Hey everyone,

Looking for some perspective from senior engineers or architects who have managed to build a side income or solo business on the side.

Here's my dilemma. I'm currently with a large UK firm. My day-to-day involves high-level system design, multi-region architecture, platform engineering, and enterprise governance.

I'd love to start a side business (father of 2 and another one's on the way). Naturally, leveraging my background would be ideal, though I'm open to other areas. And honestly, it doesn't even have to be about tech as long as it makes money.

​

Hey everyone,

I've been in IT for around 12–13 years and lately I've been questioning where I should take my career next.

I started in software packaging and installer development, moved into build and release engineering, and eventually DevOps. For the past couple of years, I've been working as a Product Owner for a DevOps team at a large enterprise.

My technical experience includes Python, CI/CD, Docker, Kubernetes, Azure, virtualization, and infrastructure automation. However, much of this has been within enterprise-specific environments rather than modern cloud-native setups.

One of the more interesting projects I've recently worked on was a large-scale migration from VMware vSphere to OpenShift Virtualization, involving hundreds of VMs across multiple teams.

I was involved in migration planning, technical discussions, troubleshooting VM compatibility issues, understanding network and storage dependencies, coordinating migrations, and validating workloads.

I genuinely enjoyed the technical aspects of this project, particularly understanding how everything fits together and solving infrastructure problems.

Here's where I'm struggling.

Despite my overall experience, I sometimes feel my technical depth isn't where it should be.

I've worked across several areas, but I wouldn't consider myself an expert in any particular technology.

My current PO role involves a lot more planning, coordination, and stakeholder management than actual engineering.

While I understand the importance of those responsibilities, I've realized I enjoy hands-on technical work much more.

I'm considering moving back into a technical role, particularly DevOps, SRE, or Platform Engineering.

I'm also curious about AI Infrastructure, MLOps, and LLMOps. With my background in Kubernetes, automation, and infrastructure, I'm wondering whether supporting AI workloads could be a reasonable direction without having to completely start over.

A few questions for people working in these areas:

1. How realistic is it to move back into hands-on engineering after spending a couple of years in a PO role? Have any of you made a similar transition?

2. How relevant is experience with enterprise infrastructure projects like VMware-to-OpenShift migrations when moving into Platform Engineering or SRE?

3. For someone with a DevOps/infrastructure background, is AI Infrastructure or MLOps a sensible direction? What additional technical skills would actually matter?

4. If you were in my position, would you focus on becoming stronger in traditional DevOps/Kubernetes first, or start exploring AI infrastructure alongside it?

I'm not looking to chase every new technology or jump into AI simply because it's trending.

I want to build deeper technical expertise and work on problems I genuinely enjoy.

I'd especially appreciate perspectives from people who've moved between DevOps, SRE, Platform Engineering, and AI infrastructure.

Thanks!

Hey everyone,

Looking for some perspective from senior engineers or architects who have managed to build a side income or solo business on the side.

Here's my dilemma. I'm currently with a large UK firm. My day-to-day involves high-level system design, multi-region architecture, platform engineering, and enterprise governance.

I'd love to start a side business (father of 2 and another one's on the way). Naturally, leveraging my background would be ideal, though I'm open to other areas. And honestly, it doesn't even have to be about tech as long as it makes money.

Found some hot new Devops roles and wanted to share them here before they disappear. Check them out!

• Senior Reliability Engineer – Power Semiconductor Reliability @ Renesas Electronics

  • 💰 $138–173K/y

• Senior DevOps Engineer @ Endava

• Senior Build Reliability Engineer @ Varda Space Industries

• Cloud/DevOps Engineer - Hybrid @ Tenet3

• Vulnerability Management Platform Engineer @ Northern Trust Company

• Site Reliability Engineer ll @ ResMed (Malaysia) Sdn. Bhd.

• Staff Software Engineer, Reliability Engineer- Order Up (Remote) @ HOME DEPOT MANAGEMENT COMPANY, LLC

  • 💰 $120–190K/y

• Senior DevOps Engineer - Top Secret @ GD Information Technology, Inc.

