DEV Community: Roman Agabekov

Laravel Deadlocks: Causes and Fixes

Roman Agabekov — Wed, 05 Aug 2026 14:54:44 +0000

Deadlocks show up once an app has enough traffic for queries to overlap. They rarely appear in development, which makes them frustrating to understand the first time you see one. Plus, deadlocks are hard to reproduce locally and even harder to diagnose after the fact.

Laravel adds its own twist here. The framework makes parallel work easy with queues, Horizon, scheduled tasks, and event dispatching, but that also means multiple processes start touching the same rows at the same time. A local setup with a single queue worker won’t reveal any of this. Production with 10 Horizon workers running jobs in parallel will.

This guide explains what a deadlock is, why it happens in Laravel workloads, and how to debug and reduce it without turning your codebase upside down.

What is a deadlock?
Common deadlock patterns in MySQL
What do developers see in Laravel?
6 Reasons why deadlocks happen in Laravel apps
Why deadlocks feel random in production
How to debug deadlocks in production
How to reduce and prevent deadlocks in Laravel
Tools that help monitor and understand deadlocks
Where this leaves you

What is a deadlock?

A deadlock happens when two transactions hold locks that the other needs. Both stop and wait. Neither can progress, so MySQL cancels one to break the stall and keep the server moving. The canceled query receives a deadlock error, and the other continues normally.

A basic example:

Transaction A updates row 1, then waits on row 2.
Transaction B updates row 2, then waits on row 1.

They are stuck. The fix is not manual unlocking. MySQL automatically ends the cheaper transaction and logs the cycle. Deadlocks are normal, not a sign that the database is breaking down. They’re a side effect of concurrency and the way InnoDB enforces isolation.

Common deadlock patterns in MySQL

MySQL tends to reveal a handful of recurring deadlock shapes or types. Each comes from the way workers, queues, and HTTP requests interact with the same tables under load.

Here are the deadlock types you’ll see most often:

Update-Update: two transactions update related rows in opposite order.
Select-for-Update conflicts: one worker locks rows for processing while another tries to modify them.
Auto-increment inserts: concurrent inserts collide with follow-up updates or related-table writes.
Gap-lock collisions: range queries or non-selective indexes lock more rows than expected.
Insert intent conflicts: multiple workers inserting into the same index gap at once.
Same-PK inserts: two writers try to insert the same PRIMARY KEY at the same time.
Foreign-key interactions: parent/child updates and deletes taken in different order.
Long transactions: broad locking footprints collide with fast writes.

What do developers see in Laravel?

When a deadlock occurs, Laravel doesn’t show the lock cycle or the conflicting query. It only reports the error returned by MySQL:

SQLSTATE[40001]: Deadlock found when trying to get lock; try restarting transaction

This is the message teams see in Laravel application logs, Horizon failed jobs, queue worker output, Sentry, Bugsnag, or other APM tools. It confirms that one transaction was rolled back, but it doesn’t tell you:

Which transaction it conflicted with
Which table or index was involved
Which rows MySQL locked**
Why the lock order diverged

Most Laravel deadlocks come from two recurring patterns:

Queries lock more rows than expected

This often happens when a query scans more of the table than intended. Maybe because an index is missing or not selective enough or because Eloquent issues an implicit SELECT before the update, or because REPEATABLE READ expands the locked range.

Queries touch tables in a different order

If two workers update the same models but reach the underlying tables in different sequences, MySQL ends up with a mismatched lock order and cancels one of them.

The next section shows how these patterns appear in real Laravel code and the adjustments you can make to reduce them.

6 Reasons why deadlocks happen in Laravel apps

Laravel code doesn’t cause deadlocks by itself. The framework generates straightforward SQL. The problems start when the same table or row is touched by several workers at the same time. Small differences in timing create new lock sequences.

1. Jobs or requests update the same rows

Symptom

If two workers touch the same row in a different order, a deadlock can form.

Example

// Worker A
Order::where('id', $id)->update(['status' => 'processing']);

// Worker B (same row, different path)
Order::find($id)->update(['last_checked_at' => now()]);

Cause

Tables like orders, invoices, carts, and inventory often receive overlapping updates from web requests, queue workers, and scheduled tasks. Laravel makes these updates simple to express with Eloquent, but each update may include hidden reads or joins that widen the lock scope.

When two execution paths update the same record but reach it in different sequences, MySQL ends up with a mismatched lock order. If you’re also loading related models (->with(...)), the initial SELECT may lock more rows than expected.

Fix

Use consistent update paths for high-traffic tables.
Add the exact index your lookup uses (id, id,status, etc.) to keep row locks narrow.
Consider SELECT . . . FOR UPDATE if you truly need exclusive access.

2. Long transactions with multiple queries

Symptom

Deadlocks occur inside DB::transaction() even though each query seems harmless on its own.

Example

DB::transaction(function () use ($order, $inventory) {
    $order->update(['status' => 'paid']);
    $inventory->decrement('count');  // touches a second table
});

Another worker might execute the same two statements but in the opposite order.

Cause

A DB::transaction() block is convenient and usually correct, but it also groups several operations under the same lock footprint. If one worker updates orders then inventory, while another updates inventory then order, the locking order diverges and a deadlock becomes possible.

The more steps there are inside a transaction, the more places this can happen.

Fix

Keep transactions short and narrow.
Always touch tables in the same order throughout the app.
Move slow operations (API calls, heavy queries) outside the transaction.

3. Hidden locking from Eloquent

Symptom

A simple model update deadlocks, even though you’re updating by primary key.

Example

$user = User::where('email', $email)->first();
$user->update(['last_login_at' => now()]);

The first query may scan more rows than expected if the column isn’t indexed.

Cause

Eloquent often performs a SELECT before it performs an UPDATE. If the SELECT touches more rows than you expect (because an index is missing or not selective enough), the transaction holds locks longer and on more rows. Range locks give deadlocks room to form.

Fix

Add the missing index (in this example, an index on email).
Avoid first() + update() patterns on non-indexed columns.
Use whereKey() or direct update() calls when possible.

4. High concurrency on a busy queue or Horizon setup

Symptom

Deadlocks appear only when Horizon or queue workers are scaled up.

Example

$product->increment('views');
LogView::create([...]);

With the same job running in parallel, each worker may hit products and log_views in different sequences depending on load, caching, or conditional code branches.

