Site Reliability Engineer (SRE) with Ansible Salary in 2024
How statistics are calculated
We count how many offers each candidate received and for what salary. For example, if a Site Reliability Engineer (SRE) developer with Ansible with a salary of $4,500 received 10 offers, then we would count him 10 times. If there were no offers, then he would not get into the statistics either.
The graph column is the total number of offers. This is not the number of vacancies, but an indicator of the level of demand. The more offers there are, the more companies try to hire such a specialist. 5k+ includes candidates with salaries >= $5,000 and < $5,500.
Median Salary Expectation – the weighted average of the market offer in the selected specialization, that is, the most frequent job offers for the selected specialization received by candidates. We do not count accepted or rejected offers.
Trending Site Reliability Engineer (SRE) tech & tools in 2024
Site Reliability Engineer (SRE)
What is site reliability engineering?
At its core, SRE is a software-enabled practice that automates many tasks within IT infrastructure, such as system management and application monitoring. Organisations use SRE to maintain the reliability of software applications in the face of frequent updates coming from development teams. SRE improves the reliability of scalable software systems in which management (including updating and monitoring) of a large system with software would offer more sustainability than manually monitoring hundreds of machines.
Why is site reliability engineering important?
Site reliability refers to the stability and quality of service the application can provide once it is at the disposal of end users. Every so often, software maintenance either directly or indirectly impacts software reliability when, for example, a developer makes some changes impacting certain use cases to cause the application to crash.
The following are some benefits of site reliability engineering (SRE) practices:
- Improved collaboration: SRE helps the development and operations teams work together more effectively. When newly arrived code is released by the development team to the production environment so as to deliver new features or resolve urgent defects, it is often necessary for a developer to make a sudden change to an application. Meanwhile, the operations team needs to make sure that the resulting service is delivered correctly. Consequently, they must stand ready to immediately realise when changes cause issues. SRE practices allow the operations team to provide close monitoring of every update and respond quickly to the inevitable problems that changes engender.
- Enhanced customer experience: Based on an SRE model, organisations are able to put in place barriers that ensure mistakes with the software will never impede the experience of a customer. Take the software team that uses tools designed and developed by SRE teams to automate the entire software development lifecycle. Doing so enables the team to reduce the rate of mistakes, meaning less feature development time spent fixing so-called bugs.
- Improved operations planning: SRE teams recognise that failures in software are a real probability, so they plan for the right incident management strategy to limit the impact of the outage on the business and the end user. They are also able to more accurately assess the cost of the downtime and understand the nature of the business impact of the failure.
What are the key principles in site reliability engineering?
The following are some key principles of site reliability engineering (SRE):
Application monitoring
SRE teams recognise that errors are an inevitable part of deploying software. Rather than seeking a perfect solution, they monitor it based on service-level agreements (SLAs), service-level indicators (SLIs), and service-level objectives (SLOs). They can even monitor performance metrics while the application is continually deployed to production environments.
Gradual change implementation
SRE best practices call for the release of frequent but small batches that support resilience. SRE automation engines use regular but repeatable processes to perform the following:
- Reduce risks due to changes
- Provide feedback loops to measure system performance
- Increase speed and efficiency of change implementation
Automation for reliability improvement
SRE employs policies and processes that bake reliability into every step of the delivery pipeline. Some automatic problem-resolution strategies include:
- Developing quality gates based on service-level objectives to detect issues earlier
- Automating build testing using service-level indicators
- Making architectural decisions that ensure system resiliency at the outset of software development
What is observability in site reliability engineering?
It’s a journey that gets the software team ready for uncertainty once the software is live with end users – in the form of SRE tools that can detect anomalous software behaviours from early warning indicators, and (much more importantly) collecting data from the observed processes that would allow the developers to understand and diagnose the root cause of the problem. Here’s what that journey entails, as far as the collection of information goes:
- Metrics: A metric is a quantifiable value that reflects how an application is performing or the status of a system. SRE teams look at metrics to evaluate whether their software is slurping up their memory or acting up.
- Logs: SRE software creates highly detailed, timestamped event logs in reaction to specific events. When software engineers dig through such event logs for patterns, they’re often asked to trace the fault through itself.
- Traces: Traces are messages that log the specific code path to complete a function in a distributed system. Checking out an order cart, for instance, might involve all of the following:
- Tallying the price with the database
- Authenticating with the payment gateway
- Submitting the orders to vendors
They consist of ID, name, and time; used by programmers to spot latency problems and make applications perform smoother.
What is monitoring in site reliability engineering?
Monitoring is the act of looking for pre-defined metrics in a system. Development staff agree on a content set of parameters to monitor – the parameters they believe are most helpful at assessing the health or status of the application. Then they configure the monitoring tools to track whether those parameters deviate by a significant margin. SRE operations staff track those key performance indicators (KPIs) and report that information in a graph.