  • 💰 $128–173K/y

• Senior DevOps Developer @ The Boeing Company

  • 💰 $137–185K/y

• Sr Platform Engineer (GitLab practice) @ INflow Federal

  • 💰 $150–250K/y

• RKS Configuration Management and DevOps, AVP @ SS CORP SVCS MUMBAI PVT LTD

  • 💰 $90–158K/y

• Senior Staff Platform Engineer - Kubernetes - Federal @ ServiceNow

• Data Platform Engineer @ Domino's

• SDK Platform Engineer @ Faraday Future

  • 💰 $80–120K/y

• OT/SCADA Deployment Engineer @ MetroSys

• Senior Plant Reliability Engineer @ Kairos Power

• Senior DevOps/SRE Engineer @ Oddball

  • 💰 $120–156K/y

• Site Reliability Engineer (DevOps) @ Accenture Federal Services

  • 💰 $112–222K/y

• Reliability Engineer II @ ICON

• Senior Embedded Build and release Engineer @ Intuitive

  • 💰 $169–243K/y

• Lead Site Reliability Engineer @ UnitedMasters | Translation

  • 💰 $195–240K/y

• Lead Site Reliability Engineer @ UMT - Internal

• Principal Software Engineer – Platform Engineering @ AlphaSense

  • 💰 $246–339K/y

• Application Deployment Engineer @ Intradiem

• Equipment Reliability Engineer (Starlink/Akoustis) @ SpaceX

• Manager, Supercomputer Site Reliability Engineering - Memphis @ xAI

• Full-Stack Platform Engineer @ Alpaca

• IoT Platform Engineer @ Bright Vision Technologies

  • 💰 $130–150K/y

• Founding Platform Engineer @ MLabs

• Site Reliability Engineer @ Matternet

  • 💰 $160–205K/y

• DevOps Platform Engineer/Linux Systems Administrator @ LEIDOS INNOVATIONS UK LTD.

  • 💰 $87–157K/y

• DevOps Engineer @ Booz Allen Hamilton_United States

  • 💰 $78–176K/y

• Sr. Engineer, Site Reliability @ T-Mobile USA, Inc.

• Staff AI Platform Engineer @ Abbott Diabetes Care Inc

  • 💰 $129–259K/y

• Senior MongoDB Database Platform Engineer @ Integon Services Co

  • 💰 $98–168K/y

• Senior Director - Platform Engineering @ Marvell Israel (MISL) Ltd

  • 💰 $213–319K/y

• Staff Platform Engineer - Materia AI @ IND Thomson Reuters International Services Private Limited

  • 💰 $158–293K/y

• Senior Site Reliability Engineer II @ Waystar

• Director, Platform Engineering @ Mastercard

  • 💰 $152–258K/y

• DevOps Engineer III @ MP Newton

• Senior Platform Engineer - ClickHouse @ Qualys

  • 💰 $125–145K/y

• DevSecOps Engineer @ University of Chicago

  • 💰 $80–120K/y

• Platform Engineer - Internal Developer Platform & Developer Experience @ Wellmark, Inc.

• Senior Platform Engineer @ Defense Unicorns

  • 💰 $149–201K/y

• Senior Trading Systems DevOps Engineer @ FalconX

  • 💰 $179–226K/y

If this list helped, hit the like button and let me know which roles you want next.

have around 2 years of experience in DevOps with a CTC below ₹8 LPA.

My goal is to reach ₹15–20+ LPA in the next 2 years.

For those who have achieved this or are already earning in this range:

Which skills should I focus on?

Which technologies are most valuable in the current job market?

How should I prepare for interviews?

What kind of projects and experience do companies expect?

What strategy helped you achieve a significant salary jump?

**Please share your practical experience and roadmap. I want to learn from people who have already made this journey

Does anyone have any recommendations on where the best place is to find AWS devops freelancers? What is the going day/hour rate for a local Melbourne freelancer. I am looking to hire someone for a SaaS project with occasional on-site deployment. Mostly to help manage, monitor, and support our AWS infrastructure for uptime, security, and performance

I’m currently working in a remote cloud migrations role that pays 100k, but my company’s recurring layoffs have me concerned about job stability. I have about six years of IT experience across help desk, system administration, and cloud roles, along with Azure, Google Cloud, CCNA, and CompTIA certifications. Devops seems like the most likely progression, but requires a lot more to learn than my current role since I don't use Terraform or Kubernetes. I have tried learning both on my own, but learning them on your own can be vastly different than on the job.

I’m trying to decide whether to apply for DevOps/cloud engineering roles or transition into data analytics. I’m concerned that DevOps might be heavily focused on software engineering and could involve intense technical interviews, a broad range of technologies, and potentially on call responsibilities. On the other hand, I’ve noticed that some data analytics positions prefer or require a master’s degree, which makes me wonder how difficult it would be to break into the field with my current qualifications and a bachelor’s degree in a different non tech field. Will I need to go back for a tech specific bachelors or masters for Devops or Data Analytics.

