Using Go in DevOps

Jan 9, 20191 like906 views

Natalie Pistunovich Engineering Manager – Fraugster Natalie is an Engineering Manager, Go Developer, Berlin’s Go User Group Lead, GopherCon Europe organizer and Public Speaker. She also describes herself as a Passionate Learner and Professional Questions Asker.

Using Go
in DevOps
Natalie Pistunovich
@NataliePis

- Intro to Go
- OPS/SRE Tools in Go
- What’s Next?

$GOOS $GOARCH
darwin 386 -- 32 bit MacOSX
darwin amd64 -- 64 bit MacOSX
linux 386 -- 32 bit Linux
linux amd64 -- 64 bit Linux
linux arm -- RISC Linux
windows 386 -- 32 bit Windows
windows amd64 -- 64 bit Windows
And there’s more…

• fmt
• io/ioutil
• net/http
• os/exec
• path/filepath
• regexp
• strings
• text/tabwriter
• time
stdlib

Pointers Exist,
Pointer Arithmetic
Doesn’t

The Go community
  doubled
in the last year

There are approx. 1.5
Million active Go users

New Go users in 2017
=
New Go users in
the last 9 years

invite.slack.golangbridge.org
github.com/golang/go/wiki
play.golang.org
golang.org/blog
twitter.com/golang (also: #golang)
Go Resources

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Many applications allow you to use hardware such as GPUs and FPGAs for acceleration. Common examples include media processing and offloading highly parallel work to a GPU. Applications that use accelerators are resource heavy and have stacks spanning kernel and user space; accelerators often have their own requirements for operating system support and kernel versions. While it may not seem intuitive to containerize this type of application, the use of containers provides benefits such as reduced setup time from container reuse, reduction in dependency conflicts and dependency on a specific operating system, and easier updates. In this session I show a media processing stack, making use of containers alongside a GPU. Specifically, I explain the kernel and user space divide of a hardware-accelerated transcode application using a device exposed to the container. This specific stack is an interesting case because of its dependency on hardware, use of a custom kernel and libraries, and operating system requirements. Our investigations have shown the use of containers has minimal performance overhead compared to running natively. Furthermore, we can quickly deploy on other machines with reduced configuration effort. There are some aspects of the application not suited to containerization, however. Since the application relies on a custom kernel, the use of containers does not necessarily increase portability. Improvement in this area would require rethinking how the applications are developed and distributed. Other areas of innovation include things such as Docker plugins to check for compatibility between the container software and host kernel.

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1. Using Go in DevOps Natalie Pistunovich @NataliePis

8. Observability

9. ObservabilityObservability

10. ObservabilityObservability

11. ObservabilityObservability

12. ObservabilityObservability

13. ObservabilityObservability

21. - Intro to Go - OPS/SRE Tools in Go - What’s Next?

22. - Intro to Go - OPS/SRE Tools in Go - What’s Next?

23. - Intro to Go - OPS/SRE Tools in Go - What’s Next?

30. Companies Using Go

32. Ops Tools in Go

69. Intro to Go

82. github.com/golang/go/wiki

83. github.com/golang/go/wiki

84. Go Beneﬁts for SRE

85. Go Beneﬁts for SRE

86. • Simple • Reliable • Efficient

87. • Simple • Reliable • Efficient

89. Open Source

90. Fast Compilation and Execution

91. Fast Compilation and Execution

92. Fast Compilation and Execution

93. Import-Defined Dependencies

94. One Binary to Rule Them All

95. Cross Compilation

96. Cross Compilation

97. $GOOS $GOARCH darwin 386 -- 32 bit MacOSX darwin amd64 -- 64 bit MacOSX linux 386 -- 32 bit Linux linux amd64 -- 64 bit Linux linux arm -- RISC Linux windows 386 -- 32 bit Windows windows amd64 -- 64 bit Windows And there’s more…

98. Cross Compilation

99. Cross Compilation

100. Garbage Collection

101. Garbage Collection

102. Garbage Collection

103. Garbage Collection

104. Garbage Collection

105. Readability

106. Testing

107. Benchmarking

108. Profiling

109. • fmt • io/ioutil • net/http • os/exec • path/filepath • regexp • strings • text/tabwriter • time stdlib