Cause

Queue workers running the same job type at the same time take different execution paths. The code is the same, but the order of queries is not guaranteed. High concurrency exposes lock order issues that do not show up locally.

Fix

Use dedicated queues for heavy write operations so they run serially.
Audit your jobs for conditional branching that changes query order.
If writes are frequent, consider moving them into batched updates or a single “writer” service.

5. Schema shape that increases lock ranges

Symptom

Deadlocks point to unexpected rows or ranges in the lock graph, even though the code only touches one model.

Example

Post::where('category_id', $id)->update(['updated_at' => now()]);

Searching on a non-selective column forces a range scan. In this case, if category_id isn’t indexed or is low-cardinality, MySQL may lock a much broader range.

Cause

Sometimes the deadlock has nothing to do with code structure. Missing or incomplete indexes may force MySQL to choose a less efficient path. Under REPEATABLE READ that can mean gap locks, next-key locks, or broad range locks that collide with other updates – even unrelated ones.

Fix

Add the right composite indexes for your most common lookup patterns.
Avoid large range updates. Break them into smaller batches if possible.
Review slow queries to confirm the optimizer has a narrow path.

6. Model events, mutators, and touches() adding hidden queries

Symptom

An update() call deadlocks even though the row being updated is indexed and the query looks simple.

Example

class Comment extends Model
{
    protected $touches = ['post'];
}

$comment->update(['body' => $newBody]);

This single update silently triggers another update on the related posts row.

Cause

Eloquent model events (saving, saved, updating, etc.), attribute mutators, and touches() relationships all introduce extra queries behind the scenes. If two workers update different comments attached to the same post, you now have multiple hidden writes targeting posts.id. Those extra writes widen the lock footprint and create new lock-order paths that weren't obvious from the code.

Fix

Disable touches() for high-write tables.
Audit model events for extra queries and move heavy logic into jobs.
Use inline DB::table()->update() where you need a truly minimal write.

Why deadlocks feel random in production

Developers often report that deadlocks “come out of nowhere.” The behavior feels random because the timing is influenced by factors you don’t see during local testing. The lock sequence changes slightly with each request, which makes the incidents look unrelated even when they come from the same pattern.

Situations that create this “random” behavior include:

Request traffic arriving in a slightly different order
Queue workers finishing tasks at different speeds
Query plans shifting when MySQL adjusts cost estimates
Background jobs overlapping with normal writes
Large reads that occasionally scan more rows than expected

These changes reorder the locks taken inside MySQL. You may never see the same pattern twice, but the underlying cause is usually stable. It only appears chaotic because the lock collisions depend on micro timing that varies under load.

How to debug deadlocks in production

Laravel’s exception messages help you detect a deadlock, but the real source of truth is the MySQL deadlock report. MySQL logs the full lock cycle so you can see what happened. The more you read these traces, the faster you can spot the problem.

1. Pull the deadlock details from MySQL

Use one of these methods:

SHOW ENGINE INNODB STATUS – returns the most recent deadlock
Performance Schema:
- events_transactions_history_long
- data_locks
- data_lock_waits
MySQL error logs if deadlock logging is enabled

2. Read the lock information

Look closely for three parts:

The victim query
The conflicting query
The locked index and row ranges
The order in which each transaction acquired locks

A real deadlock report looks like this

------------------------
LATEST DETECTED DEADLOCK
------------------------
*** (1) TRANSACTION:
TRANSACTION 123456, ACTIVE 0 sec starting index read
mysql tables in use 1, locked 1
LOCK WAIT 5 lock struct(s)
MySQL thread id 98, OS thread handle 140294
query id 5542 Update order_items set quantity = 3 where id = 42

*** (1) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 27 page no 123 n bits 72
index `PRIMARY` of table `order_items` trx id 123456 lock mode X locks rec but not gap
Record lock, heap no 8 PHYSICAL RECORD: n_fields 5; (...)

*** (2) TRANSACTION:
TRANSACTION 123457, ACTIVE 0 sec starting index read
mysql tables in use 1, locked 1
5 lock struct(s)
MySQL thread id 99, OS thread handle 140310
query id 5543 Update orders set status = 'paid' where id = 10

*** (2) HOLDS THE LOCK(S):
RECORD LOCKS space id 27 page no 123 n bits 72
index `PRIMARY` of table `order_items` trx id 123457 lock mode X

*** WE ROLL BACK TRANSACTION (1)

Transaction 1 was rolled back, so it’s the victim query. Transaction 2 continued on, so it was the conflicting (and winning) query. The query id tells you exactly which statements were involved in the locking.

Deadlocks are often caused by the database needing to lock more rows than expected. If you see a large range on a table that should be handled by a narrow index, that is a hint.

3. Check the order of operations

Compare the order of queries between the transactions. If they touch rows in a different sequence, that’s often the direct cause.

For example, if one part of the code updates a parent model before its related child, and another updates the child before the parent, the lock order shifts.

4. Try to reproduce locally

A small script with parallel workers often reveals the inconsistent locking order. Even if you don’t hit the deadlock, the mismatched query order becomes visible.

If you want to go deeper into how MySQL records deadlocks internally and how to interpret these reports in more detail, take a look at a separate guide on MySQL deadlock detection.

How to reduce and prevent deadlocks in Laravel

You cannot remove deadlocks completely, but you can reduce how often they happen and how long they take to debug. Most fixes come from tightening transaction scopes and improving lock predictability.

1. Keep transactions short

Wrap only the queries that truly need to happen together. Every extra query widens the lock footprint.

DB::transaction(function () use ($id) {
    Order::where('id', $id)->update(['confirmed' => true]);
});

Avoid loading relationships or running expensive SELECTs inside the transaction when possible.

2. Update rows in a consistent order

If two parts of your app modify related rows, standardize the order. For example, always update the parent before the child or always update by primary key in ascending order. When updates always lock rows in the same sequence, deadlocks drop sharply.

3. Use row-level locks where needed

Laravel’s query builder supports row-level locking with lockForUpdate():

$item = Inventory::where('sku', $sku)->lockForUpdate()->first();
$item->decrement('quantity');

Important: This requires a unique index on 'sku' to lock a single row. Without it, MySQL may lock a range of rows, increasing deadlock risk.

This helps when concurrent workers modify the same inventory, balance, or counter rows. It narrows the lock to the exact row instead of a larger range.