Would switching to analytics make sense, or would I be better off applying to devops roles? Some friends have to told me to switch to data analytics because the interviews would be easier, and I wouldn't have to deal with on call work. However, I would have to take a pay cut, and I'm not sure if I could even get a data analytics interview or if they will be too picky because I have not worked in an analytics role. I know SQL, Excel, and some Tableau. So, I'm familiar with what is needed. I'm just worried if my resume will even get pushed through to an interview.

Our client is a leading technology-driven organization leveraging cloud infrastructure, artificial intelligence, and large-scale data platforms to deliver innovative digital experiences. The company operates complex, high-availability systems and promotes collaboration across international engineering teams.

We are looking for an experienced DevOps Engineer to support the development, deployment, and operation of a large-scale AI-powered personalization platform. The ideal candidate has strong expertise in Linux, cloud infrastructure, automation, and container orchestration, with a proven track record of maintaining reliable production systems.

In this role, you will collaborate with software engineers, data scientists, and infrastructure specialists to improve platform scalability, automate delivery processes, and ensure high availability across cloud and on-premises environments. This is an excellent opportunity for an engineer who enjoys solving complex technical challenges and driving continuous improvements in infrastructure reliability and operational efficiency.

Key Responsibilities

Platform Operations

• Operate, maintain, and continuously improve production infrastructure supporting large-scale recommendation and personalization services.
• Participate in production operations, incident response, root-cause analysis, and service recovery.
• Establish operational standards and improve service reliability and maintainability.

Infrastructure Engineering

• Design, implement, and manage scalable, highly available, and fault-tolerant infrastructure across public cloud and on-premises environments.
• Optimize infrastructure performance, resource utilization, and operational costs.
• Support the deployment and operation of distributed applications and data-intensive workloads.

Automation & Continuous Delivery

• Develop and maintain CI/CD pipelines to improve the speed, consistency, and safety of software releases.
• Implement infrastructure as code and configuration management practices.
• Automate repetitive operational tasks using scripting and software engineering best practices.

Monitoring & Reliability

• Build and maintain monitoring, logging, alerting, and observability solutions.
• Define and improve operational metrics to identify performance bottlenecks and prevent service disruptions.
• Troubleshoot complex issues involving applications, infrastructure, networking, and distributed systems.

Cross-functional Collaboration

• Work closely with software engineers, data scientists, and platform engineering teams to bring AI models and services into production.
• Coordinate with cloud, network, and infrastructure teams to resolve technical challenges and improve platform capabilities.
• Share technical knowledge and contribute to engineering standards across geographically distributed teams.

Continuous Improvement

• Evaluate emerging technologies, tools, and operational practices.
• Identify opportunities to improve automation, reliability, scalability, and engineering productivity.
• Contribute to the evolution of infrastructure supporting real-time processing and deployment across multiple regions.

Technical Environment

• Programming & Scripting: Python, Groovy, Shell scripting
• Cloud & Infrastructure: Google Cloud Platform (GCP), Linux, on-premises infrastructure
• Containers & Orchestration: Docker, Kubernetes
• Infrastructure Automation: Terraform, Ansible, Infrastructure as Code
• CI/CD: Jenkins, GitLab CI/CD, Cloud Build
• Monitoring & Logging: Prometheus, Grafana, ELK Stack
• Data & Distributed Systems: Apache Spark, Apache Kafka, NoSQL databases

Required Qualifications

・Bachelor's degree or above in Computer Science, Computer Engineering, System Administration or a related technical field.

・More than 5 years of experience in building, deploying and operating production-grade services. (Ideally 7+ years of professional experience)

・Strong experience with Linux systems and shell scripting.

・Experience with automation and infrastructure-as-code tools (e.g., Terraform, Ansible, Chef).

・Experience with CI/CD tools (e.g., Jenkins, GitLab CI/CD, Cloud Build).

・Experience with containerization and orchestration (Docker, Kubernetes).

・Hands-on experience with a major cloud platform, preferably GCP (More than 3 years).

・Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).

・Knowledge of distributed systems and high-availability architectures.

・Good understanding of networking fundamentals.

・Awareness of good development practices (pull requests, unit tests, continuous integration and delivery).

