Diagnosing performance issues
Performance is a key factor in the success of any web portal. For Power Pages (formerly Power Apps Portals), diagnosing performance issues involves a combination of monitoring techniques, tools, design….
Tag: performance metrics
Failing to set up auto-scaling
Title: The Critical Importance of Setting Up Auto-Scaling in Cloud Environments Introduction In the realm of cloud computing, ensuring that applications can handle varying levels of demand is paramount. Failing….
Not rotating access keys regularly
Regularly rotating access keys is a fundamental practice in maintaining the security and integrity of your systems. Access keys, such as AWS IAM user access keys or service account keys,….
Application Performance Monitoring (APM) tools in cloud
iturn0image1turn0image4turn0image6turn0image8Application Performance Monitoring (APM) tools in the cloud are essential for ensuring the reliability, efficiency, and user satisfaction of modern applications. These tools provide deep insights into application behavior, enabling….
Using SLIs and SLAs in managed cloud services
Using SLIs and SLAs in Managed Cloud Services Introduction In modern cloud environments, organizations are increasingly relying on managed cloud services for everything from infrastructure to software applications. A critical….
AI-driven performance analysis in XR sports
AI-Driven Performance Analysis in XR Sports: The Next Frontier of Athletic Optimization The fusion of Artificial Intelligence (AI) and Extended Reality (XR) is revolutionizing how athletes train, compete, and recover…..
Confusion Matrix
Confusion Matrix in Machine Learning 1. Introduction to Confusion Matrix A Confusion Matrix is a performance evaluation metric used in classification problems. It helps to understand how well a machine….
ROC Curve and AUC
ROC Curve and AUC in Machine Learning The ROC (Receiver Operating Characteristic) Curve and AUC (Area Under the Curve) are essential metrics for evaluating the performance of classification models, especially….
Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score)
Model Evaluation Metrics in Machine Learning Evaluating a machine learning model is crucial for ensuring its effectiveness. Model evaluation metrics provide a way to measure performance, compare models, and fine-tune….
Underfitting vs Overfitting
Underfitting vs Overfitting in Machine Learning Introduction One of the biggest challenges in machine learning is building a model that can generalize well to unseen data. The two common problems….