Go is a compiled, concurrent, garbage-collected, statically typed language developed at Google. According to Rob Pike, one of the creators of Go, the language was designed by and for people who write - and read and debug and maintain - large software systems.
Go is an excellent programming language for engineering large software projects. Some of the most popular container technologies used in DevOps like Docker and Kubernetes are written in Go.
It is also loved by the Dev community. According to 2020 developer survey by Stackoverflow, Go stands at 5th position in the list of of most loved programming languages and at 3rd position in the list of most wanted languages to learn.
So what are some of the characteristics of Go programming language that makes it great for DevOps.
When you compile a Go program, everything is included as a single binary and there are no external dependencies that will need to be installed on the targeted machine that the Go program is intended to run on. And this makes the deployment of Go programs really easy.
Even though Go is a compiled language, it compiles directly into machine code as opposed to intermediate object code which is required for Java. Go was designed to be extremely fast. Here’s a small benchmark game comparing Go vs Python.
Binary executables of Go programs can be produced for any platform like Windows, Linux and macOS. In order for a binary to be supported on the different operating systems all it takes is setting two environment variables:
Go program has fast compilation times and fast runtimes with lower resource usage like CPU and memory especially when compared to language like Python. As the compiler fails the run if there are unused imports, the compilation time is short. And as the code is compiled to machine code, it also executes fast.
Unlike Python which often requires the use of third party libraries to implement a particular Python program, the Go programming language has a standard library which includes a lot of built-in functionality that you will need as a DevOps engineer.
This includes functionality like file processing, HTTP web services, JSON processing, native support for concurrency and parallelism as well as built-in testing modules.
Currently building SigNoz - an open-source alternative to DataDog, New Relic, etc. 💙
SigNoz's backend is written in Go.
SigNoz helps developers monitor applications and troubleshoot problems in their deployed applications. Check out our GitHub repo👇
SigNoz helps developers monitor their applications & troubleshoot problems, an open-source alternative to DataDog, NewRelic, etc. 🔥 🖥
Monitor your applications and troubleshoot problems in your deployed applications, an open-source alternative to DataDog, New Relic, etc.
SigNoz helps developers monitor applications and troubleshoot problems in their deployed applications. SigNoz uses distributed tracing to gain visibility into your software stack.
- Application overview metrics like RPS, 50th/90th/99th Percentile latencies, and Error Rate
- Slowest endpoints in your application
- See exact request trace to figure out issues in downstream services, slow DB queries, call to 3rd party services like payment gateways, etc
- Filter traces by service name, operation, latency, error, tags/annotations.
- Aggregate metrics on filtered traces. Eg, you can get error…