I really do like this extension, its auto suggestion makes me write code much faster.


M.S. in Computer Science and Engineering
I really do like this extension, its auto suggestion makes me write code much faster.

Remote SSH in VS Code is one of the cleanest ways to work on a remote Linux machine as if the files were local.
It installs a lightweight VS Code server on the remote machine over SSH. Your editor runs locally, but all:
run on the remote host.
Open VS Code → Extensions → search “Remote – SSH” → install.

From your terminal, confirm:
test below at command prompt:
ssh username@hostname
If this doesn’t work, VS Code won’t connect either.
Note: if you use NAT in your VM, you would have to create a port forward 2222 from the host to 22 in the guest/remote VM
you should connect using your host instead e.g ssh -p port username@127.0.0.0


Open the Command Palette:
press:
Ctrl + Shift + P → “Remote-SSH: Add New SSH Host”

e.g here my VM is using NAT so I have to use port forwarding to be able to remote connect ssh to it and I like to use root to remote connect as it is my local VM so no security concern here.

4. Connect
Ctrl + Shift + P → “Remote-SSH: Connect to Host…”



Enter the password of my root user and hit Enter and now I am using VScode from my windows host to remote develop on my VM.

:set paste is one of those tiny Vim commands that solves a huge headache. Since you’ve been wrestling with copying from Windows into Vim, this is exactly the right tool.
Here’s the clean, practical breakdown.
:set paste actually doesIt tells Vim:
This prevents the classic “pasted text turns into a mess” problem.
In normal mode:
type:
:set paste
Then enter insert mode:
type:
i
Now paste using your terminal shortcut (e.g., Ctrl+Shift+V, right‑click → Paste, etc.).
If you want a quick toggle key:
Add this to your ~/.vimrc:
type:
set pastetoggle=<F2>
Now pressing F2 instantly switches paste mode on/off.
When you copy sth from vim editor and want to past it to other application, you would have to install the full build of vim to have clipboard support
In a terminal (not inside vim), run:

You’ll see either:

Test if copy inside vim will be able to be pasted outside vim (+clipboard is working), please do:
Inside vim, do this:

You should not see “+y typed on the screen—vim interprets it as a command, not text.
Now go outside vim and right click → paste
Through my professional career, I was tasked to start support our client on Linux since our competitor started supporting theirs on Linux. I started developing our C# daemon service that acted as a client loader (it periodically talks to the enterprise to see if there are any packages scheduled to be deployed/downloaded and transferred to target client – Linux platform). it runs at startup in the background, and it is in fact a WCF where its front-end client is an embedded browser Chromium Embedded Framework (CEF) running Html/Css/Js etc for the UI and it interacts to this client loader C# daemon (wcf) through its service contract. I really love this project since I started its development from scratch and I learned a lots about Linux. I learned about firewalld (we locked down lots of ports by default for security), Linux securities (proxy, sudoers etc..), learn how to launch UI application since our Linux Image does not have desktop, bash script (for automation rpm build and within rpm itself), systemd (for daemon service related), bash script for automation, learned how to build rpm since we need to bundle its related files (dependencies dlls, noted we use mono so I have to bundle mono with it as well) as an rpm which can then be easily preinstalled on our Linux Hardware image by our hardware team, which we periodically release internally with our hardware team (yes we sell our enterprise application with our discounted Hardware devices e.g end user only has to pay $1 for the device as long as they buy our software contract). I also automated its rpm build nightly using Jenkin hudson where the Hudson jenkins agent running in Windows would execute its job per schedule in Hudson job configuration and I used it to execute some automation win32 batch scripts where it does automated things like Msbuild our .sln and then copied the related output files passwordless via ssh using private/public key to our Linux build machine where its designated bash script would then be executed for the rpm build. I wrote both the windows batch script and also Linux bash script for the automation of our daemon rpm nightly build so I can share the output rpm internally between hardware team and qa team to test it.
Also, when we started our development, we tried it with Ubuntu, later Centos, then Oracle Linux. And Oracle Linux is quite similiar to Centos because both are the Rebuilds of Red Hat Enterprise Linux (RHEL)
Our client is now running on Linux using .Net Core and now .Net 8

I just noticed that I wrote my full name wrong urgh.
Using latest VirtualBox Downloads – Oracle VirtualBox with latest Centos image Download – The CentOS Project

Latest Centos is still looking cool. Actually I do like it more than Ubuntu.

