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Hi, I am Masud

Masudur Rahman

Lead Software Engineer at AppsCode Inc.

A professional Software Engineer with 5 years of experience in Back-End Development in Go. A competitive programmer with great problem-solving skills. I am passionate about learning new things, and am highly adaptive to new technologies.

Leadership
Team Work
Hard Working

Skills

Experiences

1
AppsCode Inc.

Nov 2018 - Present, Dhaka Branch

AppsCode’s mission is to accelerate the transition to Containers by building a Kubernetes-native Data Platform.

Lead Software Engineer

Jan 2023 - Present

  • Lead the design and maintenance of AppsCode API Server, a RESTful API for managing Kubernetes clusters and applications. Tools: Go, go-macaron, Helm, k8s etc.
  • Restructured the cluster import flow for AppsCode Console, improving the user experience and performance.
  • Implemented dynamic feature controller for managing different features in imported clusters, such as monitoring, security
  • Restructured the Licensing system for AppsCode products, automating the license issuance, validation and enforcement.
  • Packaged AppsCode Console as a Service and made it ready for deployment in user k8s clusters (vendor-managed or self-managed) and through various DNS providers and Cloud Storage Services. Tools: CloudDNS, Cloudflare, AzureDNS, Route53 etc. and also GCS, s3, Azure Blob Storage, Linode Object Storage.
Senior Software Engineer

Jan 2021 - Dec 2023

  • Designed and Maintained ByteBuilders API Server. Tools used: Go, macaron web framework, helm, k8s.
  • Added a support for importing Kubernetes Cluster [Managed, Public & Air Gaped] to ByteBuilders Dashboard.
  • Implemented A Background Task Manager for long running tasks, log/exec features for Kubernetes pods/services and Invoice generation from users’ usage data with the help of NATS. Tools used: Go, k8s, NATS
  • Developed a Prometheus Proxy Server for Grafana datasource.
  • Added CI/CD pipelines for projects in Github Actions.
  • Involved in Deployment & Maintenance of ByteBuilders Production Server.
  • Guided and managed team-members.
Software Engineer

Nov 2018 - Dec 2021

  • Implemented a feature in Pharmer project to support Kubernetes Cluster Provisioning in Google Compute Engine using Cluster API. Tools used: Go, Shell scripts.
  • Contributed in ByteBuilders API Server integrating various features.
  • Integrated Stripe Payment APIs including product, plan, payment and invoice apis.
  • Developed a Kubernetes Controller for Provisioning and Managing Grafana Dashboards and Datasources.

Intern
Rankmylist Inc.

Sep 2017 - Nov 2017, Chittagong

2

Projects

ByteBuilders by AppsCode
ByteBuilders by AppsCode
Lead Software Engineer

ByteBuilders is the Back-End server for a Kubernetes Dashboard. Deploy, manage, upgrade Kubernetes on any cloud and automate deployment, scaling, and management of containerized applications.

Grafana Operator by AppsCode
Grafana Operator by AppsCode
Contributor

Grafana Operator is a Kubernetes Controller for Provisioning and Managing Grafana Dashboards and Datasources. It’s based on a grafana sdk.

Pharmer by AppsCode
Pharmer by AppsCode
Contributor

Pharmer is a Kubernetes Cluster Manager using Kubeadm & Cluster API.

Logger by AppsCode
Contributor

nats-logr is a logr implementation using NATS. union-logr is a logr implementation that aggregates multiple loggers.

Pawsitively Purrfect
Pawsitively Purrfect
Owner Jan 2021 - Present

Pawsitively Purrfect is a web application for Pet Adoption, written in Go, GraphQL. The project follows the Service-Repository-Data pattern for clean architecture. The Repository layer communicates with Data layer through a gRPC server.

Cluster API Provider GCP
Cluster API Provider GCP
Contributor

Fixed some issues regarding k8s version, Node role and default disk size.

Gitea
Gitea
Contributor

Refactored naming of users’ avatars.

Grafana SDK
Grafana SDK
Contributor

Refactored some existing APIs and added some new ones.

NATS Helm Chart
NATS Helm Chart
Contributor

Fixed some Websocket related issues in NATS helm chart.

Facial Expression Recognition Using CNN and SVM Approach
Facial Expression Recognition Using CNN and SVM Approach
Owner Jan 2018 - Oct 2018

Developed a program to recognize Facial Expression from a static image. CNN and SVMs used to train and classify facial expressions into various categories. Python, TensorFlow, SVM, OpenCV used for image processing and machine learning.

Education

B.Sc. in Computer Science & Engineering
CGPA: 3.76 out of 4
Extracurricular Activities
  • Participated in numerous national and international Programming contests
Higher Secondary School Certificate
GPA: 5 out of 5
Shaheb Rampur High School
2006-2011
Secondary School Certificate
GPA: 5 out of 5

Achievements

CUET NCPC 2017

ICPC Dhaka Regional 2018