Senior Full-Stack (NestJS/Next.js) for LMS Rescue: Server Fix + Video Optimization + UX (60TB Data)

@DeveloperStation

Hi there, We’ve developed similar platforms where we optimized video processing pipelines to reduce transcoding times from 1:1 to 1:10. We also implemented responsive, pixel-perfect UIs using Figma designs, ensuring a seamless user experience. As a team of dedicated developers, we can assign specialists for each task—like a DevOps expert for server management and a front-end developer for UI work—ensuring you get the best expertise at no extra cost. Let’s schedule a quick 10-minute call to discuss your project in more detail and see if I’m the right fit. I usually respond within 10 minutes. I’m eager to learn more about your exciting project. Best regards, Adil

@sn102a1k46

TITANIUM Hey there — this is exactly my wheelhouse. I’ve run rescues like this before for media platforms, and the 60TB data safety piece is non-negotiable. Here’s my straightforward plan Safety for 60TB - Before touching any Docker config, I’ll first create a complete volume and directory map outside Docker. I’ll run a read-only verification script to checksum a sample of files, then mount the existing video storage as a Docker volume using bind or nfs without moving data. Only after confirming the new container reads the data correctly will I decommission old setups. Zero data loss means treating the existing storage as sacred and attaching, not copying. Biggest FFmpeg bottleneck & fix - The 1:1 ratio usually points to a lack of hardware acceleration and poor parallelization. In Docker, the biggest bottleneck is often CPU-only transcoding with single-threaded FFmpeg commands. I’ll tune it by: Enabling hardware acceleration (NVENC/QSV/VAAPI) if available. Splitting transcoding into parallelized chunked processing via a queue (like Bull) with multiple workers. Adjusting FFmpeg parameters (preset veryfast, tuning film, GOP sizing for HLS). This should push processing well under real-time. Cheers.

@reedsystems

Hi, TITANIUM To ensure the safety of the 60TB of video data before restarting/rebuilding Docker containers, I will create a full backup of all HLS videos using rsync or another reliable backup method. This will be stored securely on an external drive or cloud storage to prevent any risk of loss during the transition. For optimizing FFmpeg transcoding speed in Docker, the biggest bottleneck often lies in CPU and memory limitations. To address this, I would first adjust Docker resource allocation settings to ensure each container has sufficient resources for transcoding. Additionally, optimizing FFmpeg parameters such as `-threads`, `-c:v`, and `-b:v` can significantly improve processing times without compromising output quality. Implementing a more efficient queuing system with proper concurrency control will also distribute the load effectively across multiple cores. Regards, Reed.

@adily1

Hey , I just finished reading the job description and I see you are looking for someone experienced in Full Stack Development, Video Processing, PostgreSQL, Learning Management Systems (LMS), Docker, Microservices and Next.js. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Adil.

@BSDesigners

Hello "Jose", I will tackle the challenges in your EdTech platform by cleaning up the server, optimizing video processing speed, and implementing a new UI while ensuring zero data loss and efficient deployment. Let's discuss further details. Thanks

@ofcjohandp

I’ve reviewed your project, and I believe I can help you build a clean, reliable, and user-friendly solution. My focus will be on a clear project structure, fast performance, and a simple and intuitive user experience. You can expect regular updates, clear communication, and easy scalability from my end. I can start immediately and provide you with a detailed plan on how I will tackle your project step by step. I look forward to discussing your requirements and collaborating to deliver the best results. Best regards, Herman Johan du Plessis

@katerynai2

Hello, As a full-stack engineer with extensive experience in building production web platforms, particularly within the Ethereum ecosystem, I believe I am the missing piece to your LMS project puzzle. I'm comfortable with every aspect of the job description, from optimizing FFmpeg transcoding on Docker to the implementation of comprehensive documentation to ensure smooth handover and everything in between. To address the first technical question, my strategy for ensuring data safety before restarting/rebuilding Docker containers would encompass: creating multiple backups on separate servers; verifying and cross-validating these backups before removing any existing data; and executing the rebuild process in a staged manner, monitoring each stage's success before proceeding. My goal is not only zero data loss but also maintaining data integrity throughout. To tackle the second technical question, the primary bottleneck in FFmpeg transcoding on Docker stems from suboptimal resource allocation. By tuning container-resource limits appropriately, running concurrent transcoding queues with respect to system capability, and refining FFmpeg settings for optimal output, I can improve the 1:1 real-time conversion ratio significantly - transforming even large files into HLS-ready format ahead of schedule. In sum, my diverse skill set underpinned by a strong development operations background (especially with Docker) combined with deep knowle Thanks!