I will install C++ on this Linux VM e.g gcc/g++/cmake etc.. for my own project 🙂
I have used and programmed in both languages professionally and academically.
For C#, I prefer VS studio or its light weighted version VS code whereas Java, I prefer Eclipse or NetBean.
These two languages are high level languages object oriented programming languages where it uses Class and Object for organizing code and code reusability/scalability.
These two programming languages are quite similar, in my own opinion it is 88% similar since they operate based on the same concept of OOP e.g Class, Object, A. P.I.E (Abstraction, Polymorphism, Inheritance & Encapsulation), Multithreading, Thread-safe capability, Exception Error Handling, Auto memory management with its memory garbage collector, Communication between multithreading, Primitive types and Reference types, Type safety, access modifier. C# supports both strongly type and weakly type like dynamic (runtime type) whereas Java only supports strongly (statically) type.
In short, they both emphasize SOLID capabilities.
S: Single Responsibility principle:
a class should only have one reason to change or in short, a class should only have single responsibility.
E.g: if an employee class has EmployeeSalaryCalculation() and also SaveEmployeeData(), it breaks this principle since these two actions are two different responsibilities and to satify this principle we should separate it to another class e.g Employee class (salary related etc.) and EmployeeReposity (data/db related etc.)
O: Open/Closed principle:
Open for Extention but Closed for modification. In short, it refers to abstract class and sub class where sub class can derive from abstract class and make its own version (extension) of abstract class method (abstract method) but no modication can be made to the abstract method because abstract method has no implementation (Closed for modification).
L: Liskov principle:
In short, it refers to polymorphism. Poly means many form. it refers to the ability of object to take on many forms. e.g a sub class can be used in place of the parent class and its method can change based on the version of each sub class (object can take on many forms). There is two types of polymorphism. Overloading (compile time polymorphism) and overriding (runtime polymorphism). Overloading e.g method overloading where same method name with different number of arguments can behave diferently based on the number of arguments whereas Overriding e.g several diferent sub class override parent class’s method.
I: Interface Segregation principle:
a client should not be forced to implement interface that they do not need or use. In short, we should always try to break big interface into subtle interface so that way it is easy for a client to only implement interface it needs and also since both Java and C# support multiple interfaces implmentation.
D: Dependency inversion principle:
This principle emphasizes the importane of decoupling high level modules from low level module. high level module should not depend on low level module and vice versa through abstraction and interface. In short, we can accomplish this principle through dependeny injection so instead of having low level class as member of our high level class (hard coupling) we should introduce interface and have interface as a member instead so that way the low level classes that implement the interface can be inject at runtime either through constructor or method that accept the interface type as an argument.
Ok let get back to illustrate that both langauge are quite similar. if you can program in C#, you should definitely be able to program in Java easily.
Java
-------------------------------------
Class MySubClass extends MySuperClass
C#
-------------------------------
Class MySubClass : MySuperClass
Java
super(args)
C#
base(args)
Java
class MySubClass implements MyInterface1, MyInterface2
C#
class MySubClass : MyInterface1, MyInterface2
Java
final class Vehicle {
void display() {
System.out.println("This is a vehicle");
}
}
// This will cause a compile-time error
// Error: Cannot inherit from final 'Vehicle'
class Car extends Vehicle {
}
C#
sealed class Vehicle
{
public void Display()
{
Console.WriteLine("This is a vehicle");
}
}
// This will cause a compile-time error
// Error: 'Vehicle' is sealed and cannot be inherited
class Car : Vehicle
{
}
Both does the exact same thing: Once assigned, cannot be changed.
Both does exact same thing: it prevents sub class from overriding the super class method.
Java
a) Create Thread through Extend Thread class
class MyThread extends Thread {
public void run() {
System.out.println("Thread running");
}
}
public class Main {
public static void main(String[] args) {
MyThread t1 = new MyThread();
t1.start();
MyThread t2 = new MyThread();
t2.start();
}
}
b)Create Thread through Implement Runnable interface
class MyRunnable implements Runnable {
public void run() {
System.out.println("Runnable running");
}
}
public class Main {
public static void main(String[] args) {
Thread t1 = new Thread(new MyRunnable());
t1.start();
Thread t2 = new Thread(new MyRunnable());
t2.start();
}
}
C#
using System;
using System.Threading;
class Program {
static void Main() {
Thread t1 = new Thread(new ThreadStart(Run));
t1.Start();
Thread t2 = new Thread(new ThreadStart(Run));
t2.Start();
}
static void Run() {
Console.WriteLine("Thread running");
}
}
Java
try {
// code that might throw an exception
int result = 10 / 0;
} catch (ArithmeticException e) {
System.out.println("Cannot divide by zero");
} finally {
System.out.println("Finally block always executes");
}
C#
try {
int result = 10 / 0;
} catch (DivideByZeroException e) {
Console.WriteLine("Cannot divide by zero");
} finally {
Console.WriteLine("Finally block always executes");
}
