We know that SQL statement compatibility can change with major database version upgrades and that you should adequately test for them. But what about minor version upgrades?

It is dangerous to assume that your existing SQL statements work with a minor update, especially when using an augmented version of an open-source database such as a cloud provider that may not be as transparent about all changes.

While I have always found reading the release notes an important step in architectural principles over the decades, many organizations skip over this principle and get caught off guard when there are no dedicated DBAs and architects in the engineering workforce.

Real-world examples of minor version upgrade issues

Here are two real-world situations common in the AWS RDS ecosystem using MySQL.

1. You are an organization that uses RDS Aurora MySQL for its production systems, and you upgrade one minor version …

This post was originally published in July 2018 and was updated in July 2023.

Now that Database-as-a-service (DBaaS) is in high demand, there are multiple questions regarding AWS services that cannot always be answered easily: When should I use Aurora and when should I use RDS MySQL?  What are the differences between Aurora and RDS? How do I choose which one to use?

In this blog, we will answer all of these important questions and provide a general overview comparing the two database services, Aurora vs RDS.

Understanding DBaaS

DBaaS cloud services allow users to use databases without configuring physical hardware and infrastructure or installing software. But …

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)
…

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 …

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, …