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Introduction to the five primary types of analytical workloads on AWS: Batch, Interactive, Messaging, Streaming, and Machine Learning. This foundational lesson will define each workload by its characteristics, such as data temperature (hot vs. cold), latency expectations (milliseconds to hours), and common use cases. It will set the context for understanding why different AWS services are designed for specific processing needs.
Introduction to SSH hardening and migrating from passwords to SSH keys. This lesson explains the vulnerabilities of password-based authentication (brute-force attacks) and the superiority of public-key cryptography. It includes a practical, hands-on lab where you will generate a modern Ed25519 key pair, use ssh-agent to manage your private key, and securely copy your public key to a remote server using ssh-copy-id to enable passwordless login.
This lesson introduces the core principles of Site Reliability Engineering (SRE) and the foundational role of observability. We will define reliability as the probability of a system performing its function over time and differentiate it from availability. The main focus will be on the Google Cloud Operations Suite, covering: Cloud Monitoring for collecting time-series data (metrics), Cloud Logging for centralized event log management, and Cloud Alerting for creating proactive notifications based on metric thresholds. We will also briefly touch upon open-source alternatives like Prometheus and Grafana.
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