Note: there is subtle difference where Java support checked Exception (forced checking exception by the compiler so the calling method has to properly handle it) through throw whereas C# does not have checked Exception.
Java
void readFile() throws IOException {
//code
throw new IOException("File not found");
}
C#
void ReadFile() {
throw new IOException("File not found");
}
Java Access Modifiers:
| Modifier | Class | Package | Subclass | The rest of the World |
|---|
private | ✅ Yes | ❌ No | ❌ No | ❌ No |
default (no modifier) | ✅ Yes | ✅ Yes | ❌ No | ❌ No |
protected | ✅ Yes | ✅ Yes | ✅ Yes | ❌ No |
public | âś… Yes | âś… Yes | âś… Yes | âś… Yes |
C# Access Modifiers:
| Modifier | Class | Derived Classes | Same Assembly | Other Assemblies |
|---|
private | ✅ Yes | ❌ No | ❌ No | ❌ No |
protected | ✅ Yes | ✅ Yes | ❌ No | ❌ No |
internal | ✅ Yes | ❌ No | ✅ Yes | ❌ No |
protected internal | ✅ Yes | ✅ Yes | ✅ Yes | ❌ No |
public | âś… Yes | âś… Yes | âś… Yes | âś… Yes |
Note: in C#
class without access modifier = internal class.
class members without access modifier = private field.
First what is thread safe. Thread safe means to prevent race condition between multiple thread. race codition occures when multiple threads access and update a shared resource at the same time. To prevent race condition in multiple thread, C# use lock object and Java use synchronize object so only one thread can acquired the shared resource and update it once at a time.
C# use AutoResetEvent or ManualResetEvent to allow one thread to signal one or more waiting threads that some event has occurred whereas Java uses notify() and notifyAll()
There are a few more but with these it shows that both languages are quite similar so if we can program in C# we can say we can program in Java. Java is an independent platform language and with .net core, it makes c# also an independent platform language.
I’ll go over this topic this weekend, as it will also help me refresh my own memory of it.
In earlier topics, we have to manually create the Amazon AWS EC2 cloud instance manually but with Terraform – A tool from HashiCorp that lets us define infrastructure as code and it allows us to automate the provision of this instance automatically through hcl code (HashiCorp Configuration Language) and it is file with .tf extension — for example1: main.tf
resource "aws_instance" "example" {
ami = "ami-123456"
instance_type = "t2.micro"
}
When we run terraform apply, it creates that infrastructure automatically (terraform loads *.tf, read them and execute)
example2: .gitlab-ci.yml
stages:
- validate
- plan
- apply
variables:
TF_ROOT: "./" # location of terraform files
TF_STATE_NAME: "default"
TF_IN_AUTOMATION: "true"
before_script:
- cd $TF_ROOT
- terraform init -input=false
validate:
stage: validate
script:
- terraform validate
plan:
stage: plan
script:
- terraform plan -out=tfplan
artifacts:
paths:
- $TF_ROOT/tfplan
apply:
stage: apply
script:
- terraform apply -auto-approve tfplan
when: manual # requires manual approval
In short, with Terraform, we can use it to define infrastructure as code as seen above so it allows us to automate the infrastructure (AWS, GCP, Azure, etc.) through GitLab Pipelines instead of manual provisioning. It’s very useful since manual processes are typically more prone to errors than automated ones.
e.g we would have a GitLab project that is responsible to automate the infrastructure of the cloud providers like AWS, Google Cloud Platform (GCP), Azure etc. and another GitLab project that is responsible to do the actual software development on that said infrastructure.
And with this automation of the infrastructure of the cloud providers we can quickly provision them through code – hcl code. It is an advance topic.
.gitlab-ci.yml?The .gitlab-ci.yml file is the configuration file that defines how our GitLab CI/CD (Continuous Integration and Continuous Deployment) pipeline runs.
It lives at the root of our GitLab repository and tells GitLab what jobs to run, in what order, under what conditions, and in what environments.
When we push code to GitLab, the .gitlab-ci.yml file triggers pipelines that can automatically:
.gitlab-ci.yml file to our repository.npm test, docker build, etc.).Example:
stages:
- build
- test
- deploy
build_app:
stage: build
script:
- echo "Building the app..."
- npm install && npm run build
test_app:
stage: test
script:
- echo "Running tests..."
- npm test
deploy_prod:
stage: deploy
script:
- echo "Deploying to production..."
- ./deploy.sh
only:
- main
Here is what we told GitLab PipeLine what to do per a set of instruction above using its .yml file aka .gitlab-ci.yml:
build_app runs (stage: build)test_app runs (stage: test)deploy_prod runs (stage: deploy) — but only when we push to the main branchHere is the cheatsheet for all the keywords recognized by the pipeline and what are their purposes?
| Section | Purpose / Notes |
|---|---|
stages: | Declare ordered stages (e.g. build, test, deploy). Jobs run by stage order. |
variables: | Global variables for jobs (unless overridden). |
default: | Default settings (e.g. image, before_script, cache) applied across jobs. |
include: | Pull in external YAML files (local, remote, template, project). |
workflow: | Define rules for when a pipeline should run (e.g. on merges only) |
Each job is a top-level key (except reserved ones). In a job we can use:
This cheatsheet is helpful esp for engineer who just starts DevOps.
Example:
stages:
- build
- test
- deploy
variables:
APP_ENV: "production"
default:
image: node:18
before_script:
- npm ci
build_job:
stage: build
script:
- npm run build
artifacts:
paths:
- dist/
test_job:
stage: test
script:
- npm test
dependencies:
- build_job
deploy_job:
stage: deploy
script:
- ./deploy.sh
environment:
name: production
url: https://myapp.example.com
when: manual
only:
- main
Name: Web-Server
Choose Amazone Linux