4. Add the right indexes

Deadlocks often come from queries that lock many rows. Missing or weak indexes enlarge those ranges. Look for:

Queries scanning a full table to find a single record
Updates that use a non-selective index
JOINs that lock broader ranges than expected

Better indexing means fewer rows touched, which means fewer collisions.

5. Avoid unnecessary reads inside writes

If a write operation requires a read, try to move the read outside the transaction or rely on known primary keys instead of scanning.

6. Implement retry logic for deadlock-prone operations

Deadlocks are transient errors—the rolled-back transaction can usually succeed if retried immediately. Laravel supports automatic retries in transactions:

// Laravel 8+
DB::transaction(function () use ($order) {
    $order->update(['status' => 'paid']);
    $order->inventory()->decrement('count');
}, attempts: 3);

For more control, use manual retry logic:

use Illuminate\Database\QueryException;

retry(3, function () {
    DB::transaction(function () {
        // your logic here
    });
}, sleepMilliseconds: 100, when: function ($exception) {
    return $exception instanceof QueryException 
        && str_contains($exception->getMessage(), 'Deadlock found');
});

This approach is especially useful for queue jobs that process high-contention rows like inventory counts or user balances.

Tools that help monitor and understand deadlocks

To debug deadlocks properly, you need visibility into both sides of the conflict:

Which queries were running
Which tables and indexes were locked
How MySQL’s lock order diverged

Many teams rely on logs, APM tools, or exception trackers to spot deadlocks. APM systems like Sentry are great for surfacing the exception, but they don’t record the conflicting transaction, the locked index, or the range of rows involved. It’s incomplete information.

Database monitoring platforms add a bit more depth:

Percona Monitoring and Management (PMM) collects MySQL deadlock events and shows the raw InnoDB report
Navicat Monitor displays captured deadlock graphs in a UI and makes single-event lock cycles readable
MONyog pulls MySQL deadlock details and provides alerts, but focuses on event detection rather than suggesting fixes.
Releem captures every deadlock, stores the full history, groups recurring incidents, classifies the deadlock type, and provides guidance on how to resolve the underlying lock pattern.

Where this leaves you

Your first Laravel deadlock can be a bit of a surprise. It typically appears when your application scales with Horizon workers, queued jobs, and scheduled tasks all touching the same rows. It feels unpredictable until you learn to read MySQL's lock report, but even then you only see one incident at a time.

To actually prevent these patterns, you need ongoing visibility into how transactions overlap and what queries keep causing pressure.

Some teams use tools like Releem to keep this visibility continuously, so deadlock patterns are easier to spot before they turn into recurring incidents.

Safe automation for MySQL index recommendations | What’s New At Releem

Roman Agabekov — Mon, 03 Aug 2026 07:40:00 +0000

Over the past few months, we’ve been expanding Releem into more database environments while making recommendations easier to understand and act on. June continues that work with updates designed to shorten the path from identifying an issue to resolving it safely.

This release introduces a more guided Installation Wizard, broader PostgreSQL configuration coverage, improvements to reporting and reliability, and a new workflow for safely applying index recommendations.

Together, these updates bring Releem closer to our vision of a single workflow for database performance, resource usage, security, and availability.🎯

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Product Updates

Safe automation for index recommendations

Releem can now safely apply index recommendations. Every change goes through a guarded workflow designed to protect availability and preserve a recovery path:

Before a schema change is sent to the Agent, Releem validates whether the affected data can be recovered and whether the operation can run online in that environment.
The workflow accounts for the database distribution, version, storage engine, and table structure when selecting an eligible execution method. If the database cannot support an online backup, point-in-time recovery is unavailable, or the change would require a blocking operation, Releem stops before execution.
The Agent then checks available space in the backup and database filesystems and confirms that the required backup tools are installed. It creates a backup and runs a schema-change dry run before applying the index. Any failed prerequisite, backup, or dry run aborts the change. This gives teams a controlled path from identifying a missing index to applying it safely.

Added multi-step Installation Wizard

The new Installation Wizard guides users through three setup decisions:

Which database they want to connect
Where the database is running
How Releem should be installed

The wizard supports MySQL, MariaDB, and PostgreSQL. For self-managed environments, users can choose Linux, Windows, WHM/cPanel, Docker, or Kubernetes. Managed cloud options include AWS, Google Cloud, and Azure.

For Linux and Windows installations, the database password is no longer entered in the web interface. The generated script requests it locally during installation, keeping the credential out of the browser-based setup flow for added security.

Expanded PostgreSQL configuration recommendations

Releem now provides recommendations for a broader range of PostgreSQL settings, giving users more control over autovacuum behavior, memory allocation, storage use, parallel query execution, and idle transactions.

The expanded recommendation set includes:


– autovacuum_max_workers – autovacuum_vacuum_cost_limit – autovacuum_vacuum_cost_delay – autovacuum_naptime – autovacuum_vacuum_scale_factor – autovacuum_vacuum_threshold	– autovacuum_analyze_scale_factor – autovacuum_analyze_threshold – idle_in_transaction_session_timeout – hash_mem_multiplier – max_parallel_workers_per_gather – work_mem_recommended

These additions allow Releem to make more specific recommendations based on how each PostgreSQL database is operating.

Show just the recommended configuration changes

Recommended Configuration now includes a Show just changes view, allowing users to focus on the settings that differ from their current database configuration instead of reviewing every available value.

Reports for invited users on shared servers

Invited users can now receive reports for servers shared with them. This keeps collaborators informed about the databases they work on without requiring the server owner to forward updates manually.

Removed an irrelevant security check for cloud-managed MySQL and MariaDB

Releem previously displayed a symlink security check for managed cloud MySQL and MariaDB instances, even though users cannot change the related setting or access the underlying host.
The check is now skipped for cloud-managed instances, removing a warning and advice that users could not act on.

Fixed deadlock analysis for names with special characters

Deadlock analysis can now parse quoted database and table names that contain special characters. We update the parser’s regular expressions after finding cases where these names prevented Releem from reading the deadlock output correctly.

Fixed an error when adding servers simultaneously

We fixed an error that could occur when two servers were added at the same time. Parallel server onboarding can now complete without one addition interfering with the other (Closes #515).

Releem Now Supports PostgreSQL, Azure MySQL, and Better Windows Automation

Roman Agabekov — Mon, 22 Jun 2026 06:27:10 +0000

Releem now supports more database environments, helping teams monitor database health, review recommendations, and improve security, performance, and reliability from one workflow.

