Rishabh Parihar | NetDevOps Engineer

Hi, I'm Rishabh Parihar.

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A Network Engineer who is self-driven and eager to explore the potential of network automation to enhance network performance and efficiency.

About

As a Network Engineer with a passion for automating complex workflows, I specialize in creating solutions that enhance the stability and usability of products. With a focus on network automation, I am dedicated to designing and implementing systems that optimize performance and improve efficiency. By leveraging my skills and expertise, I am able to deliver top-quality results that exceed expectations and drive success for my clients.

Languages: Python, Ansible, Html, Rest-API, Selenium
Networking: SDWAN, SASE, NFV, VPN, TCP, TLS, DNS, Linux Networking, IPTables
Firewall Vendors: CheckPoint,Palo Alto, Juniper MX/SSG, Fortigate, Cisco ASA, Linux
Libraries: Netmiko, Pandas, Nornir, IPAddress, Threaded, JC, Asyncio
Frameworks: Flask, PyWebIO
Tools & Technologies: Git, Heroku, JIRA, Confluence, PostMan

Experience

Aryaka Networks

Sr Lead, New Services Introduction

Responsibile to ensure new Products/Offerings are ready for Customer consumption
Responsible to add workflow automation to simplify process and reduce efforts required by end engineer
Drive discussion with Engineering Team on new tools/features/enhancements
Reduce time spent in bulk jobs by automating steps using Python
Tools: Python, Selenium, PostMan

Nov 2021 - Till Date | Bengaluru, India

Aryaka Networks

Lead Network Consulting Engineer

Responsible for providing architectural direction, technical solutions, drive industry best practices and managing relationships with Aryaka strategic customers.
Responsible to work with Stakeholders in designing LLD and HLD Documents
Primary point of contact for the dedicated accounts for all technical issues
Responsible for designing design documents, delivering migration plans, with a thorough understanding of networked applications and related dependencies

Jan 2016 - Oct 2021 | Bengaluru, India

Infosys Ltd.

Juniper TAC

Responsible for configuring, troubleshooting and managing Juniper SSG Firewalls
Worked as Juniper TAC(Level 1) and providing technical support and resolving day-to-day network issues faced by customers across the world

July 2014 - Dec 2015 | Pune, India

Projects

                
CheckPoint Bootstrap Generator
                  Flask WebApp for Day0 config
                
AccomplishmentsTools: Flask, Jinja2, Python, Bootstrap, PythonAnywhere
Generates VNF Firewall Day0 config
Generates .iso config file for config during bootup process.
Minimizes user input
Validations added to prevent Typos/Duplicate IP/Network errors/

SASE ToolKit
                  A Python based SASE Platform Testing App
                
AccomplishmentsTools: PyWebIO, Flask, Python, PyTest
Tool will initiate traffic mimicking web browser and generate PyTest Report Dashboard
URL Filtering Test: Checks if response is 200OK with no redirects to Captive Portal 
SSL Filtering Test: Checks if response is 200OK and server Cert matching with the SASE Platform Generated 
Anti Malware Test: Checks if Eicar/Wicar Test Malware files get downloaded from web browser 
Public IP Test: Checks if traffic is routed from known owned Provider Block(using curl ifconfig.me/ip)

Blog Web-App
                  A simple and extensible blog web-app based on Flask.
                
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, SQLAlchemy, Postgresql, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.

Visual Question Answering
                  An attention-based classification model that aims at generating an answer for a given input image.
                
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term
                    Memory for extracting question
                    embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the
                    VQA evaluation metric.

Video Summarizer
                  A Seq2Seq model that generates a short summary of the given input video.
                
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for
                    generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71,
                    0.52 scores respectively on ROGUE,
                    BLEU, METEOR evaluation metrics.

Image Generator
                  An image generator based on the concept of adversarial networks (GANs)
                
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs
                    of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by
                    the generator.

Head Counting System
                  A system that calculates the attendance of the class from a panoramic image of a live classroom.
                
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing
                    techniques and morphological operations to
                    detect the number of heads.