Greetings everyone!!!!!

Let’s begin the phase II of our blog on Aurora serverless-V2.

Part 1 – https://mydbops.wordpress.com/2022/05/22/exploring-auAurora-serverless-v2-for-mysql

Here, I have focused primarily on the migration strategies, hence this blog will be helpful for those who are in a stance to migrate towards serverless V2.

Before entering into the migration strategies, let’s take a look at the feature called “Mixed-Configuration”. and then discuss about the migration strategies

1. Mixed-Configuration: …

Recently, while doing a test process to examine resource usage and the time required to alter the table using pt-osc, it leads to a loss of triggers even though the –preserve-triggers option is specified. I made the decision to recreate the identical circumstance so that everyone could see it.

Test environment : 

OS: Amazon Linux 2

MySQL version: 5.7.40

pt-online-schema-change version: 3.1.0

Before digging deeper, we must first obtain the whole picture. Here is an illustration of the table’s structure.

Table structure:

 …

I’ve had this list on a post-it note on my monitor for all of 2022. I figured it was time to write it down, and reuse the space.

In summary, AWS suffers from the same problem that almost every other product does. It sacrifices improved security for backward compatibility of functionality. IMO this is not in the best practices of a data ecosystem that is under constant attack.

• Storage should be encrypted by default. When you launch an RDS cluster its storage is not encrypted. This goes against their own AWS Well-Architected Framework Section 2 – Security.
• Plain text passwords. To launch a cluster you must specify a password in plain text on the command line, again not security best practice. At least change this to using a known secret from AWS secrets manager.
• TLS for administrative accounts should be the only option. The root user should only be REQUIRE SSL (MySQL syntax).
• Expanding on …

Aurora Serverless V2 is generally available around the corner recently 21-04-22 for MySQL 8 and PostgreSQL, with promising features that overcome the V1 disadvantages. Below are those major features

Features

• Online auto instance upsize (vertical scaling)
• Read scaling (Supports up to 15 Read-replica)
• Supports mixed-configuration cluster ie, the master can be normal Aurora(provisioned) and readers can be in serverlessv2 and vice versa
• MultiAZ capability (HA)
• Aurora global databases (DR)
• Scaling based on memory pressure
• Vertically Scales while SQL is running
• Public IP allowed
• Works with custom port
• Compatible with Aurora version 3.02.0 ie., >= MySQL 8.0.23 (only supported)
…

During a recent Aurora MySQL 8 upgrade process, a number of validation checks have failed. This is an analysis of the error message “present in INFORMATION_SCHEMA’s INNODB_SYS_TABLES table but missing from TABLES table”.

Some background

During a Major Upgrade from Aurora MySQL 5.7 to Aurora MySQL 8.0 the cluster instances were left in an incompatible-parameters state. The upgrade-prechecks.log shed some more light on the situation with

{
            "id": "schemaInconsistencyCheck",
            "title": "Schema inconsistencies resulting from file removal or corruption",
            "status": "OK",
            "description": "Error: Following tables show signs that either table datadir directory or frm file was removed/corrupted. Please check server logs, examine datadir to detect the …

A recommendation we often give to our customers is along the lines of “archive old data” to reduce your database size. There is a tradeoff between keeping all our data online and archiving part of it to cold storage.

There could also be legal requirements to keep certain data online, or you might want to query old data occasionally without having to go through the hassle of restoring an old backup.

In this post, we will explore a very useful feature of AWS RDS/Aurora that allows us to export data to an S3 bucket and run SQL queries directly against it.

Archiving Data to S3

Let’s start by describing the steps we need to take to put our data into an S3 bucket in the required format, which is called Apache Parquet.

Amazon states the Parquet format is up to 2x faster to export and consumes up to 6x less storage in S3, compared to other text formats.

1. Create a snapshot of the database (or …

The RDS Aurora MySQL/PostgreSQL capabilities of AWS extend the High Availability (HA) capabilities of RDS read replicas and Multi-AZ. In this presentation I discuss the different capabilities and HA configurations with RDS Aurora including:

• RDS Aurora Cluster single instance
• RDS Aurora Cluster multiple instances (writer + 1 or more readers)
• RDS Aurora Cluster multi-master
• RDS Aurora Global Cluster
• RDS Aurora Cluster options for multi-regions

Each option has its relative merits and limitations. Each will depend on your business requirements, global needs and budget.

• Presented at Percona Live Online 2021
• …

Up until now we have seen MDS (MySQL Database Service) and MySQL in Azure.
As the Cloud technology keeps moving fast, I thought it would be a good idea to see how to set up a MySQL in Amazon , as a service, that is RDS.

The post MySQL in Amazon (RDS) first appeared on dasini.net - Diary of a MySQL experts.

Recently one of our customers ran into an issue, wherein a bad actor(code) from the application had made the wrong update to 16 M records of a critical table in the database, causing the entire production process to go down. The application Team was able to find the bad actor and block it, our Remote DBA was involved in the Data Recovery/Rollback.

Here I would like to discuss possible recovery methods for the above said scenario

Delayed Slave:

A simple and effective way to recover is by using a delayed slave, RDS started supporting this feature from version 5.6.40 and 5.7.22 i.e., you can induce a SQL thread delay-interval for applying the writes to a slave, detailed implementation is covered in our blog here. It’s …

This week I was evaluating AWS QLDB. Specifically the verifiable history of changes to determine how to simplify present processes that perform auditing via CDC. This is not the first time I have looked at QLDB so there was nothing that new to learn.

What I found was that creating a workable solution with an existing application is hard. Even harder is creating an example to publish in this blog (and the purpose of this post).

First some background.

Using MySQL as the source of information, how can you leverage QLDB? It’s easy to stream data from MySQL Aurora, and it’s easy to stream data from QLDB, but it not that easy to place real-time data into QLDB. AWS DMS is a good way to move data from a source to a target, previously my work has included MySQL to MySQL, MySQL to Redshift, and MySQL to Kinesis, …