Use my existing keypair

In Network settings section, we are going to click on Edit and Click Add security group rule

Note: for the simplicity of this post/demonstration, I choose http type (I know it is not secured) because if we choose https we have to configure and use tls for traffic encryption but that is not the intention of this post so I will go with http for simplicity’s sake.

Go ahead and we click on Launch instance ec2

Ok our designated Web-server linux instance is running.

Note down its ip address above
at our win machine, we will remote ssh to it using private key MyLinux.pem so we can then install our Apache web server there


we are connected. next, we will have to elevate ourselves to root with sudo -i so we can install the Apache web server

Next, we will yum install it where httpd is the Apache Web Server.


type y and enter to confirm the installation

install completed and this looks good so let start and check the status of our Apache web server daemon service

Good, it started and running with pid 25664
we can check it in the task managers with ps aux | grep 25664

yes it is there running as daemon /usr/sbin/httpd -DFORGROUND
let makes it run at start up with systemctl enable httpd

let check our web server through the browser client to make sure it is actually running as well and listing on port 80 that we have configured in the security group rule
By going to the browser and type our web server amazon linux public ip address (note we don’t have to specify its default 80) and yes it is running and listening on port 80 as expected

that is being said, we will do that through ssh where gitlab will use private key and our apache webserver would then use the mactching public key so gitlab can remotely deploy stuff to our apache web server. So let turn on public key authentication for our apache web server:
Enable Public Key Authentication in SSH Server
sudo vi /etc/ssh/sshd_config


scroll down and we will see that pubkey auth is commented out by default so we are going to uncomment it. press i for writing mode and remove #

press esc then type :wq to write and quit
since we made a change in its configuration file, we need to restart it so the change will be taken into account with systemctl restart httpd

check its status: systemctl status httpd

Ok good it is running and taken into account our configuration change.
Next we will need to generate public/private key pair from our local repo which is windows
and save it at c:\webkey folder with ssh-keygen -t rsa -b 4096

Next, getting my remote repo “projectX” to my local repo since I already have remote repo “projectX” at the GitLab so I will just clone it in my local directory

Next, copy our public key id_rsa.pub from our local repo id_rsa.pub and input it in our webserver’s public key aka “authorized_key”

