines to spread them across time and devices and prevent teams from being blocked

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Creating automation engineers from manual testers is hard. Even if testers are willing, they have a lot of hurdles to get over to feel like the same kind of subject matter experts in automation as they are in manual testing. As a career-long manual tester making the leap to automation, Jenny Bramble has experience to explain frustrations and provide solutions. In this SauceCon 2019 presentation, she discusses managing the expectations of testers and their managers (what’s the time frame? Why isn’t this working?), techniques for teaching (such as games! Pair/mob programming! Software fundamentals!), and how to know when testers have made it (what should manual testers be aiming for when they start?)

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Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

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In today's dynamic e-commerce landscape, the payment gateway emerges as a linchpin, ensuring smooth and secure transactions between buyers and sellers. In this discourse, we delve into the meticulous process of devising test cases tailored for scrutinizing payment gateways. Crafting precise test cases for payment gateways is a quintessential responsibility for testers operating within the service industry. This article meticulously explores pivotal scenarios integral to how to test payment gateways, coupled with essential guidelines for drafting effective test cases.

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Continuous Delivery for "Mature" Codebases by Melisa Benua

1. 5/7/2019 1 Continuous Delivery for ‘Mature’ Code #SauceCon 2019Melissa Benua about me Melissa Benua Senior Engineering Manager mParticle mbenua@gmail.com @queenofcode 1 2

2. 5/7/2019 2 what is continuous delivery? Source Control Code Review Build + Test Deploy + Monitor @queenofcode #SauceCon 2019 why continuous delivery? +50% market cap growth over time -50% time remediating security issues +2x likely to be recommended as a great place to work @queenofcode #SauceCon 2019 3 4

3. 5/7/2019 3 what is a cd roadmap? Where you are Where you want to go Reasonable path between the two @queenofcode #SauceCon 2019 pillars of concern 01 Source Control 02 Quality 03 Deployment 04 Monitoring @queenofcode #SauceCon 2019 5 6

4. 5/7/2019 4 source control practices Level1 A source control system might exist! Level2 Inefficient use of branches – either too many levels, or too few Level3 GitHub Flow Level4 Main trunkline development with frequent (daily) commits to master @queenofcode #SauceCon 2019 quality practices Level1 Few tests No auto test runs Don’t all pass ‘It works on my machine’ Level2 Unit tests auto run Test suites are reliable Manual integration tests Level3 >60% unit test coverage Automatic int tests Manual specialty tests Level4 Fully auto regr tests Specialty test runs (perf, security, UI, etc) @queenofcode #SauceCon 2019 7 8

5. 5/7/2019 5 deployment practices Level1 Builds sometimes deployed from a developer’s machine Level2 Builds created from an auto build system Level3 Components are able to deploy independent from the whole Level4 Infrastructure as code (containers) @queenofcode #SauceCon 2019 monitoring practices Level1 Logs exist on individual servers Level2 Centralized, searchable logs Level3 Some metrics collected, but adhoc per- developer Level4 Standard metrics, alerts, structured log data @queenofcode #SauceCon 2019 9 10

6. 5/7/2019 6 continuous delivery stages STAGE 4 Full Automation STAGE 3 Significant Automation STAGE 2 Early Automation STAGE 1 Very Manual Automated Builds Automated Staging Manual Deployments Automated-ish Builds Manual Staging Manual Deployments Automated Builds Containerized Staging Push-Button Deployments Automated Builds Automated Staging Automated Deployments @queenofcode #SauceCon 2019 step 1: self assessment Source Control 1 - None 2 - Inefficient 3 - GitHub Flow 4 - Trunkline Quality 1 - None 2 - Unit Tests 3 - Integration Tests 4 - Specialty Tests Deployment 1- Manual 2 - Auto Builds 3 - Service Builds 4 - Container Builds Monitoring 1 - Server Logs 2 - Central Logs 3 - Metrics 4 - Structured Tracing Delivery Stage 4 - Manual 8 - Early Auto 12 - Semi Auto 16 - Full Auto @queenofcode #SauceCon 2019 11 12

7. 5/7/2019 7 step 2: goal assessment What’s the standard in our industry? Do we have any internal blockers? Do we have any external or regulatory blockers? Do we have customer blockers? @queenofcode #SauceCon 2019 step 3: plot your map Are all four tires in the same condition? Do we have enough fuel in the tank? Do we have the necessary licensing and authorization? Do we have the correct size engine? @queenofcode #SauceCon 2019 13 14

8. 5/7/2019 8 Key Takeaways Don’t let the tail wag the dog – capabilities beget behavior Know the pillars, and where your team is on them; stay balanced Be honest about the investment your team can make Make the ‘right’ thing easy, and success will follow @queenofcode #SauceCon 2019 thank you! @queenofcode #SauceCon 2019 15 16

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