@josepht032

Hello , I am a Full Stack Software Engineer with strong experience Full Stack Development, Microservices, Learning Management Systems (LMS), PostgreSQL, Docker, Video Processing and Next.js. My background includes API and microservice development, cloud deployment, database design, and the integration of machine learning models and LLM-based workflows into real-world products. I focus on clean architecture, maintainable code, and solutions that solve practical business problems. I work well in collaborative environments, communicate clearly, and can support projects from initial design through deployment and iteration. I would be happy to discuss how my skills align with your project goals. Best regards, Joseph

@francentimothyc

Hello I have solid experience integrating both RESTful and GraphQL APIs across different platforms, including e-commerce systems, payment gateways, logistics services, and internal tools. I write clean, maintainable code with proper error handling, rate limit control, and performance optimization. I’m also familiar with authentication methods like OAuth2, webhooks, and token-based systems to ensure safe and consistent communication between services. I have strong experience working with databases such as PostgreSQL, MySQL, and MongoDB. I’m comfortable with database schema design, writing optimized queries, indexing, handling migrations, and ensuring data consistency across systems. I’ve also worked with relational and non-relational data models depending on the use case. Looking forward to working with you Thanks

@Nayeem1217

As a seasoned professional with extensive experience in video processing, I am well-versed in the many facets of your critical project, which encompasses both backend revitalization and frontend design requirements. I understand the importance of seamlessly managing vast amounts of data like the 60TB HLS video content you currently have. With my deep familiarity in Docker volumes, I can confidently assure you that zero data loss will be upheld during the rebuild as your safety concerns are my utmost priority.

@alexo526

TITANIUM Hey there! Here’s how I’d handle your two big questions: ✅Safety: First thing, I’d map all 60TB of video data to persistent Docker volumes before touching anything. I’d double-check paths, permissions, and run a small checksum sample to ensure files aren’t at risk. Basically, I treat the existing HLS library as untouchable until the containers are correctly pointing to it. No rebuild, no restart until I confirm every bit of data is correctly mapped and accessible. ✅Video Speed: The biggest bottleneck in FFmpeg inside Docker usually comes from CPU allocation, I/O throughput, and inefficient container resource limits. To speed it up beyond 1:1 real-time, I’d optimize FFmpeg settings for HLS segmenting, enable hardware acceleration if available, and run parallel conversion queues inside Docker with proper CPU/memory limits. Sometimes, simply tuning the segment length and avoiding unnecessary re-encoding for unchanged streams cuts massive time. I can take your server, optimize the transcoding pipeline, and implement the new UI while keeping all 60TB completely safe. If you want, I can also sketch the step-by-step sequence I’d follow to go live without downtime. Best, Alex

@MancicSoftDev

TITANIUM 1. Safety: - I will create a full inventory map (paths, manifest files, HLS playlists, permissions) without changing anything. I will catalog file counts / total sizes and checksums (sampled) to verify later. - I will not move or copy the 60TB initially. I will map host directories into containers via Docker bind mounts (or Docker volumes that reference host paths) so containers operate in-place on the existing data. - Use rolling container restarts and staged Compose changes. Keep an immediate rollback plan (docker-compose override file that restores prior config). I will avoid any bind mount or volume reformatting and never run destructive commands that could truncate or delete data. 2. Video Speed: - Poorly tuned FFmpeg command lines (presets, filter graphs), and insufficient concurrency/queue design. - I/O (reading 60TB from disk, especially if many concurrent jobs hit the same spindle). - CPU single-thread limits for certain filters/codecs and number of CPU cores available to the container.