In April and May, we added PostgreSQL support, Azure Database for MySQL support, Windows installation improvements, automated configuration changes for Windows, and several Query Analytics updates to make recommendations faster to understand. 🎉

We’ve also been sharing more of our database research with the community. This month, Gabriel presented a deep technical session at Percona Live titled The Hidden Lives of Temp Tables: Unraveling MySQL Internal Management.

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Product Updates

- Expanded database support to PostgreSQL

Releem now supports PostgreSQL, giving teams a more consistent way to monitor database health, receive recommendations, and manage performance across MySQL, MariaDB, and PostgreSQL environments. Health checks, security checks, query analytics, activity monitoring, and configuration tuning are currently in place.
Read the PostgreSQL installation docs

- Expanded database support to Azure Database for MySQL

Releem now supports Azure database for MySQL, making it easier to connect managed MySQL environments on Azure and bring them into the same database management workflow as other supported databases (Closes #265).
Read the installation docs

- Improved Windows installation and automation

We added a Windows installer and helper scripts to simplify installation, updates, apply, and rollback workflows on Windows. This reduces manual setup and makes it easier to keep Releem Agent installed and up to date in Windows environments (Closes #436).
Read the Windows installation docs

- Safe configuration changes on Windows

Releem can now safely apply approved configuration changes on Windows. Teams can review recommendations in the dashboard, approve them with a click, and let Releem apply the selected changes automatically.

- Query recommendations now shown in Query Analytics

Query Analytics now shows query recommendations directly inside the analytics tab. Instead of clicking a button to request results, you can see available recommendations immediately and move from identifying expensive queries to reviewing what can be improved.

- Last analysis details added to Query Analytics

Query Analytics now shows when each SQL query was last analyzed with a timestamp displayed in this format: Analyzed at: 2026.5.29 20.01. This helps teams understand whether recommendations reflect recent workload activity, which is especially useful after deployments, traffic changes, or configuration updates.

- Configurable Security Checks

Releem now allows you to disable Security Checks that are not relevant to your environment. This gives teams more control over security monitoring and helps reduce noise from checks that do not apply to a specific system configuration. A special thanks to our early user Jeff for suggesting this improvement 🙌 (Closes #472)

- Demo server added for new users

New users now get access to a demo server. This makes it easier to explore the Releem dashboard, review the recommendation workflow, and understand the product before connecting to a production database.

- Notifications for invited users

Invited users now receive weekly reports, recommendations and other notifications, so partners and teams can bring additional users into the workflow more easily.

- Agent security fixes

We shipped security fixes for Releem Agent as part of our ongoing work to keep the Agent safer and more reliable in production environments.

What's New At Releem - WHM/cPanel integration is available

Roman Agabekov — Thu, 30 Apr 2026 22:00:13 +0000

We spent March focused on expanding query optimization, building out partner integrations, continuing PostgreSQL testing, and improve the overall experience for hosting providers and teams using Releem.

We also had the chance to connect with the hosting community at CloudFest. There, we met with hosting providers interested in partnering with Releem to offer Database Advisor to their customers. I gave a talk on Database Advisor for teams running databases without a DBA.

Gabriel presented a deep technical session at Scale23X titled The Hidden Lives of Temp Tables: Unraveling MySQL Internal Management.

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.

Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Product Updates

Batch SQL query analysis and recommendations

You can now see recommendations for all queries directly in Query Analytics without any additional clicks, and save them to the Query Optimization tab for further review and optimization.

If no issues are found, the result shows that the query was analyzed along with the timestamp of the latest check, so you can clearly see what was reviewed and when.

Releem continues to automatically identify the most impactful queries based on workload and adds them as discovered opportunities in the Query Optimization tab.

Custom SQL query optimization

You can now analyze and get recommendations for your own SQL queries, not just the ones Releem detects automatically. Developers can review and optimize queries before they reach production. In Queries & Schema plate go to Query Optimization tab and press + Add Custom Query

WHM/cPanel integration

Releem also integrates with WHM/cPanel, simplifying the installation process and providing access to the Releem dashboard directly from WHM. During installation, Releem disables cPanel auto-tuning rules to ensure compatibility.

Learn more in the documentation.

API and WHMCS integration for hosting partners

We released an API for hosting partners, enabling programmatic integration of Releem into hosting platforms and making it possible to offer Database Advisor to VPS, dedicated, and cloud server customers.

Releem also integrates with WHMCS, allowing providers to sell and manage Database Advisor as an add-on through their existing billing workflows.

Get the partner deck to learn more about integration and partnership options.

AWS Aurora Serverless support

We added support for AWS Aurora Serverless, bringing Releem’s performance analysis and recommendations to these environments (Feature request #477).
The installation process is the same as for AWS RDS.

Deadlock export to CSV

Detected deadlocks can now be exported to CSV for external analysis and reporting (Feature request #503).

Improved data collection performance

We fixed an issue in how Releem queried table_io_waits_summary_by_index_usage reducing unnecessary full table scans on servers with many databases (Issue #500).

Uninstallation dependency fix

The agent no longer downloads unnecessary dependencies during uninstallation (Issue #466).

Duplicate index detection improvement

We improved duplicate index analysis to account for foreign key-backed indexes, helping prevent unsafe recommendations during index optimization (Issue #478).

Expanded query parser support

Releem now supports optimization for queries that start with '(' instead of 'SELECT' (Issue #427).

Offline agent apply-task fix

We fixed an issue that allowed configuration apply tasks to be scheduled while the agent was offline (Issue #311).

What’s New At Releem - January 2026

Roman Agabekov — Thu, 05 Mar 2026 17:01:47 +0000

In the first month of the new year, we focused on practical improvements for the Dashboard, Platform, and Agent, while continuing development on a set of larger integrations that are nearing release. We’ll be sharing details soon.

In March, we’ll be at CloudFest in Germany (23–26 March), and you can find us in Startup Alley. If you’re planning to attend, let us know so we can connect in person and discuss database performance, automation, and partnership opportunities.

For Releem Community members, we have free tickets available.
To claim your free ticket and save €499, just send us request.

We also shipped Dashboard Sharing 💪 This was something we initially treated as a lower-priority request, but it kept coming up. Eventually it became clear it was blocking teams from using Releem together, so we moved it up and shipped it.