In SRE, software teams monitor these metrics to gain insight into system reliability:
- Latency: Latency is the period of time that elapses between when an application receives a request and provides a reply. For instance, a webform submission might take three seconds before it completes and redirects the user to an acknowledgment webpage.
- Traffic: For example, traffic is the number of users actively using your service. Software teams use traffic to budget computing resources so that your service level – your users’ ability to use your service in a timely, error-free fashion – is consistent for everyone.
- Errors: A failure, in turn, is characterised by an error: a condition in which an application doesn’t do what it’s supposed to do, or succeed in producing what is requested of it. A web page that refuses to load, a bid that fails to go through, the loss of some data – these are all examples of errors that SRE teams track and address automatically with special software.
- Saturation: Saturation describes how much the application is busy at any given point in time. Saturation typically reduces the performance of an application. Site reliability engineers monitor saturation and make sure it is below a certain threshold.
What are the key metrics for site reliability engineering?
SRE teams use the following metrics for measuring quality of service delivery and reliability:
- Service-level objectives: These objectives are referred to as service-level objectives (SLOs). The SLOs you establish are specific and quantifiable, and you have confidence that the software can deliver them at a reasonable cost to the other metrics, such as those below:
- Uptime, or the time a system is in operation
- System throughput
- System output
- Download rate, or the speed at which the application loads
An SLO promises actual delivery to the customer: for instance, the food delivery app launched by your company has an SLO of 99.95 per cent uptime.
- Service-level indicators: Service-level indicators (SLIs) are the actual measurements of the metric that an SLO defines. In the real world, you could get either exactly the same amount of the ‘up’ calls as the SLO demands or you might well get less than that, like in the case where your application was up 99.92 per cent of the time, short of the agreed-upon SLO.
- Service-level agreements: The specifics of these service-level agreements (SLAs) are spelled out in the legal clauses of what should happen when one or more of your service-level objectives (SLOs) aren’t being met. The SLA might say, ‘If your technical team doesn’t solve your customer’s problem within 24 hours of it being reported, then we have to refund your customer their money.’ That might mean that your SLOs should suggest a target for that area of your work, and your team should have to pay up if they don’t hit the objective.
- Error budgets: An error budget describes how much an SLO can be violated. For example, if the SLO specifies an uptime of 99.95 per cent, the corresponding error budget is 0.05 per cent. If the error budget for software downtime is exhausted, then the software team puts all their resources and attention into bringing the application back to a stable state by relieving the source of the problem.
How does site reliability engineering work
SRE holds that you should have site reliability engineers in a software team. The SRE team specify your key metrics, and establish what’s called an error budget; that is, what the system is willing to allow in terms of error. If your error budget, which represents your ability to make mistakes and survive, is low, then the development team is free to roll out more features. But if errors exceed the error budget, you pack up and put new changes on hold. You find and eliminate the problems you already have.
For example, a site reliability engineer (SRE) uses a service to monitor performance statistics and to look out for unusual behaviour from the application. If something is wrong, the SRE team submits a report to the software engineering team. Developers fix reported problems and release the new application.
DevOps
DevOps is a kind of software culture that overcomes the traditional boundary between the development (Dev) and the operation (Ops) teams. We can no longer find the development team and the operation engineer as a pair of barrels or brothers. They originally develop software, deploy and maintain software with systematic software tools, and follow the trend of business model update in software update release frequency and speed.
SRE compared to DevOps
SRE is operationalising DevOps. DevOps provides the philosophical basis of what needs to happen to continue to establish the necessary level of software quality against a backdrop of an ever-decreasing time-to-market window. Site reliability engineering provides the answers to what needs to happen to have DevOps succeed. SRE assures that the DevOps team delivers on DevOps the right way (speed-of-release balanced against stability of the code base).
What are the responsibilities of a site reliability engineer?
Site reliability engineer is a system expert of IT through the method of software reliability monitoring and observing and intervention in the production environment. When software problems arise, they use automation tools to quickly identify and solve them. Former system administrator or operation engineer with good codibility would be excellent at one of these jobs. The following is the role of site reliability engineer:
Operations
In addition to designing, site reliability engineers spend up to 50 per cent of their time doing ‘ops work’, which involves:
- Emergency incident response
- Change management
- IT infrastructure management
The engineers use SRE tools to automate several operations tasks and increase team efficiency.
System support
SREs interact with the development team to build features and stabilise production systems; SREs define an SRE process, collaborate with development to build new features and stabilise their production systems, and are on call where engineers are forced to make field changes; SREs write procedures so that customer support can run the production service; SREs build runbooks to assist customer support agents in responding to valid complaints.
