This case study focuses on a project where we needed to connect several P5 instances, the highest-performance GPU-based servers available. We utilized 32 fiber-optic cards, establishing a robust connection for an impressive throughput of 3.2 Tb/s between servers. Each server houses 8 NVIDIA H100 graphics cards with 600 GB of GPU memory. Although the final cluster is relatively small—totaling 1.8 TB of GPU memory, 576 CPUs, and 6 TB of RAM—it's just the beginning of what we aim to achieve.

When we think about security, we typically focus on backend applications and servers. They usually find their safe spot behind firewalls, where access is restricted by VPNs, systems are kept up to date, and every action is audited. :) But what about front-end applications? A few years ago, "frontend" was merely a view generated by our backend servers. However, we've moved toward Single-Page Applications, incorporating a lot of JavaScript and business logic. We build them and allow anyone to run them. But what about their runtime environment? Is it secure? Is it up to date? How easily can it be hacked? In this presentation, I want to show you that we should care about runtime for our frontends. I’ll also show you how to use mechanisms built into browsers to help us secure our users.

The DevOps role has evolved from handling every imaginable infrastructure task to specialized platform engineering focused on AWS and GCP expertise. Discover our team approaches multicloud challenges, builds security into infrastructure modules from day one, and maintains a learning culture that keeps them at the forefront of cloud technology.

Cloud doesn't scale infinitely, multi-cloud rarely prevents downtime, and serverless becomes expensive at scale—these myths cost companies millions in unnecessary infrastructure spend. Discover real-world DevOps strategies for application scalability, AWS cost reduction, infrastructure as code, and automated security implementation.

How we started Let's Go DevOps during COVID-19 with clients on day one, and what we learned about managing infrastructure at scale: preventing configuration drift across 70+ engineers, Kubernetes security layers, and why cloud-native architecture saves companies 5-10x on AWS costs.

Most companies approaching petabyte-scale compliance data choose expensive native cloud storage or complex MySQL replication, resulting in massive costs and poor performance. Discover how optimized file chunking, BigQuery external storage, and automated lifecycle policies reduced audit log costs to $500 monthly while improving query speed by 2,000x.

DevOps isn't just about infrastructure engineering or cloud expertise—it's an organizational culture built on transparency, communication, and mixed competencies across teams. Learn why DevOps teams often become isolated silos instead of collaboration hubs, and how platform engineering, soft skills, and proper team composition make the difference between success and bottlenecks.

Load balancing seems simple until you hit production scale with 100+ microservices, 6,000 containers, and daily infrastructure losses of 15%—then round robin algorithms reveal their ugly side. Discover why least connections can route 90% of traffic to broken servers, how misconfigured Kubernetes readiness probes send traffic to dead services for 60 seconds, and the real-world architecture running entirely on AWS spot instances while handling 800 requests per second.