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Updates to Releem Dashboard

This month’s dashboard updates concentrate on making Query Analytics easier to work with and streamlining how you handle optimization recommendations:

Filtering control statements

You can now filter out control statements such as COMMIT, USE, and similar commands inside Query Analytics. This helps isolate performance-relevant queries without noise from session or transaction control statements (Closes #457).

Improved query optimization workflow

You can now delete optimization recommendations directly from the interface, with a confirmation step to prevent accidental removal.

Filter queries by status

Easily filter optimization recommendations by status to focus only on discovered, custom or optimized items.

Optional schema checks

You can now disable schema checks when they’re not relevant to your database environment.

Google authentication

Google Sign-In is now available during new account registration, making it faster to get started with Releem.

Updates to Releem Platform

We pushed out several fixes this month to improve reliability and compatibility:

Fixed duplicate entry errors during multiple team member invitations (Closes #489).
Fixed InnoDB index key size detection logic (Closes #487).
Fixed configuration application issues for RDS MariaDB instances (Closes #484).

Updates to Releem Agent

We simplified Releem Agent installation for WHM/cPanel environments.

The agent received security and performance improvements:

Updated Go and dependencies to the latest versions, resolving critical and high-severity CVEs.
Removed envsubst from the Agent image to eliminate unnecessary vulnerability exposure.
Fixed an issue that triggered full table scans during constraint metadata collection, reducing impact on database servers (Closes #493).

Events

We spoke at AI DBA Conf and MariaDB Day in Brussels during FOSDEM, connecting with DBAs and engineers focused on automation and database performance.

If you missed these sessions, you can watch them here:

When “MySQL” isn’t actually MySQL

Roman Agabekov — Tue, 17 Feb 2026 14:23:57 +0000

I was recently looking at engine distribution across a few thousand production database instances.

What stood out is that some teams believed they were running MySQL, but were actually on MariaDB.

In most cases this isn’t confusion. It’s environment defaults.

Many Linux distributions replaced MySQL with MariaDB years ago. Hosting panels and cloud images often install MariaDB by default. The mysql client works the same. ORMs abstract most differences. From the application layer, everything looks like “MySQL.”

Is your database engine an intentional architectural choice, or something inherited from your base image or hosting stack?

Releem 2025 Recap: Building a Database Advisor for Developer Teams

Roman Agabekov — Thu, 22 Jan 2026 15:20:10 +0000

Hello friends 👋

2025 was the year we finally had the team we needed.

For most of Releem's existence, I was the bottleneck. Features sat in backlogs. Support tickets aged. Every decision waited on me.

Getting Victor and Dmitrii full-time changed that overnight. Features moved from idea to production faster, and more time went into tickets, feedback, and edge cases.

We also welcomed the TuningWizard team and their founder Gabriel to Releem. Their hands-on SQL optimization experience directly shaped how we analyze queries today and pushed us to raise the bar on accuracy and safety.

The scale still surprises me. We reached milestones that honestly felt far away when we started:

348 billion SQL queries collected
808 million API requests
714,000 schema recommendations
6 million query recommendations
571,000 deadlocks detected and analyzed
53,000 config tuning suggestions

Around 1,000 new users joined along the way 🚀

What we shipped

On the product side we spent most of the year improving visibility into problems that usually surface too late, and adding automation that is safe to trust in live systems. This included:

Real-time deadlock detection with root cause analysis
Live visibility into blocking and long-running queries
Schema checks for missing, unused, and redundant indexes
Full configuration history with before-and-after performance metrics
Full support for GCP Cloud SQL
Per-server access control and user roles

Oh, and Dark Mode🌙. Users really wanted dark mode.

Thank you

Behind the scenes, the team ran more than 100 live demos, answered over 1,400 support questions, shipped 1,292 commits, and deployed the platform roughly 200 times.

None of this would be possible without everyone who was willing to try something new, report issues, ask hard questions, and push us to do better. Thank you to our early adopters, our customers, and the broader database community for the trust and feedback throughout the year ❤️

We are proud of what we built in 2025 and excited to keep going in 2026.

What's New At Releem - November 2025

Roman Agabekov — Wed, 24 Dec 2025 22:18:39 +0000

Another month wrapped up at Releem, and this month we focused on removing friction in everyday workflows.

We finally brought Dark Mode to Releem Dashboard 🎉 It took longer than expected, with small UI details needing clean up before it was ready to ship. We quietly rolled the feature out, but a few dozen users enabled it right away!

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Updates to Releem Dashboard

We’ve shipped a set of dashboard improvements focused on usability, collaboration, and the workflows you use everyday:

Dashboard Sharing & User Roles

You can now invite users to shared dashboards per server through server Settings and assign roles (Issue #279):

Viewer – Read-only access to dashboard and insights
Editor – Can change settings and apply recommendations.

Dark Mode

You can now apply a dark theme to the dashboard. Dark Mode has always had a dedicated group of users who overwhelmingly prefer it to light mode. We’re glad to finally make it available.

Export Process List to CSV

You can now export the process list directly to CSV, making it easier to analyze queries, share snapshots, and include data in reports and incident reviews (Issue #437).

Improved Apply Workflow

To reduce confusion during configuration changes, the Apply button has been moved directly into the Recommended Configuration popup. This keeps review and action in one place.

Updates to Releem Platform

Several fixes this month focused on recommendation accuracy and schema analysis:

Smarter Buffer Pool Recommendations

Releem now takes overall system memory pressure into account when generating innodb_buffer_pool_size recommendations. When RAM usage is already high, recommended values are scaled down instead of being calculated solely from total available memory. This prevents over-allocation in constrained environments and reduces the risk of memory pressure (Issue #481).

Primary Key Detection Fix

Resolved an issue where tables could be flagged as missing a primary key where the Agent has limited schema permissions. Previously, missing column-level metadata could lead to false “no primary key” warnings. The updated logic now handles these cases correctly (Issue #475).

Updates to Releem Agent

Expanded Initial Configuration Options

We added support for generating an initial MySQL configuration directly from the Releem Agent. With a single command, the agent analyzes server hardware and creates a sensible baseline config for new or default MySQL installations, before workload-based tuning kicks in. You can find full details in the updated documentation.

What’s New At Releem - October 2025

Roman Agabekov — Wed, 12 Nov 2025 14:39:26 +0000

Another month in the books – and it’s been a great one. Highlights include support for GCP Cloud SQL, enhanced servers overview for multi-server management, and a round of Agent improvements focused on stability and lighter performance impact.

