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Practical Aurora MySQL Operations for Large-Scale Events

Ahead of a major event, what should you prepare in your database, and what should you check first when it goes live? Practice your pre-, during, and post-event response sequence using training Aurora logs of Reader CPU spikes, lock waits, deadlocks, and failovers, along with diagnostic SQL.

2 learners are taking this course

Level Intermediate

Course period Unlimited

MySQL
MySQL
AWS
AWS
aws-aurora
aws-aurora
SQL
SQL
Python
Python
MySQL
MySQL
AWS
AWS
aws-aurora
aws-aurora
SQL
SQL
Python
Python

What you will gain after the course

  • Distinguish CPU utilization from DB load to identify execution bottlenecks versus wait bottlenecks, and determine the order of initial responses.

  • Read lock wait chains, metadata locks, and raw deadlock output using performance_schema and SHOW ENGINE INNODB STATUS.

  • Calculate load contribution from interval differences in query fingerprints and cumulative statistics, then classify actions as immediate, same-day, planned, or deferred based on service impact and contention.

  • We validate Claude’s index recommendations for result equivalence, execution plans, and write costs, then adopt, reject, or defer them.

  • We review baseline metrics, load test stop criteria, connection budgets, and the impact of scaling Readers before the event.

  • After failover, verify that the connection has recovered and manage recurrence by distinguishing between improvements, items not executed, and missing data collection.

Recommended for
these people

Who is this course right for?

  • A backend developer at a loss about what to prepare on the DB side ahead of a large-scale event.

  • SREs and junior DBAs who have a list of slow queries but struggle to decide which ones to fix first

  • Developers and DBAs who want to use AI like Claude to analyze queries, but are wary of trusting it blindly.

Need to know before starting?

  • Basic Concepts of SELECT, JOIN, and Indexes

  • Basic Understanding of Aurora and RDS Writer–Reader Architecture

  • Run terminal commands and Python 3.10 or later

Hello
This is dorian05202988

Career Verified

A data craftsman with over 20 years of experience in databases and IT. As a DBA and manager of a DB Platform team, I work with database platforms and specialize in MySQL, PostgreSQL, Oracle, MongoDB, SQL tuning, AWS, Terraform, and Python. Drawing on experience in the gaming, finance, and IT services industries, I explain database and cloud architecture. I have published 『Oracle Practical Tuning: Learning SQL Patterns』 and 『Oracle Pro*C Practical Project Guide』, and have presented on serverless architectures, database selection, and multi-database strategies at AWS Summit 2018 and 2019 and DataYa Nolja 2020. Recently, I have been working on slow-query analysis and tuning recommendations using Bedrock LLM, automated DB specification sizing, and query workflows through a DB metadata MCP server and Slack bot. I explain database automation for developers and AI applications for non-developers through hands-on exercises tailored to the audience and objectives of each course. Rather than applying AI suggestions as-is, I teach a decision-making framework that verifies result equivalence, execution plans, and observability conditions, and defers action when the supporting evidence is insufficient. Company operational data and credentials are not included in the course materials.

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Curriculum

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60 lectures ∙ (3hr 6min)

Course Materials:

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