In the previous blog, I focused on accelerating CI by parallelization. However, since there is a limit to the hardware resources because of their costs, therefore efficient distribution of the limited resources to parallel tasks is the key to further speeding up. In this blog, I will show you how to improve job throughput by optimizing the allocation of CPU usage.
In Rocro, a series of processes caused by events such as git-push and pull requests are called jobs and processes executed on individual containers in jobs are called tasks. In other words, a job is a collection of tasks. For example, in the following rocro.yml, the entire process set in YAML is a job and the process of each tool (such as gofmt), setup process for executing these tools, etc. are tasks.
inspecode:
gofmt: default
golint: default
go-test: default
Since the execution time of a job depends on the slowest task, in order to improve the throughput of the job, it is necessary to level the execution time of each task as much as possible. For Inspecode/Docstand, CPU usage can be specified by cpu option in rocro.yml. cpu: 1 indicates that the tool can use one CPU core to its full extent. With cpu: 1, 3.75 GiB memory is allocated and the allocation is proportional to the CPU usage. You can specify the amount in 1/1000th units by specifying the usage amount with a decimal fraction such as cpu: 0.25 or by adding m (milli) at the end. cpu: 250m is equivalent to cpu: 0.25.
If go-test takes the longest time in the above rocro.yml, assigning more CPU resources to go-test than the other tools will improve the processing time of the whole job:
inspecode:
gofmt:
machine:
cpu: 0.25
golint:
machine:
cpu: 500m
go-test:
machine:
cpu: 1.25
This level of finer optimization of CPU resources is not available in other CI tools and services. Inspecode/Docstand are completely free during the beta period and you can use a total of 8 CPU cores for free. So I hope you can try out various optimizations.
Rocro Engineering Blog 