Kicking things off, we’re excited to share that the TuningWizard team has officially joined Releem, bringing their expertise in database optimization and performance analytics directly into what we’re building together.

Led by Gabriel Ciciliani, TuningWizard has spent the past four years perfecting SQL Query Optimization, helping users identify costly queries and improve performance with precision. This partnership traces back to an introduction by Peter Zaitsev, founder of Percona, which sparked a collaboration that’s been growing ever since. You can read more about how the teams are merging efforts in our official announcement.

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Updates to Releem Dashboard

We’ve added new controls to simplify multi-server management and speed up configuration workflows across all your databases:

Servers Overview Bar

Provides a quick summary of total servers and pending configurations directly on the Servers page, improving visibility and navigation for teams managing multiple instances.

One-Click Apply Across Servers

You can now apply configuration recommendations to all servers simultaneously. This reduces repetitive work and saves you even more time (Feature request #452).

Status Indicators

Adds clear visual markers for Error and Unapplied configurations, helping you see what needs attention at a glance.

Automatic Restart Option

A new “Restart if needed” checkbox allows Releem to safely handle restarts during configuration updates without your intervention.

Updates to Releem Platform

We’ve expanded Releem’s platform with smarter indexing and broader cloud coverage. This update helps optimize complex queries and brings full support for Google Cloud SQL alongside AWS RDS:

GCP Cloud SQL Support

Adds full integration for Google Cloud’s managed MySQL and PostgreSQL databases, joining existing AWS RDS and Azure Database compatibility (Feature request #259). Enterprise customers can now enjoy complete cloud provider coverage with Releem.

GROUP BY / ORDER BY Index Detection

Now identifies missing indexes in queries that aggregate or sort large result sets, cutting down on processing time for reporting and analytics (Issue #441).

Looks at real query history to pinpoint where indexes will make the biggest difference and suggest practical fixes.
In testing, these improvements have delivered 30-50% faster query performance for affected queries.

Index Identification Accuracy

Fixed an issue where optimization recommendations remained marked as “Discovered” even after indexes were created. The platform now correctly tracks index changes across multiple databases and updates the status to “Evaluating” once the fix is applied (Issue #474).

Updates to Releem Agent

We’ve improved Releem Agent to make it more accurate, responsive, and efficient. It now handles version changes and server reporting more smoothly while using fewer resources overall.

Database Upgrade Detection

The Agent now recognizes the exact MySQL / MariaDB / Percona version when the database is upgraded and updates recommendations to match. This prevents outdated or irrelevant suggestions when variables are added, changed, or deprecated in newer releases (Issue #408).

Server Visibility Fix

Now registers servers in the Releem Dashboard immediately after startup. Previously, some servers remained invisible for hours if the Agent existed during early metric collection (Issue #411).

Optimized Data Collection

Streamlined how query examples and process data are gathered. This has lowered Agent resource consumption by 25% and sped up metric collection. Monitoring now runs with less impact on production workloads.

What's New At Releem - September 2025

Roman Agabekov — Tue, 28 Oct 2025 09:49:24 +0000

September was a month of momentum. We focused on problems that frustrate every DBA: deadlocks, incomplete visibility, and cloud deployment quirks. We’ve shipped real-time deadlock monitoring, expanded the weekly reports, and fixed key issues with Releem Agent for RDS.

Beyond the product, our company flag reached Kazbek Mountain (5,047m and one of the highest peaks in the Caucasus). It’s a small but symbolic reminder of how far we’ve come as a team and community.

And while one part of the team was climbing mountains, our co-founders Dmytrii Kochetov and Victor Podkopaev represented at Percona University Yerevan 2025. They shared insights into how LLMs can help with database performance tuning.

Community Contributions

We're always collecting issues and feature requests on our GitHub. Here's where you can contribute:

Issues – If you encounter any problems or bugs, report them here.
Feature Requests – Have an idea to make Releem even better? Share your suggestions here.

Updates to Releem Dashboard

Deadlock Monitoring

After many requests, real-time MySQL and MariaDB deadlock detection has landed (Issue #293). No more hunting through logs. You’ll now see:

Instant alerts when a deadlock occurs
A detailed breakdown of conflicting transactions
Actionable recommendations to prevent recurrence

Read our full deep-dive on deadlock detection to learn more.

New Weekly Reports

Weekly reports now give a richer snapshot of your server health including:

Expanded Health Checks – System, MyISAM/InnoDB, Memory, Queries/Logs
A new Security Check summary with severity levels
Cleaner formatting for quick scanning

Updates to Releem Agent

Resolved AWS Security Hub Alerts

Releem Agent was previously being flagged by AWS Security Hub. The new update corrects those triggers (Issue #415).

Improved EC2 Deployment Documentation

We’ve added guidance for monitoring multiple RDS instances from one EC2 instance. This reduces setup overhead and cuts Fargate resource costs. Read the documentation here.

Stabilized Setup Process

Fixed an issue that caused the Agent to restart MySQL/MariaDB unnecessarily during initial installation. It was annoying everyone and we’re glad it’s no longer a problem (Issue #413)

News You Might Have Missed

Laravel News recently covered a Releem study on how MySQL’s default settings can drag down performance for Laravel apps. It’s a great read if you want to learn more about what’s hiding behind “out-of-the-box” configurations. The Hidden Cost of MySQL Defaults in Laravel Apps.

MySQL Deadlock Detection: How to Find and Fix Transaction Conflicts

Roman Agabekov — Mon, 13 Oct 2025 15:34:17 +0000

Understand, detect, and resolve deadlocks in your database with Releem’s automated monitoring and alerting.

What is a deadlock?

A deadlock is a situation where two or more transactions are each waiting for the other to release a lock. Because neither transaction can proceed, they become stuck. MySQL has a built-in mechanism to detect deadlocks when the innodb_deadlock_detect setting is enabled, which is the default in most setups. When MySQL detects a deadlock, it automatically rolls back one of the transactions to break the loop.

Deadlocks are not always a sign of a bug. They can occur in any system with high concurrency or complex workflows involving multiple statements. However, when deadlocks happen repeatedly or appear in the same workflow, they often signal a deeper issue in how transactions are structured, how indexes are applied, or how application logic interacts with the database.