Logout from root and cd to the hidden folder .ssh

cd to the hidden .ssh and we will see authorized_keys file there
vi authozied_keys

press i for writing mode and then copy our public key from our windows local repo id_rsa.pub
and paste in this authorized_keys file and save it

press esc then :wq to write and quit vi
Good that concludes that we have configure public key in our designated webserver Apache.
Next we will configure private key in our GitLab.
Project → Settings → CI/CD → Variables → Project variables and click on Add varaible

scroll down till you see below two value key/value pair

Give Key as SSH_PRIVATE_KEY and Value we will copy and paste the private key we generated from our local repo in windows PC



this concludes the handshake btw our GitLab’s CI/CD pipeline and AWS EC2 Linux Apache WebServer where CI/CD would use privatekey and the WebServer would use the matching public key.
image: node:latest
stages:
- test
- deploy
# -------------------------
# Test Stage
# -------------------------
test-job:
stage: test
script:
- npm install -g html-validator-cli
- html-validator --file=index.html --verbose
only:
- main
# -------------------------
# Deploy Stage
# -------------------------
deploy_to_server:
stage: deploy
before_script:
- apt-get update -y && apt-get install -y openssh-client
- mkdir -p ~/.ssh
- echo "$SSH_PRIVATE_KEY" | tr -d '\r' > ~/.ssh/id_rsa
- chmod 600 ~/.ssh/id_rsa
script:
- scp -i ~/.ssh/id_rsa -o StrictHostKeyChecking=no index.html ec2-user@18.191.251.195:/var/www/html/
only:
- main
only: - main means:main branch.”Our index.html from GitLab should look like this after GitLab CI/CD validate its html syntax and deploy it to the target webserver at AWS EC2.

<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width,initial-scale=1" />
<title>Colored Text Example</title>
<style>
:root {
--accent-color: #0077cc; /* change this to update the accent color site-wide */
}
body {
font-family: system-ui, -apple-system, "Segoe UI", Roboto, "Helvetica Neue", Arial;
line-height: 1.5;
padding: 2rem;
color: #222; /* default text color */
background: #f8f9fb;
}
.accent {
color: var(--accent-color);
}
.muted {
color: #6b7280; /* gray */
}
.danger {
color: #cc0000; /* red */
}
</style>
</head>
<body>
<h1 class="accent">Welcome — colored text demo</h1>
<p>This paragraph uses the default text color.</p>
<p class="muted">This paragraph uses a muted (gray) color.</p>
<p class="danger">This paragraph uses a "danger" (red) color.</p>
<p style="color: #2a9d8f;">This paragraph is colored with an inline style (#2a9d8f).</p>
<p>To change the main accent color site-wide, edit the <code>--accent-color</code> in the <code>:root</code> CSS rule.</p>
</body>
</html>
our index.html
Now let check our CI/CD pipeline deploy stag’s logging.

It runs successfully and deployed index.html from remote repo in GitLab to the target AWS EC2 cloud Apache Web server at default directory /var/www/html
so if we go to the browser and put in our web server public ip, the web server should render our index.html. (note the Not Secure because we use http protocol instead of https as using https requires TLS configure which is not intended for this simplicity of this post)

