Site Reliability Engineer (SRE) with Terraform 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 Terraform 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 Terraform used?
Infra-as-Code Party Tricks
- Spinning up a herd of servers faster than a microwave popcorn during a Netflix binge.
- Playing multi-cloud hopscotch with your entire application stack, no sweat or tears involved.
- Laying out network topologies like a spider spins its web, with precision but without getting tangled.
- Version-controlling the cloud as if it's a video game save point - reload when the boss level gets too tough.
Terraform Alternatives
Pulumi
Pulumi is an infrastructure as code tool that allows developers to define and deploy cloud resources using familiar programming languages such as JavaScript, TypeScript, Python, Go, and .NET.
- Uses real programming languages.
- Supports multi-cloud configurations.
- Brings familiar test practices to IaC.
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const bucket = new aws.s3.Bucket("my-bucket", {
acl: "private",
});
- Slightly steeper learning curve for IaC newbies.
- Diverges from declarative approach of Terraform.
- Tooling and editor integration might be less mature.
CloudFormation
AWS CloudFormation provides a declarative way to outline AWS infrastructure using a template made up of JSON or YAML.
- Native integration with AWS Services.
- Supports rollback of changes if deployments fail.
- Built-in drift detection.
Resources:
MyBucket:
Type: AWS::S3::Bucket
Properties:
AccessControl: Private
- AWS-specific; not suitable for multi-cloud.
- Templates can be verbose and complex.
- Less flexible compared to Terraform Modules.
Ansible
Ansible is a configuration management tool that can also be used for orchestration or as an IaC tool, focusing on automation using YAML-based playbooks.
- Agentless; manages nodes over SSH.
- Extremely simple to set up and use.
- Large, supportive community and plenty of modules.
- hosts: servers
tasks:
- name: ensure the S3 bucket exists
aws_s3:
bucket: mynewbucket
mode: create
- Less suited for complex orchestration.
- Imperative approach might lead to drift in state.
- Performance can degrade with large inventories.
Quick Facts about Terraform
Once Upon a Manual Laborland...
In the dark ages of 2014, a wizard named Mitchell Hashimoto conjured up a spell called Terraform. Yeah, you heard it right, in the IT realm, four years is akin to a century ago! Poof, and suddenly infrastructure became code. I mean, who needs wands and broomsticks when you can just write down what you want your cloud kingdom to look like and abracadabra, it's done!
Upgrading the Spellbook
With great power comes great responsibility... and a bunch of updates! Terraform didn't just stay put; it evolved faster than a rabbit population. By 2021, it had shape-shifted into version 1.0, looking all spiffy and stable, promising those who practice the arcane arts of DevOps a 'backward compatibility' charm. That's code for "We won’t break your stuff with updates," which, as you know, is quite the pledge in the software sorcery world.
The Incantation Syntax
Eloquent as Shakespeare and structured like a LEGO set, Terraform's language, HCL (HashiCorp Configuration Language), was designed to describe the end state of your infrastructure with the clarity of a tropical lagoon. It's both human and machine-friendly, so even the robots can't complain. Seek and ye shall find! Behold, the sacred script to summon an S3 bucket:
resource "aws_s3_bucket" "bella_bucket" {
bucket = "my-supercool-bucket"
acl = "private"
}
What is the difference between Junior, Middle, Senior and Expert Terraform developer?
| Seniority Name | Years of Experience | Average Salary (USD/year) | Responsibilities & Activities |
|---|---|---|---|
| Junior | 0-2 | 50,000 - 70,000 |
|
| Middle | 2-4 | 70,000 - 100,000 |
|
| Senior | 4-6+ | 100,000 - 130,000 |
|
| Expert/Team Lead | 7+ | 130,000 - 160,000+ |
|
Top 10 Terraform Related Tech
HCL (HashiCorp Configuration Language)
Picture yourself crafting a love letter, but instead of professing your undying affection, you're sweet-talking a server setup. That's HCL for you – the poetry of Terraform configuration! Intuitive as a pet following crumbs, HCL's got a JSON-compatible sheen, making your Infrastructure as Code endeavors a walk in the park. A harmonious blend of human-readable meets machine-efficient, HCL lets your infrastructure bloom like a well-watered Chia Pet.