・Business-level communication skills in English, and the ability to work in an international, distributed team of senior engineers.

Preferred Qualifications

・Scripting or development experience in Python, Scala, Java or Ruby.

・Previous experience with Spark, Kafka, Couchbase or Redis.

・GCP Professional Cloud Engineer or equivalent certification.

・Contributions to open-source projects.

・Interest in data analytics, machine learning and personalization systems.

Working Environment

Fast-paced, dynamic global environment with collaborative teams across multiple locations

Salary: ¥9M – ¥12M JPY per year (Senior Level)
Location: Hybrid (4 days in the office, 1 day remote)
Office Location: Tokyo, Japan
Working Hours: Flexible schedule with core hours from 11:00 AM to 3:00 PM
Visa Sponsorship: Available
Language Requirement: English only

Apply now or contact us for further information:
[Aleksey.kim@tg-hr.com](mailto:Aleksey.kim@tg-hr.com)

Hey everyone,

Prepping for HashiCorp Terraform Associate (004) and CKA next. I have a solid background in Linux, networking, Docker, and backend, but no formal "DevOps Engineer" title on my resume.

I know certs alone aren't enough, so I'm building a proper GitHub repo (IaC modules, K8s cluster setup, CI/CD, and monitoring).

However, looking at the current job market, almost nobody is hiring entry-level / Junior DevOps engineers—companies want Mid/Senior with 3+ years of experience.

For hiring managers or folks who made this transition recently:

1. Does CKA + Terraform + GitHub portfolio actually help clear HR filters for Junior/Mid roles, or is lack of paid experience a total dealbreaker?
2. What’s the most realistic entry path today if entry-level positions are non-existent (targeting Mid directly, Cloud/SysAdmin/Support first, etc.)?

Appreciate any honest feedback!

We looked at 3,518 open job postings across 81 companies' public Greenhouse boards, covering seven job categories. The goal was simple: find out which keywords employers actually use.

A few findings stood out.

• Software engineering: Mentoring appeared in nearly half of the postings, more often than Kubernetes or React. Python was the most frequently mentioned programming language.
• Product management: More than 85% mentioned roadmaps. Jira appeared in just 7 of 421 postings.
• Marketing: Google Ads showed up in only 6 of 347 postings, while pipeline appeared in more than half.

We also noticed a pattern across roles: employers often described the practice rather than naming a specific tool. Observability came up where you might expect Grafana, and SIEM where you might expect Splunk.

What does this mean for your resume?

If you're listing tools but leaving out the responsibilities, practices, and skills explicitly mentioned in the job description, you could be missing relevant keywords.

That doesn't mean stuffing your resume with buzzwords. It means describing your actual experience using language that matches the role you're applying for.

One important caveat: the sample leans heavily toward tech companies and uses a single ATS platform, so these results aren't representative of every employer.

The full study, including findings for sales, cybersecurity, DevOps, and accounting, is here:

https://www.zoevera.com/resume/ats-resume-keyword-study

We are building AI to simulate the world through merging art and science.

We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.

World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.

Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.

About the role

We're looking for an ML infrastructure engineer to own model evaluation at Runway, end to end. Every decision we make about a model – which checkpoint to keep training, what to ship to millions of users, which datamix and architecture shows the most promise – rests on evals. Today that work is spread across the organization. You'll turn it into one platform.

Your job will be to design and build the systems that generate samples at scale, score them with automated metrics and human annotations, track results across checkpoints and releases, and put the answers in front of researchers in minutes rather than days. You'll define what "better" means operationally – how we measure it, how confident we are, and how a result becomes a ship/no-ship decision.

You'll be embedded within research teams as a member of ML Platform, and you'll set the technical direction for evals across the company. This is an extremely high-leverage role: the quality of our models is bounded by how well we can measure them.

A peek at our technical stack

Our inference and training code is written in Python (PyTorch) and is cloud‑native. We leverage multiple clouds and use a combination of Kubernetes native and home‑grown tooling for efficient job orchestration.

We’re big users of agentic development and operations. We have a robust internal platform and provide broad access to the latest models and harnesses.

You’ll have access to best‑in‑class models, agents, GPUs, storage and cloud services you need to drive a world class evaluation pipeline that helps us deliver frontier models.