Process improvement
Site reliability engineers enhance the software development cycle via after-action post-incident reviews. The SRE team maintains a shared knowledge base detailing software incidents, along with their respective solutions, which will be a useful asset when the software team has to deal with similar issues in the future.
What are the common site reliability engineering tools?
SRE teams use various classes of tools to support monitoring, observation and incident response:
- Container orchestrator: A container orchestrator is used by software engineers to run containerized applications on different computing platforms. The source code files and resources required by an application are bundled within a self-contained package known as a container. For instance, Amazon Elastic Kubernetes Service (Amazon EKS) is used by software developers to run and scale cloud applications.
- On-call management tools: An on-call management tool is a type of software that SRE teams use to schedule, organise, and manage support staff who have the ability to respond to reports of software issues SRE teams might use the software to ensure that support staff are on standby to receive notifications of software anomalies.
- Incident response tools: An incident is something that needs to be addressed through an incident response tool that provides an escalation pathway for reported software issues. An incident response tool provides different severity levels for reported issues, and allows the SRE team to take appropriate courses of action, as well as provide post-incident analysis report to prevent incidents of similar type.
- Configuration management tools: Configuration management tools are software that automates the workflow of software; SRE teams use tools to eliminate the repetitive tasks in order to be more productive. For example, site reliability engineers use AWS OpsWorks to automate the provisioning and management of servers in AWS environments.
Where is Ansible used?
DevOps Dance Off
- Managing a server farm like it's a ballet - Ansible choreographs installations, updates, and all that jazz without missing a beat.
Configuration Conundrums
- Like Mary Poppins for your configs - Ansible swoops into your systems, straightening out settings with a spoonful of YAML.
Continuous Deployment Disco
- Ansible's the DJ in the house, spinning up the latest app versions to keep the party live in production environments. Groovy!
Security Salsa
- Ansible shakes its hips to security rhythms, enforcing policies and patching holes faster than you can say 'Cha Cha Cha'!
Ansible Alternatives
Puppet
Configuration management tool used for deploying, configuring, and managing servers. It automates repetitive tasks and enables deployment at scale.
node 'example.com' {
include apache
}
- Model-driven approach with dependency management.
- Comprehensive reporting and auditing features.
- High scalability due to compiled catalogs.
- Steep learning curve for new users.
- Slower than some competitors due to heavy design.
- Puppet code can become complex at scale.
Chef
It's a powerful automation platform that transforms infrastructure into code, allowing users to automate how they build, deploy, and manage their infrastructure.
package 'ntp' do
action :install
end
- Flexible with a strong community and mature product.
- Integration with major cloud providers.
- Robust tooling and testing frameworks available.
- Requires Ruby knowledge for advanced use.
- Initial setup and configuration can be involved.
- Master-agent model may not fit all environments.
SaltStack
Designed for IT automation, config management, and remote task execution. It uses YAML for its configuration files and is known for its speed.
httpd:
pkg.installed:
- name: apache2
- Fast and scalable due to asynchronous execution.
- Flexible and easily extensible through custom modules.
- Good for both configuration management and remote execution.
- Can be less intuitive than other configuration languages.
- Less mature than Puppet or Chef with a smaller community.
- Documentation can be less comprehensive.
Quick Facts about Ansible
The Birth of Ansible: One Man's Distaste for Complexity
In a world crammed with convoluted automation tools, one software engineer named Michael DeHaan decided he'd had enough. In 2012, he put on his coding cape and concocted Ansible. His mission was simple: make software automation a walk in the park. Little did he know, his creation would soon become the go-to for sysadmins who preferred sipping coffee over scripting nightmares.
Radical Simplicity: The Human-Readable Playbook Revolution
When Ansible strutted onto the scene, it flipped the script on the status quo. Before Ansible, automation scripts were as cryptic as hieroglyphics to the untrained eye. But with Ansible's human-readable YAML playbooks, even mere mortals could command complex deployments with a few keystrokes. Behold the power of simplicity:
---
- hosts: all
tasks:
- name: Say hello
ansible.builtin.debug:
msg: "Hello, simplicity!"
Sprinting Through Versions: From Baby Steps to Giant Leaps
Ansible hit the ground running and hasn't slowed down since. From its initial release, it sprinted through versions faster than a developer chasing pizza on release night. Each iteration brought new features, reaching milestones like the Ansible Tower in 2014, and by the time 2020 rolled around, the tool was at version 2.10, flaunting its ever-expanding capabilities and plugins by the dozens. Now, if only version updates were as smooth as Ansible's learning curve!