How to monitor deadlocks manually

If you want to manually check for a deadlock on your MySQL server, run the following command:

SHOW ENGINE INNODB STATUS\G

Look for the section labeled LATEST DETECTED DEADLOCK. Examine the output for:

------------------------
LATEST DETECTED DEADLOCK
------------------------
2025-09-19 21:42:10 0x7f2cd67fa700
*** (1) TRANSACTION:
TRANSACTION 24692, ACTIVE 3 sec starting index read
mysql tables in use 2, locked 2
LOCK WAIT 5 lock struct(s), heap size 1128, 3 row lock(s)
MySQL thread id 127, OS thread handle 139832472479488, query id 44118 localhost appuser updating
UPDATE order_items 
  SET qty = qty + 1 
  WHERE order_id = 500 AND id = 1001
*** (1) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 121 page no 145 n bits 72 index `PRIMARY` of table `shop`.`orders` trx id 24692 
lock_mode X locks rec but not gap waiting
Record lock, heap no 7 PHYSICAL RECORD: n_fields 6; compact format; info bits 0
 0: len 4; id=500
 1: ... (hidden/internal fields omitted)

*** (2) TRANSACTION:
TRANSACTION 24691, ACTIVE 4 sec updating or deleting
4 lock struct(s), heap size 1136, 4 row lock(s)
MySQL thread id 123, OS thread handle 139832488126208, query id 44116 localhost appuser updating
UPDATE orders 
  SET status = 'processed' 
  WHERE id = 500
*** (2) HOLDS THE LOCK(S):
RECORD LOCKS space id 121 page no 145 n bits 72 index `PRIMARY` of table `shop`.`orders` trx id 24691 
lock_mode X locks rec but not gap
Record lock, heap no 7 PHYSICAL RECORD: n_fields 6; compact format; info bits 0
 0: len 4; id=500
 1: ... (hidden/internal fields omitted)
*** (2) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 122 page no 88 n bits 80 index `fk_order_items_order_id` of table `shop`.`order_items` trx id 24691 
lock_mode X locks rec but not gap waiting
Record lock, heap no 12 PHYSICAL RECORD: n_fields 6; compact format; info bits 0
 0: len 4; order_id=500
 1: ... (hidden/internal fields omitted)

*** WE ROLL BACK TRANSACTION (1)

Transaction IDs and SQL queries
Lock types and what each transaction was waiting for
Table names and indexes involved

This manual approach works, but it’s reactive, time-consuming, and only shows the latest deadlock. You also won’t get historical data unless you’re already logging it elsewhere.

Deadlock types and how to fix them

Deadlocks can be grouped by the type of operation or lock pattern that caused them. Different deadlocks require different fixes. Recognizing the type helps you identify the underlying cause and choose the right fix. Here are the most common categories:

1. Update-Update deadlock

Occurs when two transactions update the same rows but in a different order. For example:

Transaction A updates orders, then order_items.
Transaction B updates order_items, then orders. Since both are waiting on each other’s locks, the transactions are stuck.

How to fix:

Access and update rows in the same order in every transaction.
Standardize your transaction logic across your application.

2. Select-for-Update deadlock

This happens when one transaction uses SELECT ... FOR UPDATE to lock rows that another transaction is trying to update or delete. This often occurs in job queues or task schedulers that select rows for processing while other workers modify or remove the same data.

How to fix:

Only use FOR UPDATE when necessary.
Consider LOCK IN SHARE MODE if full write-locks aren’t needed.
Separate row selection and modification into different steps when possible.

3. Insert Auto Increment deadlock

InnoDB places a special lock (called the auto-inc lock) on the end of the index when inserting into a table with an AUTO_INCREMENT column. If multiple transactions insert rows and then touch related tables, they can block each other in unpredictable ways.

How to fix:

Move insert operations to the end of your transaction.
Use bulk inserts to reduce contention.
Avoid mixing inserts with updates on related tables in the same transaction.

4. Gap lock deadlock

InnoDB uses gap locks to lock ranges of index values for SELECT ... FOR UPDATE, DELETE, or UPDATE queries that use inequality or range filters. These range locks can block other inserts or updates that try to work within the same range. This is common with pagination, uniqueness checks, or complex filters.

How to fix:

Use equality comparisons instead of ranges if possible.
Reduce the locked range by adding filters or more specific indexes.
Consider READ COMMITTED isolation level to reduce the range lock scope.

5. Insert Intention deadlock

An insert intention lock is a type of gap lock set by INSERT operations prior to row insertion. This lock signals the intent to insert in such a way that multiple transactions inserting into the same index gap need not wait for each other if they are not inserting at the same position within the gap.

How to fix:

Use INSERT IGNORE, REPLACE, or INSERT ... ON DUPLICATE KEY UPDATE if the inserted row may already exist.
Use SELECT ... FOR UPDATE beforehand to lock the row and avoid conflicts.
Reduce the locked range by adding filters or more specific indexes.
Consider READ COMMITTED isolation level to reduce the range lock scope.

6. Insert same PK deadlock

Plain INSERT is not idempotent when multiple workers try to write the same key at once . Two writers collide on the same PRIMARY key and deadlock.

How to fix:

Change the statement to one of these patterns so the second writer doesn’t need to “win” a brand-new insert: INSERT IGNORE, REPLACE, or INSERT ... ON DUPLICATE KEY UPDATE if the inserted row may already exist.
Reduce the locked range by adding filters or more specific indexes.
Consider READ COMMITTED isolation level to reduce the range lock scope.

7. Foreign key deadlock

This affects operations where one transaction deletes or updates a parent row, and another interacts with the child table. If referential integrity checks are triggered mid-transaction, InnoDB may require shared or exclusive locks on multiple tables, resulting in a deadlock.

How to fix:

Always delete or update related rows in a consistent parent-first or child-first order.
Use ON DELETE CASCADE or ON UPDATE CASCADE appropriately.
Minimize transactional overlap on dependent tables.

8. Long transaction deadlock

A transaction that touches many rows or tables and holds locks for a long time can easily deadlock with smaller, faster transactions. This isn’t necessarily a logic bug, but sometimes it simply happens due to bad timing under high load.

How to fix:

Break large transactions into smaller chunks.
Commit frequently when possible.
Avoid idle sessions within a transaction.

9. Lock escalation deadlock

Though relatively rare in MySQL, some workloads cause escalation-like behavior when multiple row-level locks start conflicting across transactions in unexpected patterns. These usually surface in high-concurrency systems with heavy writes and insufficient indexing.

How to fix:

Add indexes to reduce full scans and write lock contention.
Analyze patterns in locking and restructure queries to reduce overlap.
Consider queuing or scheduling batch operations to run sequentially.