Voila works as expected.
This conclude that our CI/CD deploy stage is able to deploy work to targeted AWS EC2 cloud Apache web server on Amazon Linux successfully.
To refresh our memory: What is GitLab runner?
Runner is a GitLab component that actually executes our CI/CD pipeline (Continuous Integration (CI)/Continuous Delivery (CD) ).
We define our CI/CD pipeline stage and job using its .gitlab-ci.yml (.yaml) file which defines jobs (like builds, tests, deploys), the runner is what runs those scripts on some compute environment e.g our aws ec2 cloud instance amazon linux.
Example of .gitlab-ci.yml looks like
stages:
- build
- test
- deploy
build-job:
stage: build
script:
- echo "Hello, $GITLAB_USER_LOGIN!"
test-job1:
stage: test
script:
- echo "This job tests something"
test-job2:
stage: test
script:
- echo "This job tests something, but takes more time than test-job1."
- echo "After the echo commands complete, it runs the sleep command for 20 seconds"
- echo "which simulates a test that runs 20 seconds longer than test-job1"
- sleep 20
deploy-prod:
stage: deploy
script:
- echo "This job deploys something from the $CI_COMMIT_BRANCH branch."
environment: production
with .yml above, it is like set of instruction that we tell how GitLab would run the runners for our CI/CD pipeline. Like above, we tell GitLab that the runner would have 3 stages
first stage is build, second stage is test, and third stage is deploy.
then we can add job that linked to the stage by
stage: <stage_name>
stage:
- <stage_name>
<job_name>:
- stage: <stage_name>
- script:
<script_statements>
e.g above Example of .gitlab-ci.yml, we only have one build job, two run jobs (one short, one longer), last but not least, we have one deploy job.
When we use GitLab SaaS (e.g., our project is hosted at gitlab.com):
.gitlab-ci.yml.But Saas runner is just one type of runners that GitLab supported.
GitLab Runner SaaS refers to GitLab’s managed runners — runners hosted and maintained by GitLab itself.
| Type | Description | Managed By |
|---|---|---|
| SaaS / Shared Runner | Preconfigured runners available for all projects on GitLab.com | GitLab |
| Group or Project Runner | Dedicated to our group or project, still hosted by GitLab | GitLab |
| Self-Managed Runner | Installed and maintained by us (e.g. on our own VM or cluster) | Us |
So today, we explore how we can setup and managed our runner. And we will use AWS ec2 cloud Amazon Linux to demonstrate it here:
Please have a look at below link which I already covered briefly how to get AWS ec2 instance running and ssh to it remotely using private key:
Connecting local git repo with remote GitHub repo in AWS Linux instance – csforce.de | VIC: Setup self-managed GitLab runner on AWS ec2 cloudFirst we will have to add GitLab runner repo and then yum install it:
by executing below curl piped command to add the repo & yum install command to install it at terminal:
# Add the official GitLab Runner repository
curl -L https://packages.gitlab.com/install/repositories/runner/gitlab-runner/script.rpm.sh | sudo bash
# Install the runner
sudo yum install gitlab-runner -y
after the piped command we should see this which mean our gitlab repo is added to our amazon linux distro repos:


This looks good our GitLab’s runner is now installed in our AWS ec2 cloud linux distro successfully.
Next, we need to setup our GitLab’s repo and point our runner to our AWS ec2 cloud linux runner instance.
Go to our project’s repository, then navigate to Settings → CI/CD → Runners, and disable the instance (SaaS) runners by toggling them off.

Next, go to Project Runners → Create project runner

For the simplicity, we will check untagged and click create runner

Choose Linux since our AWS cloud is EC2 Amazon linux

And copied and paste the following command at our aws ec2 cloud instance (amazon linux) to register it there (to link them: Gitlab <-> aws ec2 linux runner instance)


hit enter since we will use the default url https://gitlab.com
and enter “linuxrunner” as the name our self-managed runner here:

next type shell for the executor and hit enter (since this is a simple demonstration of the setup of self-managed runner, we chose shell for our .gitlab-ci.yml’s script aka bash, but if you want you can choose vm, or docker etc and chose by typing the executor type here)

This looks good:
At our GitLab project settings CI/CD we would see this below:

Click on View runners and we should see our project runner is registered successfully and online (green means it is online)

Note that our simple .gitlab-ci.yml is as below: 3 stages (build, test, deploy), 1 build job, 2 test jobs, and one deploy job.

so any commit to our main branch of our project branch would trigger the pipeline as seen below:

All the jobs completed and passed successfully





We can check our ci/cd pipeline jobs log as seen above and we saw that our script were executed successfully.
This concluded that we have pointed our project’s CI/CD pipeline runner to our self-managed runner on AWS EC2 cloud Amzon Linux successfully.
In addition, how do we check the status of our runner whether it is running or not?
our runner is actually a daemon. think of daemon like a windows service which we can check using service.msc but how do we check the status of daemon service in linux?
A Linux daemon service is a background process that runs continuously on a Linux system, typically without direct user interaction. Daemons are often used for system or network services — like web servers, database servers, or schedulers — and are managed using the systemd service manager in most modern Linux distributions.
in centos family like Amazon linux distribution, we can check it using
sudo systemctl status <daemon_service_name>
e.g:
sudo systemctl status gitlab-runner

to make gitlab-runner daemon service run automatically at start up we can execute command below:
sudo systemctl enable gitlab-runner
To start/stop it:
sudo systemctl start gitlab-runner
sudo systemctl stop gitlab-runner