18 days ago
Auto-scaling based on custom metrics. CPU usage alone wasn't enough for our workload! #autoscaling #cloud #aws
18 days ago
Auto-scaling based on custom metrics. CPU usage alone wasn't enough for our workload! Implemented scaling based on queue depth and request latency. Predictive scaling for known traffic patterns (like daily peaks). The cluster now responds to actual business metrics. Right-sizing finally achieved! #autoscaling #cloud #aws #optimization
18 days ago
Deployed ML model with FastAPI and Docker. Inference time under 100ms! Used ONNX Runtime for optimized inference. Implemented batching for throughput optimization. Horizontal scaling with Kubernetes handles load spikes. From Jupyter notebook to production in 2 weeks. MLOps maturity achieved! #mlops #deployment #ai #fastapi
19 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
19 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
20 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
20 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
20 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! #kubernetes #k8s #devops
20 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
21 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
21 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
21 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
21 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! #kubernetes #k8s #devops
21 days ago
Deployed ML model with FastAPI and Docker. Inference time under 100ms! Used ONNX Runtime for optimized inference. Implemented batching for throughput optimization. Horizontal scaling with Kubernetes handles load spikes. From Jupyter notebook to production in 2 weeks. MLOps maturity achieved! #mlops #deployment #ai #fastapi
22 days ago
Deployed ML model with FastAPI and Docker. Inference time under 100ms! Used ONNX Runtime for optimized inference. Implemented batching for throughput optimization. Horizontal scaling with Kubernetes handles load spikes. From Jupyter notebook to production in 2 weeks. MLOps maturity achieved! #mlops #deployment #ai #fastapi
23 days ago
Auto-scaling based on custom metrics. CPU usage alone wasn't enough for our workload! Implemented scaling based on queue depth and request latency. Predictive scaling for known traffic patterns (like daily peaks). The cluster now responds to actual business metrics. Right-sizing finally achieved! #autoscaling #cloud #aws #optimization
23 days ago
Deployed ML model with FastAPI and Docker. Inference time under 100ms! Used ONNX Runtime for optimized inference. Implemented batching for throughput optimization. Horizontal scaling with Kubernetes handles load spikes. From Jupyter notebook to production in 2 weeks. MLOps maturity achieved! #mlops #deployment #ai #fastapi
24 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
24 days ago
Layer 2 scaling solutions make blockchain practical. Fast and cheap transactions! Deployed on Arbitrum - 100x cheaper than mainnet. Same security guarantees through rollups. User experience finally matches expectations. The scaling roadmap is working. Ethereum is ready for mainstream! #layer2 #ethereum #scaling #arbitrum
24 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
24 days ago
Standing desk, multiple monitors, Grafana dashboards everywhere. Watching the metrics during a traffic spike. Auto-scaling kicked in perfectly. The infrastructure held. Satisfying! #monitoring #autoscaling #office
24 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
25 days ago
Auto-scaling based on custom metrics. CPU usage alone wasn't enough for our workload! #autoscaling #cloud #aws
25 days ago
AR application for furniture visualization. Customers can see products in their space before buying! ARKit on iOS, ARCore on Android. Accurate scaling was the biggest challenge. Returns dropped 40% after implementation. The technology is finally mature enough for mainstream use! #ar #augmentedreality #retail #visualization
26 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! #kubernetes #k8s #devops
27 days ago
Auto-scaling based on custom metrics. CPU usage alone wasn't enough for our workload! #autoscaling #cloud #aws
27 days ago
28 days ago
Kubernetes cluster is finally production-ready. Auto-scaling handles traffic spikes beautifully! Set up HPA based on custom metrics from our application. During Black Friday, the cluster scaled from 10 to 45 pods seamlessly. Zero downtime despite 10x normal traffic. Worth every hour of setup! #kubernetes #k8s #devops #autoscaling
28 days ago
Layer 2 scaling solutions make blockchain practical. Fast and cheap transactions! Deployed on Arbitrum - 100x cheaper than mainnet. Same security guarantees through rollups. User experience finally matches expectations. The scaling roadmap is working. Ethereum is ready for mainstream! #layer2 #ethereum #scaling #arbitrum
1 month ago
Deployed ML model with FastAPI and Docker. Inference time under 100ms! Used ONNX Runtime for optimized inference. Implemented batching for throughput optimization. Horizontal scaling with Kubernetes handles load spikes. From Jupyter notebook to production in 2 weeks. MLOps maturity achieved! #mlops #deployment #ai #fastapi
