Ishu Gupta

DevOps Engineer

Mumbai, Maharashtra, India3 yrs experience

Highly Stable

Key Highlights

Expert in scaling high-availability production systems.
Proficient in GCP, Terraform, and Kubernetes.
Strong focus on observability and automation in SRE.

Stackforce AI infers this person is a Cloud Infrastructure Engineer with a strong focus on Site Reliability Engineering.

Contact

Skills

Core Skills

Site Reliability Engineering (sre)DevopsCloud InfrastructureSoftware Development

Other Skills

TerraformGoogle Cloud Platform (GCP)JenkinsGrafanaELKInfluxDBKubernetesLinuxAnsibleASP.NETReactJSMySQLJestOperating SystemsTechnical Skillset

About

DevOps / Site Reliability Engineer with ~3 years of experience building and operating high-availability, low-latency production systems at scale. Currently working at Jio Platforms, supporting large-scale SSAI platforms with millions of concurrent users. I specialize in production reliability, observability, and automation — defining SLIs/SLOs, reducing alert fatigue, improving MTTR, and eliminating toil using Infrastructure as Code (Terraform) and Python automation. I’ve worked extensively on GCP-based architectures, predictive autoscaling, Kubernetes, CI/CD pipelines, and cost optimization — ensuring systems remain stable during extreme traffic spikes (e.g., IPL events). 🎓 IIT (BHU) Varanasi graduate 🔧 Interests: SRE, Production Engineering, Distributed Systems, Cloud Infrastructure 📩 Open to DevOps / SRE opportunities

Experience

3 yrs

Total Experience

3 yrs

Average Tenure

3 yrs

Current Experience

Jio platforms limited (jpl)

2 roles

DevOps / Site Reliability Engineer – Jio Platforms

May 2024 – Present · 2 yrs 1 mo · On-site

𝐒𝐜𝐚𝐥𝐞𝐝 𝐡𝐢𝐠𝐡-𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 to support 𝟓𝐌+ 𝐜𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐬𝐞𝐬𝐬𝐢𝐨𝐧𝐬, maintaining 𝟗𝟗.𝟗𝟗% 𝐮𝐩𝐭𝐢𝐦𝐞 during peak traffic events.
𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐞𝐝 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐚𝐮𝐭𝐨𝐬𝐜𝐚𝐥𝐢𝐧𝐠 for GCP Managed Instance Groups using custom metrics to eliminate scaling lag.
𝐑𝐞𝐯𝐢𝐭𝐚𝐥𝐢𝐳𝐞𝐝 𝐨𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐬𝐭𝐚𝐜𝐤𝐬 (Grafana, ELK, InfluxDB), reducing alert fatigue by 𝟒𝟎% through user-centric SLIs/SLOs.
𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐞𝐝 𝐂𝐚𝐧𝐚𝐫𝐲 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 and automated rollbacks via Jenkins to safeguard error budgets.
𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐞𝐝 𝐦𝐮𝐥𝐭𝐢-𝐫𝐞𝐠𝐢𝐨𝐧 𝐃𝐑 using modularized 𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦 (𝐈𝐚𝐂) for 300+ servers.
𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐥𝐚𝐭𝐞𝐧𝐜𝐲-𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 (<50ms budget) through TCP tuning and connection pooling.
𝐃𝐫𝐨𝐯𝐞 𝐚 𝟑𝟎% 𝐜𝐥𝐨𝐮𝐝 𝐜𝐨𝐬𝐭 𝐫𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 via capacity planning and preemptible instance strategies.
𝐇𝐚𝐫𝐝𝐞𝐧𝐞𝐝 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 using Kafka and KeyDB, maintaining a 𝟗𝟗% 𝐜𝐚𝐜𝐡𝐞 𝐡𝐢𝐭 𝐫𝐚𝐭𝐢𝐨.

TerraformGoogle Cloud Platform (GCP)JenkinsGrafanaELKInfluxDB+3

Graduate Engineering Trainee

Jun 2023 – May 2024 · 11 mos · On-site

> Gained hands-on experience with Linux administration and cloud fundamentals using AWS and GCP, focusing on server setup, networking, and monitoring.
> Learned to automate infrastructure using Terraform and Ansible, creating basic deployment scripts and managing configurations in cloud environments.

LinuxTerraformAnsibleCloud Infrastructure

Amazon

Amazon ML Summer School

Jul 2022 – Jul 2022 · 0 mo

Selected for the program to learn ML topics & interact with Amazon Scientists
Inculcated knowledge about some key ML topics including Supervised Learning, Deep Neural Networks,
Dimensionality Reduction, Unsupervised Learning, Probabilistic Graphical Models, and Sequential Learning

Kritikal solutions

Software Engineer Intern

May 2022 – Jul 2022 · 2 mos · Remote

Developed a web application for the staff portal using MVC architecture with ASP.NET, ReactJS, and MySQL.
Implemented CRUD functionalities including search, create, view, edit, and delete operations to manage employee data.
Implemented unit and integration tests for the ReactJS application using Jest and React Testing Library.

ASP.NETReactJSMySQLJestSoftware Development