autoscaling
Stop Wasting GPU Budget: Autoscaling AI Inference on Kubernetes with KEDA
The rush to deploy Large Language Models (LLMs) and generative AI has created a massive infrastructure bottleneck. Platform engineering teams are spinning up expensive GPU node pools on Kubernetes, but they are ...
How to Keep Cloud-Native Applications Running During DDoS-Scale Traffic Surges
Prepare your cloud-native apps for chaos! Discover essential strategies to handle traffic surges, from resilient architecture to real-time monitoring, ensuring your applications thrive under pressure ...
Kubernetes v1.35 Arrived, Right On Workload-Aware Schedule
Discover the latest enhancements in Kubernetes workload scheduling, including the Workload API and gang scheduling features aimed at optimizing application performance and management ...
Closer to Serverless for Databases on Kubernetes
Running stateful elements like databases on Kubernetes has led to new and unique challenges and opportunities, particularly in autoscaling ...
Scaling Kubernetes With AI and Machine Learning
Applying AIOps models and moving toward autonomous infrastructure can reduce Kubernetes complexity and improve scale for microservices applications ...
StormForge Extends Kubernetes Autoscaling Capability
StormForge today announced it has expanded its ability to vertically or horizontally scale Kubernetes pods automatically using machine learning algorithms. Rich Bentley, product marketing manager for StormForge, says the latest version of ...
Best of 2021 – How Not To Use Kubernetes: 5 Failure Stories
As we close out 2021, we at Container Journal wanted to highlight the most popular articles of the year. Following is the fifteenth in our series of the Best of 2021. I ...
Scaling is Still Hard. Machines Make it Easier
At StormForge, we’ve been focused on extracting the most from your applications. As we’ve talked at length about optimization, sustainability and related concepts, one implementation topic has reared its head over and ...
