Hello there, I'm Subhash Polisetti!

• Security builds (on FreeBSD) provisioning automation across 900+ public/private data centres worldwide.
• Built fail-safe data pipeline connecting internal in-house cloud weblog data to BIGQuery (GCP with OAuth) to analyse (with pandas,scikit-learn,Pytorch) customer transaction data/workload patterns & do capacity planning for new features like Data Loss Prevention.
• Validated configs & Restarted 1k+ high-priority Production Services with Self-healing scripts(across time-zones).

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• Handled 5G Telecom customer clusters scale:
  • 3000+ pods kubernetes cluster
  • 200+ nodes baremetal openstack clusters ( k8s on openstack/baremetal servers)
• Part of Cloud RnD business unit, which was sold to Red Hat. (info: Nokia and Red Hat Partnership, Red Hat Press Release)
• Built automation & monitoring tools/processes to deploy/upgrade various telco-grade products on k8s & Openstack/ceph.
• Resolved over 150 critical bugs & escalations throughout infra stack from kernel upgrades, HW certs, storage performance to observability involving various internal/open-source tools like Zabbix, Prometheus, Grafana, ELK stack, Fluentd, Istio, and Calico.
• Improved visibility for applications running on Kubernetes by debugging and integrating acceptance tests, low-level system and network metrics from CLI into Fault/Performance management dashboard tools for better resource estimation.
• Developed over 20 validations in internal cluster health/log collection tools using Python/Ansible playbooks to fix the current state of the services and enable smoother lifecycle operations like scale-in/out nodes, PKI certificate renewals etc.

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Hands-on experience with almost all traditional ML algorithms/techniques(like one hot ecnoding, scaling, Normalization, PCA), libraries (infra ecosystem) and architectures, having applied them to multiple datasets.

Explored the evolution/timeline of AI, from the early days of the perceptron to Hopfield and Boltzmann networks, followed by Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and the more recent developments in attention mechanisms. Realized history of Computing is just history of creating Artificial Intelligence and Von Neumann architecture might just be a detour.

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• Closely Interacted with Upstream Linux (Fedora, centos), Ansible, Ceph, Openstack, Kubernetes, Jenkins open source communities and contributed to new feature/bug fixes discussions.
• Worked on Ceph, a unified distributed software-defined storage system with block-file-object level access from a single managed cluster on the backend.
• Usually called the Linux of Storage or the future of storage (almost 2 Million lines of C++ project.. low level distributed storage system at kernel level which can scale to PetaBytes lvl clusters).
• Contributed to multiple major & minor releases of RHCEPH 2,3 by automating critical test cases in rados, iSCSI & file system components.
• Automated IOPS testing by including them as part of the sanity suites with tools like dd, fio, covering various stress/load/idle scenarios.
• Wrote test cases for all possible workloads and components of RHEL/Ceph & various new storage features, keeping regressions in mind.
• Implemented container verification pipeline by configuring RabbitMQ for new container images built for multiple parallel releases of RHCEPH & RHEL; Integrated layered product interop testing of early RHEL 7.x, 8.x builds with Ceph.
• Actively collaborated in QE-CI initiative efforts across Red Hat's global QE organization, building common best practice CI/CD pipelines and tools from scratch, leading to 95% implementation of CI best practices in the CephQE team.
• Enhanced test-metric analysis for each release via integration of ReportPortal.io ML dashboard into automation framework.
• Core maintainer of CephCI and Teuthology test framework GitHub repositories, which are tightly coupled with pytest, apache-libcloud/gevent & ssh paramiko libraries, where containerized Ceph is deployed on top of auto-provisioned baremetal/VMs.
• Analyzed and filed critical bugs in librados and Ceph-Rados Gateway (RGW) component, a REST interface to Ceph cluster providing object storage with Amazon S3 and OpenStack Swift API compatibility.

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PCgaming benchmarking enthusiast: overclocking gpus/cpus/memoryClocks, worrying about fan-temperature-voltage control ..Upgrading every generation ,pci gen3 to gen5,gtx 9400 to 4090s etc

Obsessed with game benchmarking and performance optimizations at driver level:

• Meticulously analyzed frame rates, Obsessed on 1% (Percentile , p95,p99,p99.9,p99.99) lows for smooth gameplay..Looking back MFUs might be a better measure of performance than gpu Utilizations and frametime (alteast for ML workloads: theoretical max FLOPS vs actual FLOPs util)
• Experimented with various graphics settings to find optimal balance of visuals and performance
• Occasionally rage quit when encountering frustrating frame drops or stutters/artifacts

Hail PCMR! (eyes always on top left corner of the screen tracking fps drops..focus shifted from videos games to harnessing the power of spice)

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Started with tvboy.jpg, a nostalgic reminder of early gaming days. Later upgraded to couple Nintendos consoles.

Electric shocks and bad grounding(while connecting tvboy to CRT) dint stop me lol ,was in LFG mode to play with friends

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