Install and Setup
The course is part of this learning path
If you're thinking about engineering the next big dotcom application then you should seriously consider using Go!!
The Go Programming Language is without doubt one of the hottest languages to learn, particularly in this cloud native era. More and more companies are adopting Go to engineer highly performant, stable and maintainable applications. Popular projects such as Docker, Kubernetes, Terraform, Etcd, Istio, InfluxDB have all been built successfully using Go!!
This introductory level training course is designed to bring you quickly up to speed with the many key features that the Go programming language provides. You'll also learn how to setup your own Go development environment - consisting of the Go toolchain, Visual Studio Code, and several related Go based extensions - all to ensure that you are able to be productive writing your own source code.
We’d love to get your feedback on this course, so please give it a rating when you’re finished. If you have any queries or suggestions, please contact us at email@example.com.
By completing this course, you will:
- Learn about what makes Go a great language
- Learn how to install the Go toolchain
- Learn how to setup Visual Studio Code to edit and debug Go programs
- Learn how to work with the Go Playground to test and run snippets of Go code
- Learn and understand the basic Go language syntax and features
- Learn how to use the Go tool chain commands to compile, test, and manage Go code
- And finally, you’ll learn how to work with and manage Go modules for module dependency management
This course is intended for:
- Anyone interested in learning the Go Programming Language
- Software Developers interested in using Go to compile and test Go based applications
- DevOps practitioners looking to learn about Go to support Go based applications
To get the most from this course, you should have at least:
- A basic understanding of software development and the software development life cycle
All sample Go source code as used and demonstrated within this course can be found here:
- [Jeremy Cook] Timeouts can be specified in select statements to help manage situations where it's taking too long to receive a message from any one of the channels being monitored.
Consider using timeouts when you're implementing something that connects to an external resource. When working with external resources, you can never guarantee the response times and, therefore, may need to proactively take action after a predetermined timeout. Implementing a timeout with a select case statement is very straightforward. Simply import the time package and then have a case statement that unblocks on the time.after channel. With this configuration in place, the select statement will timeout and unblock after a configured amount of time if no other channels liven up. Let's see this in action. Running this program results in the message Timeout. The explanation for this follows. We start up an anonymous go routine on lines nine through to 13.
Within it, we immediately pause for five seconds. Regardless, the main program flow continues onto the select case statements implemented across lines 15 to 20. The last case statement declares a two-second timeout using the time.after function. And the result follows that the message Timeout is returned in the program's output, as seen here. Let's swap the timings on lines 10 and 18 and then rerun the program. This time, the timeout is not exceeded, and the program instead prints out the message cloudacademy.
In summary, you've just observed how a timeout can be declared within a select case statement and how to utilize the time.after function to implement a timeout when working with channels and messages.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).