What you’ll do

• Own the evaluation platform end to end: the tooling and systems required to generate, annotate, review and adapt at frontier scale
• Define the CLIs, APIs, GUIs and storage layers required to make this process seamless, fast, sophisticated and collaborative
• Work directly with research teams on video, image, audio, agents, and robotics to understand what they need to measure and build it, then generalize the result into the platform
• Help set the standards for how we evaluate models at Runway: reproducibility, metric definitions, reporting formats, and when a result is trustworthy enough to act on
• Support broad adoption of the platform and its integration throughout Runway’s research efforts across training, production model serving and more
• Contribute broadly as a member of the ML Platform team to tools and systems that help Runway train and serve frontier models

What you'll need

• 5+ years of experience building ML infrastructure or data platforms in production environments, with at least some of that time spent on evaluation, experimentation, or benchmarking systems
• Strong Python and PyTorch, and hands‑on experience running large batch GPU workloads on Kubernetes
• Experience designing data pipelines and storage for large volumes of media or model outputs, with attention to versioning and reproducibility
• Familiarity with experimental statistics: paired comparisons, confidence intervals, multiple‑comparison pitfalls, inter‑rater agreement
• Comfort building internal tools end to end, from the command line to the browser
• Ability to lead a broad technical area: gather requirements from many teams, set direction, make tradeoffs, and drive a roadmap without waiting to be told
• Familiarity with the full model development lifecycle: data, training, evaluation, serving
• Self‑starter who can work embedded with research teams and move fast
• Strong systems thinking and pragmatic approach to production reliability
• Humility and open mindedness; at Runway we love to learn from one another

Nice to have

• Track record of building evaluation suites for generative models
• Hands‑on work with LLM‑or VLM‑as‑judge pipelines
• Experience with online experimentation platforms and connecting offline metrics to product outcomes
• Prior work evaluating agents or robotics policies

Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.

There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.

Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.

Apply: Member of Technical Staff, ML Platform at Runway

I’m a DevOps Engineer from LATAM with 7+ YOE, currently making around $53k USD/year.

I’ve been testing the market lately, and most opportunities seem to fall within the $36–54k range, with very few offering more.

For those making $80–100k+ while based in LATAM, how did you get there?

What’s your experience, technical expertise, and how did you land your role?

Any advice for those of us trying to break past that salary ceiling?

[Hiring] Recrutez pentru mai multe roluri IT în București – Go, Kubernetes, Cloud, Security, Java, Engineering Management

Salutare tuturor! 👋

Sunt recruiter IT și în perioada aceasta lucrez la câteva oportunități tehnice pentru echipe internaționale, în special în zona de Cloud Infrastructure, Software Engineering, Platform Engineering și Cybersecurity.

M-am gândit să le las și aici, poate sunt persoane interesate sau cunoașteți pe cineva care ar fi potrivit.

📍 Locație: București (modalitatea de lucru diferă în funcție de rol)

1. Engineering Manager – Cloud Platform

• Go (Golang), Kubernetes, Cloud Infrastructure
• Technical Leadership & People Management
• Experiență cu sisteme distribuite și platforme cloud
• Potrivit pentru Engineering Managers sau Tech Leads cu experiență hands-on

2. Senior Cloud Engineer

• Go (Golang), Kubernetes, Linux
• OpenStack, Terraform, Infrastructure as Code
• Cloud Infrastructure, automatizare și sisteme distribuite
• Experiență solidă în Platform Engineering / DevOps

3. Senior Cloud Security Platform Engineer

• Kubernetes Security, OpenStack, Linux Security
• Go/Python, Terraform, HashiCorp Vault
• SIEM/EDR, SentinelOne, Kyverno/OPA, eBPF
• Cloud Security, DevSecOps și Security Automation

4. Senior Software Engineer – Cloud Infrastructure (IaaS)

• Go / Golang, Cloud Infrastructure
• OpenStack, Kubernetes, Linux
• API Development, Distributed Systems, Automation
• Dezvoltarea și scalarea serviciilor de infrastructură cloud

5. Senior Software Engineer – Java

• Java, Spring Boot, AWS, Kubernetes
• Microservices și sisteme enterprise
• Germană B2+ obligatorie
• București, hybrid

6. Test Architect / QA Architect

• Test Architecture & Automation
• Test Strategy, CI/CD, Quality Engineering
• Experiență în proiecte software complexe și colaborare cu echipe tehnice

Ce este important de știut?

