milindyadav

Open to senior backend, platform, DevOps and SRE roles

I build platforms that are easier to run, debug and change.

Platform and DevOps engineer with 5+ years of software engineering experience across backend systems, CI/CD, Kubernetes, cloud infrastructure and observability.

Explore selected work LinkedIn
current focus / build-observabilityIN PROGRESS
01Job evidencelogs · metrics · traces
02System contextcontroller · agent · machine
03Investigationcorrelate · explain · fix

→ A failed build should come with enough evidence to understand what happened.

Platform engineeringDevOps automationObservabilityBackend systemsCloud infrastructureDeveloper experience

01 / Selected work

A few things I have built or am building.

I have kept the descriptions general where the implementation is proprietary.

01

Current observability project

Bringing Jenkins and machine telemetry into one view

I am building an observability setup for Jenkins controllers, agents, jobs, Kubernetes workloads and bare-metal machines. The stack uses Prometheus, Loki, Tempo, Grafana, Alloy and OpenTelemetry.

Why it matters

The next step is reliable correlation across build telemetry, followed by an assistant that can investigate failed builds.

GrafanaPrometheusLokiTempoAlloyOpenTelemetry
02

Security tooling

Replacing a licensed security scanner with an in-house tool

Built an in-house Python security-scanning framework that kept the required checks and fit the team's existing workflow.

Why it matters

Removed approximately USD 12,000 in annual licensing cost.

PythonSecurityAutomation
03

Data engineering

Calculation pipelines and reporting

Implemented performance and attribution calculation logic in Spark data pipelines and contributed to data-lake schema work. Superset was used for dashboards after an initial Looker and LookML proof of concept.

Why it matters

The work covered calculation logic, storage design and reporting.

SparkData lakeSupersetLookML

02 / How I work

Most of my work sits where code, delivery systems and infrastructure meet.

I have worked in backend development, system software validation and DevOps and infrastructure roles. That path has made me comfortable moving between application code, pipelines, cloud services, Kubernetes and the machines underneath them.

I like problems where a failure crosses layers. I prefer to look at the evidence first, understand the failing path and then change the smallest part that actually solves the problem.

01Start with evidence

Reproduce the issue and understand the failing path.

02Automate repeated work

If a team keeps doing it by hand, I look for a safe way to automate it.

03Make systems easier to own

Write down the reasoning and leave the next person a clearer path.

03 / Notes from the margin

Books I argue with, underline and return to.

I read to sharpen how I think about systems. These are my own paraphrased notes, not quotations from the books.

DDIA01

Distributed systems

Designing Data-Intensive Applications

by Martin Kleppmann

What stayed with me

The most useful shift for me was treating failure as normal. A good design makes failures easier to understand, contain and recover from.

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04 / Working toolkit

Tools I use regularly.

Build & delivery

Jenkins · Groovy · Docker · Helm · Kubernetes

Cloud & platform

AWS · EKS · S3 · IAM · Redis · MySQL

Observability

OpenTelemetry · Grafana · Prometheus · Loki · Tempo

Software

Python · Java · Spring · Kotlin · C++

05 / Start a conversation

I am open to senior backend, platform, DevOps and SRE roles.

If my experience fits what your team is building, please get in touch.

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