Inside Releem: How AI Is Reshaping MySQL Performance—Insights from Roman Agabekov

Releem is an AI-powered tool designed to take the pain out of MySQL performance tuning. It continuously monitors your database, detects performance issues, and automatically recommends or applies configuration changes and query optimizations—so you don’t have to. Whether you're using MySQL, MariaDB, or AWS RDS, Releem simplifies everything from identifying slow queries to fine-tuning server settings, all in one place.

With its open-source agent and smart recommendations, Releem helps teams move beyond manual logs, EXPLAIN analysis, and trial-and-error index tuning. It’s database optimization without the grunt work.

But what inspired this shift toward full automation in MySQL performance? And where is Releem headed next?

We spoke with Roman Agabekov, Releem’s founder, to learn more about the vision behind the product—and how it’s changing the way developers and DBAs manage databases. Read the conversation below:

TDT: How does Releem integrate with existing Drupal setups without adding overhead or complicating workflows?

Roman: Releem integrates with MySQL directly, so it doesn’t require any changes to your Drupal codebase. It collects performance data in the background using a lightweight agent. All optimization happens outside the Drupal  application, so there’s no performance impact or workflow disruption. You just install Releem, and it starts analyzing queries and MySQL configuration automatically - no Drupal-specific setup needed.

TDT: What level of customization does Releem offer for teams that want more control over indexing and optimization recommendations?

Roman: Releem offers customization through its Dashboard and API (we're working on it now). Teams can review and approve recommendations before applying them. It’s designed to be flexible - you can use it in fully automated mode, or keep full manual control depending on your needs.

TDT: What challenges did you face when building an automated solution for something developers usually handle manually — and how did you solve them?

Roman: Making a performance recommendation isn’t just about knowing what could be better - it’s also about knowing what’s safe to change, what tradeoffs are acceptable, and what the risk of regression is. This is where traditional developer intuition plays a big role - and where automation has to be cautious.

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There’s a risk in changing MySQL configuration or adding indexes automatically, especially on production systems. A bad recommendation might improve one query but degrade others. Worse, it could cause instability.

Solution:

We started with a rule-based expert system, where each recommendation is based on known best practices and verified performance heuristics. Then we layered on guardrails to avoid risky changes (e.g., avoiding indexes that are too large, or not changing innodb_buffer_pool_size too aggressively).

To measure effectiveness, we track performance before and after every change. This feedback loop allows us to refine the logic over time - and it forms the basis for a more advanced, AI-powered tuning engine we’re developing. Over time, Releem will learn from real-world outcomes to improve its future decisions.