To maintain healthy and scaleable Kubernetes deployments it is essential to have observability mechanisms in place. These mechanisms can range from extremely manual bootstrapped solutions to highly sophisticated software, some of which incorporate AI and machine learning. However, it's crucial to take into account the right information, at the right time, regardless of where the organization is on the transformation spectrum or how many tools they are using.
In this virtual event, we will discuss what organizations should be observing to optimize the troubleshooting process. We will also cover the best practices for deriving useful and actionable insights from this data and how to take advantage of AI and machine learning in the process.
If you're interested in Kubernetes troubleshooting and how AI and machine learning can enhance performance, this session is for you.
🎁 🎁 Two raffle prizes will be given away during the event by our sponsors Sosivio & CloudRoads.
🎓 What you will learn
Common Challenges in Kubernetes Troubleshooting
Essentials for Real-time Collection and Analysis
Best practices for AI in Kubernetes Troubleshooting
How AI can be used to troubleshoot Kubernetes and what tools and techniques are involved in the process?
👨🏻💻 👩💻 Who Should Attend
IT leaders interested in learning more about AI in cloud-native and Kubernetes