Performance Optimization Strategy Generator

I want to optimize the performance of a web application. The application is built using Python (Django framework) and a PostgreSQL database, hosted on AWS EC2 instances. The main goal is to reduce the average page load time, which is currently at 5 seconds. I suspect the database queries and inefficient caching mechanisms are the bottlenecks. Generate a comprehensive list of optimization strategies, including code-level changes, database optimizations, and infrastructure adjustments. Prioritize strategies that can yield the most significant improvements with minimal effort and risk.

My team is responsible for maintaining a large-scale data processing pipeline that ingests data from various sources, transforms it, and loads it into a data warehouse for analysis. The pipeline is implemented using Apache Spark and runs on a Hadoop cluster. The current processing time is unacceptably long, and we need to identify and address performance bottlenecks. Describe a detailed strategy for optimizing the performance of this data processing pipeline. Include steps for profiling the pipeline to identify bottlenecks, recommendations for optimizing Spark configurations and data partitioning, and suggestions for improving the efficiency of data transformations. Also, consider strategies for optimizing the underlying Hadoop cluster to support the pipeline's performance requirements.

We're experiencing performance issues with our cloud-based microservices architecture. Services are written in Go and deployed using Docker containers on Kubernetes. Latency is high, and we are seeing increased error rates during peak load. Suggest a detailed performance optimization plan. Consider aspects like inter-service communication, resource allocation within Kubernetes, database connection pooling, caching strategies, and monitoring/alerting configurations. Provide specific recommendations for tools and techniques we can use to diagnose and address these performance challenges.