What is the difference between Junior, Middle, Senior and Expert Ansible developer?
| Seniority Name | Years of Experience | Average Salary (USD/year) | Responsibilities & Activities | Quality-wise |
|---|---|---|---|---|
| Junior | 0-2 years | $50,000 - $70,000 |
| Requires supervision and regular reviews. |
| Middle | 2-5 years | $70,000 - $95,000 |
| Consistent quality with occasional guidance. |
| Senior | 5-10 years | $95,000 - $120,000 |
| High quality, autonomous, sets standards. |
| Expert/Team Lead | 10+ years | $120,000 - $150,000+ |
| Exceptional quality, visionary, drives excellence. |
Top 10 Ansible Related Tech
YAML Ain't Markup Language (YAML)
So, you want to dabble in Ansible, huh? Well, saddle up partner, because YAML is the horse you're gonna ride! It's the backbone of Ansible Playbooks and pretty much looks like a grocery list that got a degree in computer science. You'll write tasks in YAML like you're dictating a letter to your computerized butler, telling it what you want done without the sass.
---
- hosts: webservers
tasks:
- name: Ensure the cow says hello
command: /usr/bin/cowsay 'Hello, World!'
Python
Let's be real, Python is the Swiss Army knife for, well, everything! For Ansible, it's like the wizard behind the curtain pulling all the levers. You'll need to brush up on your snake-charming skills if you want to contribute to Ansible's core code or write custom modules. It’s both beginner-friendly and as powerful as a love potion.
# Custom Ansible module in Python example
#!/usr/bin/python
from ansible.module_utils.basic import AnsibleModule
def run_module():
module_args = dict(
message=dict(type='str', required=True)
)
result = dict(
changed=False,
original_message='',
message=''
)
module = AnsibleModule(
argument_spec=module_args,
supports_check_mode=True
)
result['original_message'] = module.params['message']
result['message'] = module.params['message'][::-1]
module.exit_json(**result)
if __name__ == '__main__':
run_module()
Jinja2
Think of Jinja2 as the magical hat that pulls rabbits out of YAML files. It's the templating language for Ansible playbooks that helps you create configurations as unique as a snowflake in a Florida summer. Basically, it's where you add a sprinkle of logic to your otherwise static files, turning them into dynamic masterpieces.
# An example of a Jinja2 template
server {
listen 80;
server_name {{ inventory_hostname }};
root {{ nginx_root }};
}
Version Control Systems (Git)
You surely wanna keep track of the rollercoaster ride of changes in your Ansible code, right? Git is like the time machine for your codebase, allowing you to travel back when your code was still beautiful and bug-free. It's essential for collaboration, just like coffees are for early morning meetings.
# Clone an Ansible repository
git clone git@github.com:yourusername/ansible-playbooks.git
# Create a new branch for your changes
git checkout -b my-amazing-feature
Continuous Integration/Continuous Deployment (CI/CD)
Imagine deploying your code with the confidence of a squirrel jumping across trees – that's what CI/CD gives you. Tools like Jenkins, GitLab CI, and GitHub Actions let your code waltz gracefully into production after passing the test gauntlet. It’s the chess grandmaster in the realm of automation!
# A simple GitHub Actions workflow example for Ansible testing
name: CI
on: [push]
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Run Ansible Lint
run: ansible-lint .
Docker
Ah, Docker - the container maestro, making sure your Ansible playbooks can run in the same cozy environment across different machines. Think of containers as virtual lunchboxes for your apps – they keep everything nice, tidy, and consistent. No more "But it works on my machine!" excuses, okay?
# Run an Ansible playbook inside a Docker container
docker run --rm -v $(pwd):/ansible/playbooks ansible/ansible-runner ansible-playbook your-playbook.yml
Red Hat Enterprise Linux (RHEL)
Here's the thing: Ansible and RHEL go together like peanut butter and jelly. Red Hat's the parent of Ansible, so they've got some special bonding. If you're in a corporate setting, mastering RHEL will have people leaning on you like you're the last pillar in a crumbling temple.
Cloud Services
Cloud services like AWS, Azure, and GCP are like the golden buffets of the computing world. And Ansible? It's your VIP pass to automate deployments across these platforms. Conjure up servers in the cloud like a wizard casting spells, without even breaking a sweat. Abracadabra, instance provisioned!
Virtualization Tools (Vagrant, VirtualBox)
If you love fiddling with machines but hate the mess, virtualization tools like Vagrant and VirtualBox are your digital playgrounds. They're like playing the Sims but for servers - you can build, destroy, and rebuild virtual environments faster than you can say "Oops!" Perfect for testing out your Ansible escapades.
# Spin up a Vagrant box to use with Ansible
vagrant init ubuntu/bionic64
vagrant up
vagrant ssh
Monitoring and Logging Tools (ELK, Grafana)
Now you don't wanna just set up and forget your systems, do you? Monitoring and logging tools like ELK (Elasticsearch, Logstash, Kibana) Stack and Grafana are like the neighborhood watch for your infrastructure. They'll keep an eye on your setups, and alert if anything funky happens. It's like having a guardian angel for your servers – but with more graphs.