resource "aws_instance" "example" {
ami = "abc123"
instance_type = "t2.micro"
}Version Control Systems (Git)
Git, the safety net for your coding high-wire act, captures every somersault of your Terraform code. Commit by commit, branch by branch, it guards against the "Whoops, shouldn't have deleted that" fiasco. Git also pairs with Terraform like peanut butter with jelly, ensuring your infrastructure recipes can be versioned, tracked, and shared – just shy of slapping a bow on it and calling it a gift.
git add .
git commit -m "Add initial Terraform config for a new VPC"
git push origin mainContinuous Integration/Continuous Deployment (CI/CD)
CI/CD platforms, like juggling while unicycling, keep the Terraform deployment balls beautifully airborne. Jenkins, GitLab CI, and GitHub Actions let you push updates without breaking a sweat or the infrastructure. Automate your Terraform plan and apply, and you can sit back, relax, and watch as your code gets deployed like clockwork-powered cupcakes on a conveyor belt!
pipeline {
agent any
stages {
stage('Terraform Init') {
steps {
sh 'terraform init'
}
}
}
}Cloud Service Providers (AWS, GCP, Azure)
If Terraform is your orchestra conductor's baton, cloud service providers are the symphony – vast, powerful, and ready to perform. Whether you’re spinning up instances in AWS, networking in Azure, or databasing in GCP, Terraform scripts are the sheet music for your cloud performance. Just strike up the band and watch as your configurations turn cacophonous resource provisioning into harmonious melodies.
resource "aws_vpc" "main" {
cidr_block = "10.0.0.0/16"
}Infrastructure as Code (IaC) Tools Comparison (Pulumi, CloudFormation)
While Terraform reigns supreme in the IaC kingdom, a court of competitors like Pulumi and CloudFormation vie for the crown. Pulumi speaks your favorite programming language, letting you whisper sweet nothings to your infrastructure using actual code. CloudFormation, Amazon's loyal knight, valiantly automates AWS resource dance moves. Knowing the strengths and party tricks of each can elevate your IaC waltz to a full-on boogie.
Monitoring & Logging Tools (Datadog, Splunk)
Monitoring tools like Datadog and Splunk are your infrastructure's babysitters, keeping an eagle eye on them while you're away. They ensure your setups don't throw wild parties, alerting you if the CPU usage spikes from doing the Macarena or if the memory consumption gets out of control trying to beatbox. Groove to the rhythm of your metrics and logs as these tools lay down the beat.
Container Orchestration (Kubernetes, Docker)
Kubernetes is the grand puppet master of containers, skillfully orchestrating your Docker darlings across a stage of servers. It ensures each container plays its part seamlessly, whether it's the prima donna front-end or the sturdy back-end bass. Combined with Terraform, deploying these container performances becomes as smooth as a Broadway show tune.
Configuration Management Tools (Ansible, Chef)
Imagine your infrastructure as unruly hair, and Configuration Management tools are the combs and gels bringing it to a slick pompadour. Ansible scripts are like gentle strokes, soothing your servers into uniformity. Chef, with its recipes and cookbooks, whips up a gourmet dish of automated settings. Terraform lays the canvas, and these tools paint the final polish.
Scripting Languages (Bash, Python)
Scripting languages are your Swiss Army knife in a jungle of tasks. Need to automate a chore? Bash it. Want to parse some complex output? Python it. When your Terraform deployment scripts need that extra sprinkle of logic or a dollop of decision-making, these tried and true comrades are ready to jump into the fray, torches blazing!
# Bash script to initialize Terraform
terraform init
terraform plan -out=tfplan
terraform apply "tfplan"Terraform Modules and Registries
Terraform modules are like Lego blocks for cloud architecture, snapping together to create infrastructural masterpieces. With modules, repetition becomes a relic. Simply piece together pre-configured constructs, and you're well on your way to build whatever your heart desires, from a cloudy fortress to a server village. And the Terraform Registry? It's the toy store shelves stocked with every module under the sun – ready for your grabbing.