✅ Roluri cu responsabilități tehnice complexe și oportunități de dezvoltare

✅ Echipe internaționale și tehnologii moderne

✅ Senioritatea și cerințele exacte diferă în funcție de poziție

✅ Pot oferi mai multe detalii despre proiect, responsabilități, beneficii și procesul de recrutare în privat

Dacă unul dintre roluri vă atrage atenția, îmi puteți scrie direct în DM, cu rolul care vă interesează și, dacă aveți, un profil LinkedIn sau GitHub.

Nu trebuie să fiți neapărat în căutare activă. Putem avea și o discuție exploratorie.

De asemenea, dacă știți pe cineva cu experiență în Go, Kubernetes, OpenStack sau Cloud Security, recomandările sunt binevenite.

Mulțumesc și spor la coding! 🚀

Hi there i am freshly graduated and looking for a job in devops/cloud i have done projects in my internships where i touched many things like
SSO Entra ID configuration of sonarqube
Security best practices: Identity Federation to authenticates ci/cd to ARM
Devsecops with (DAST) Owasp ZAP to scan authenticated backends and SAST with SonarQube
Deployment of initila config with terraform and helm chart on aks
I did the gateway api and DNS records , debugging is inmy skill
i did migration of Ingress nginx to gateway api with envoy since it's goiing to be deprecated

I did automation to generate test cases in jira with ai through pythin and ai token

in my personal projects:
i worked on SRE with Grafana and prometheuse, sending aletrs through emails whenever there is something wrong to us

built a k8s from ec2 instances to understand how things work

i have certs:
- AWS SAA - AZ-104 - RHCSA - RHCE(completed a course)

But i still can not find a job in devops
please dm me if anyone can help find a decent job
location: Morocco + Europe if there is visa sponshorship

Hi everyone!

We’re looking for a motivated Web Developer for remote freelance work involving website development, improvements, and technical tasks.

Responsibilities

• Develop and improve website features
• Fix bugs and troubleshoot issues
• Work with frontend or backend technologies as needed
• Test functionality and maintain code quality
• Communicate progress and follow project requirements

Requirements

• Knowledge of HTML, CSS, JavaScript, and relevant frameworks
• Understanding of responsive design and debugging
• Good problem-solving skills
• Ability to meet deadlines
• A portfolio or GitHub examples are welcome

Work type: Remote freelance
Experience: Entry-level and experienced applicants welcome
Compensation: [10 to 18$]

How to apply

Please message me with your experience, technical skills, portfolio/GitHub, availability, and expected rate. Shortlisted candidates may be asked to complete a clearly explained skills assessment as part of the selection process

Thank you!

I'm interested in how candidates prepare for practical DevOps and Linux interviews.

Imagine you're asked to investigate one of these situations:

• A Linux server suddenly shows high CPU usage.
• A production service is down, but the process is still running.
• A Docker container keeps restarting.
• An EC2 instance is unreachable over SSH.
• An application cannot access an S3 bucket.
• A Bash script fails when run through cron but works manually.

Which scenario would you find most challenging, and what would you investigate first?

I'm exploring ways to help candidates practise these kinds of questions in mock interviews, including Linux, Production Support, Docker, AWS (EC2, EKS and S3), and Bash/python scripting

I'd love to hear what candidates are struggling with most right now.

DEVOPS ENGINEER ******** Services (SaaS Platform) | Jan 2020 - Present

Architected a custom dynamic content caching strategy using a third-party CDN to front AWS infrastructure, slashing AWS data egress fees and reducing origin load by 25%.

Slashed customer environment provisioning time from 30 minutes to under 5 minutes by developing a Python serverless onboarding API utilising AWS Lambda and API Gateway.

Built and operated hardened production Amazon EKS environments, managing secure RBAC, ingress controllers, autoscaling, and node lifecycles to guarantee infrastructure reliability and scalability.

Engineered an Ansible powered Internal Developer Platform (IDP) that automated Docker provisioning with self-configuring reverse proxies, automated SSL renewals, and container self-healing.

Applied a defensive engineering mindset to production operations, treating every infrastructure update as a potential failure vector; designed automated rollback mechanisms and strict canary testing that significantly minimised deployment blast radiuses.

Provisioned and managed multi-environment AWS infrastructure using modular, reusable Terraform code, successfully eliminating configuration drift and enforcing deployment consistency.

Automated CI/CD and GitOps delivery via GitHub Actions and Argo CD, shifting security left by embedding policy engines, SAST, DAST, and container vulnerability scanning into the release pipeline.