@revival786

Greetings! I’m a top-rated freelancer with 16+ years of experience and a portfolio of 750+ satisfied clients. I specialize in delivering high-quality, professional full stack developing services tailored to your unique needs. Please feel free to message me to discuss your project and review my portfolio. I’d love to help bring your ideas to life! Looking forward to collaborating with you! Best regards, Revival

@simonp75

TITANIUM Bid should be less than 1500 characters, so I'll answer tech questions directly without introduction myself. Sorry. 1. Data safety -Map all volumes (docker volume ls/inspect) and host paths. -Create full rsync backup to secondary storage + verify checksums. -Test rebuild in staging with data sample. -Tag current images & keep original compose file. -Only proceed after 100% backup confirmation. 2. Video Speed - the biggest bottleneck is single thread of FFmpeg run -Set -threads 0 (auto) or 8–16. -Use -preset ultrafast/superfast. -Allocate more CPU (cpus: 8 in compose). -Process segments in parallel queues (BullMQ). -Enable HW accel (NVENC/VAAPI) if GPU available. -Result: 2–5x faster typical. Looking forward to hearing back from you soon. Semen

@manpreetkaur991

Hello Greetings, After reviewing your project description, I am confident and excited to work on this project for you. However, I have some crucial points and questions to clarify. Please leave a message in the chat to discuss this, and I can share my recent work that is similar to your requirements. Thanks for your time! I am excited to hear from you soon. Best regards,

@natanr28

TITANIUM Dear hiring manager, I can execute this mission within 3-4 weeks timeline I'm a senior software engineer with deep expertise in NodeJS (NestJS, ExpressJS), React, Next with typescript and hign-performance docker/FFmpeg pipelines. 1. 60TB Data safetuy: I'll mount the existing volume as read-only in the new Docker setup, validate app paths, and perform a checksum-verified migration only after full confirmation. 0 data loss is guaranteed. 2. Video Speed bottleneck: The 1:1 ratio points to single-threaded CPU encoding and I/O contention. I'll implement parallel FFmpeg processing per scene, optimize H.264 preset/CRF settings, and tune queue concurrency - targeting 3-5 x speed gains. Plan: - Week1: Secure server, map 60 TB data, overhaul transcoding pipeline. - Weeb2-3: Build, integrate pixel-perfect NextJS UI from figma - Weeb4: Full testing, swagger docs, deployment README, stable launch. I'm an expert in NestJS, NextJS, Docker and FFmpeg optimization. Available to start immediately. Best regadrs, Natan.

@rahulb058

Hi, This is exactly the kind of takeover and stabilization project I specialize in: solid backend foundations, but production pain due to infrastructure drift, slow media pipelines, and a UI that needs a serious upgrade. I’m comfortable owning this end-to-end and delivering it as a fixed-price, milestone-driven engagement. You already have good bones (NestJS microservices rated 8/10 is a strong starting point). My focus would be to secure your data first, stabilize the platform second, and then move fast on performance and UX.

@Solutionzhere

I am more than capable of cleaning up your server mess and ensuring the safety of your monumental 60TB video data. With my expertise not only will zero data loss be ensured by carefully mapping the data volume to new Docker containers, but my devops skills will also help bring order to your chaotic Docker/Nginx configurations. Rest assured, with me on board, your server rescue and data safety concern will be a thing of the past! Let's talk details over chat/call. Thanks and regards.

@wasifmuneer

TITANIUM Hi there, I'd love the opportunity to connect and discuss your project in detail—feel free to reach out via chat anytime. I'm a full-stack developer with strong experience in building both web and desktop applications. I’m confident I can manage and deliver your project efficiently and on time. I have hands-on experience in DevOps, giving me a broader perspective on project deployment and scalability. My technical expertise includes: MERN / MEAN Stack: Extensive hands-on and team leadership experience, ensuring smooth front-end to back-end integration. .NET Core & Angular: Implemented various data visualizations using D3.js, integrated complex APIs, and developed dynamic, responsive applications. Azure Logic Apps & SharePoint: Built multiple workflow automation solutions; also familiar with PowerApps development. Salesforce Development: Developed Apex triggers to interact with MSSQL via custom .NET APIs. Created Visualforce pages to fetch and display external API data. Performed CRUD operations on both standard/custom Salesforce objects. Conducted R&D on Salesforce Flows for automation (with some custom object limitations). I bring a full-lifecycle development mindset and enjoy solving real-world business challenges through code. Looking forward to hearing from you! Thanks!