Eliminated repetitive operational tasks by developing a comprehensive library of reusable Python and Bash scripting tools, streamlining troubleshooting and incident response triage.

Maintained 99.99% application availability by engineering comprehensive monitoring and alerting topologies across AWS and EKS environments using Prometheus, Grafana, and CloudWatch.

Guaranteed an aggressive 1-hour RPO and 30-minute RTO by implementing automated hourly backup pipelines and regularly executing simulated disaster recovery restore workflows.

Developed a Django based customer onboarding platform integrated with Stripe payments, seamlessly handling 2,500+ monthly active users and streamlining registration pipelines.

can i get a job with Azure sertificate as a junior devops engineer ? help me guys, need your advices

Hi everyone!

I'm currently looking for my first opportunity in IT infrastructure and would really appreciate any job leads, referrals, or guidance from this community.

My background:

\- BBA graduate with 1.5 years of professional experience in operations at Cotiviti India.

\- Completed Linux System Administration training (RHCSA-level) and Cloud & DevOps training.

\- Hands-on practice with RHEL, VMware, AWS EC2, Ansible, Git/GitHub, Bash scripting basics, users and permissions, LVM, SELinux, firewalld, systemd, and troubleshooting.

\- Worked on Linux and cloud-related hands-on projects as part of my learning.

Roles I'm looking for:

\- Junior Linux System Administrator

\- Linux Support / Linux Engineer (Fresher)

\- Junior DevOps Engineer

\- Cloud & DevOps Intern / Trainee

\- Junior System Administrator

I'm primarily looking for fresher-friendly roles that offer an opportunity to learn and grow. I'm open to opportunities across India, including Kerala, Bangalore, Chennai, Hyderabad, and other locations.

If your company has any suitable openings or you could refer me to a relevant role, I'd be very grateful. Any advice from people who started their careers in Linux or DevOps would also be appreciated.

I can share my resume via DM.

Thank you for your time and support!

I’ve been working in software for about 15 years, mostly backend, and I specialize in Go. I also have around 3 years of DevOps/SRE experience, though that was about five years ago and in a small company.

Lately, my backend role is almost entirely prompting and reviewing AI-generated code. At my company, even people who aren’t engineers can open PRs.. Management thinks that "help" us, but thanks no thanks, 1k+LOC PR is not helping anyone... They want us to build some magical "harness" that will produce exactly the feature you want with all good practices embedded.
I worry that my job is heading toward purely supervising AI-driven workflows rather than writing and designing software.

I’ve been considering moving back toward SRE, platform, or DevOps work. Perhaps it's naive, but I think it's less exposed to the AI frienzy, as it's not directly part of product. I get that a lot of things get automated (incident response, dashboard) but that's kind of in the spirit of devops ?
I see it as more job secure and more interesting in this day and age, as you'll always need people to run your infra for ai workflows (right anakin ?)

Also part of the appeal is that these roles seem more available where I live, while remote backend jobs have been hard to find. Devops skills can be reused in a lot of company of various sizes.

Question for you: how has AI changed your day-to-day work? Is it making the work more interesting, or just shifting more of it toward reviewing generated configs and automation? How do you see it evolving or enduring ?

Hi everyone,

I just finished my Computer Engineering coursework in Mexico City (degree paperwork in progress) and I have no formal job experience yet. My hands-on experience is my university social-service project: I designed and deployed a web portal on a physical server with 2 GB of RAM using FastAPI, Nginx, K3s, Argo CD and MySQL. I also built a personal GitOps/SLO project with Prometheus and Grafana.

I’m studying for the CKA (KodeKloud + Killer.sh), and after that I plan to take the Terraform Associate and build a small Terraform project on AWS. Longer term, I’d like to move toward DevSecOps. I’m also starting to learn how AI agents work, since I think knowing how to supervise them will matter.

To be honest, the job search has been tough and I’ve been feeling a bit down lately, so I really appreciate any advice and experiences you’re willing to share.

Questions:

1. For entry-level cloud ops / Linux admin / infra-adjacent roles, does a CKA help a candidate with no job experience, or do recruiters mostly ignore it?
2. How do you see the path from DevOps to DevSecOps? Is it a realistic branch for someone just starting out, and what would you focus on first (IAM, secrets management, container/IaC scanning, something else)?
3. Does my order (CKA → Terraform → AWS project) make sense, or would you change it?

Thanks, any honest feedback is welcome!!!

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