How Releem helps with deadlock monitoring

Releem's Deadlock Monitoring Service continuously checks for deadlocks by analyzing MySQL's internal reports. It captures complete information about every detected deadlock and makes that information accessible and actionable.

Here’s what Releem’s deadlock monitoring does:

Automatically detects all deadlocks in real time using SHOW ENGINE INNODB STATUS
Captures all relevant information, including SQL statements, table names, lock types, and indexes
Sends notifications through your preferred channels
Stores the full history of deadlocks, accessible through the Releem web interface.
Provides practical guidance to help you understand the lock type and fix the root cause

What you’ll see in a deadlock alert

When Releem detects a deadlock, it sends an alert that includes everything you need to start investigating. This includes:

The exact time the deadlock occurred
The full SQL statement for the transaction that was rolled back
The SQL statement that blocked it
The table names involved
The type of locks that were in conflict

For example:

How to respond to a Releem deadlock notification

Step 1: Review the alert

Start by examining the SQL statements in the alert. Look at the tables involved and the type of lock that caused the block. This gives you an immediate view of what was happening in the database at the time of the deadlock.

Step 2: Find the code

Use the query text and table names to trace the transaction back to the relevant part of your codebase. If the query comes from an ORM, enable SQL logging to get the original code. Most ORMs provide a way to log generated SQL, such as enabling echo=True in SQLAlchemy or enabling query logs in Laravel.

Step 3: Apply Fix

Once you’ve identified the query and type of deadlock, apply the corresponding fix based on the lock pattern involved.

How to prevent deadlocks in the future

Deadlocks aren’t always avoidable, especially in high-concurrency environments. But you can reduce how often they occur and how disruptive they are by structuring your transactions and queries more deliberately:

Access tables and rows in a consistent order: Inconsistent ordering is one of the most common causes of deadlocks. Always access tables and rows in the same order across all parts of your application.
Use proper indexes on frequently updated or filtered columns: When queries scan too many rows due to missing indexes, they hold locks longer than necessary. This increases the likelihood of conflicting transactions. Add indexes to support any columns used in joins, updates, deletes, and SELECT ... FOR UPDATE queries.
Keep transactions short and commit as early as possible: Long-running transactions hold locks open and increase contention. Avoid starting a transaction and then performing multiple slow operations or leaving the session idle. If changes are unrelated, split them into separate transactions.
Avoid combining SELECT FOR UPDATE and INSERT statements in the same transaction when possible: Locking existing rows and writing new ones can create complex lock dependencies, especially in tables with AUTO_INCREMENT values or triggers.
Consider adjusting your isolation level: The default isolation level in MySQL, REPEATABLE READ, holds more locks than READ COMMITTED. If you don’t need consistent snapshots for the duration of a transaction, switching to READ COMMITTED can help reduce lock contention.
As a last resort, serialize critical sections with explicit table locking: If nothing else helps, you can use LOCK TABLES to manually control access to entire tables. This approach guarantees exclusive access, but it comes with tradeoffs. You must start with SET autocommit = 0, lock the tables, perform the operations, then commit and release the locks. It should only be used in tightly scoped, low-volume parts of the application where deadlocks are unavoidable through normal means.

Releem makes deadlocks easier to deal with

Deadlocks are a natural part of working with transactional databases, but that doesn’t mean you have to treat them as a black box. With Releem’s Deadlock Detection, you get automated early warnings, full context, and clear next steps. It reduces the time you spend diagnosing blocking issues and gives you visibility into the health of your transaction patterns.

If you're ready to stop chasing deadlocks after the fact, turn on Deadlock Detection in your Releem dashboard. It takes care of the tracking so you can focus on fixing the real issues.

ChatGPT Alternative for SQL Query Optimization

Roman Agabekov — Mon, 13 Oct 2025 10:53:47 +0000

Working with SQL query optimizers powered by LLMs has its ups and downs. I’ve noticed that even with tools like ChatGPT or Claude, the process can feel awkward:

Write a prompt → Paste the query → Wait → Refine prompt → Repeat

This cycle is fine once or twice, but quickly becomes tedious — especially for long or complex queries.

So I built a tool that removes prompt engineering from the equation and focuses purely on helping you analyze and optimize SQL queries.

How It Works

1. Paste your SQL query
2. Select your database (PostgreSQL, MySQL, SQL Server, etc.)
3. Click “Analyze”

The screenshot:

You’ll Get

- ✅ A list of suggestions with brief reasoning
- 🔄 A rewritten (optimized) version of your query
- 🎯 A confidence tag for each recommendation (High / Medium / Low)

The screenshot:

Want deeper insights?

You can optionally add:

EXPLAIN plans
Schema
Indexes
Table stats

The tool will use this additional context to refine its suggestions and increase recommendation confidence.

The screenshot of this step:

Deeper Technical Rationale

The tool supports two levels of analysis:

1. Standard Analysis (available to all users)

When you paste a SQL query and click “Analyze”, the system runs a one-step evaluation:

Parses the query syntax and structure.
Identifies common inefficiencies.
Generates a list of suggestions based on known performance patterns and best practices.
Provides an optimized version of the query.
Assigns confidence tags based on available context.

This mode is fast and lightweight, ideal for quick feedback.

2. Deep Analysis (available to registered users)

Deep Analysis follows a multi-stage reasoning process using an internal AI agent:

Hypothesis Generation
The model builds multiple performance-related hypotheses based on the SQL query and any provided context — including schema, EXPLAIN plans, table/index stats, constraints, etc.
Validation and Filtering
It then self-evaluates each recommendation. Weak or irrelevant suggestions are filtered out. This step prevents common LLM hallucinations or overly generic advice.
Optimized Query Generation
A refined, rewritten query is generated — informed by the validated insights and context.

This approach improves both precision and reliability of recommendations, especially for complex queries involving joins, CTEs, subqueries, or large tables.

Who is this for?

This tool isn’t trying to replace profilers or DB-specific advisors. It’s designed for:

Developers who want quick feedback on queries
Teams who want to share and discuss queries
People learning SQL who want to understand improvements

Give It a Shot

You can try the tool here: https://sqli.to

I’d love to hear your thoughts❤️

DEV Community: Roman Agabekov

Laravel Deadlocks: Causes and Fixes

Table of contents

What is a deadlock?

Common deadlock patterns in MySQL

What do developers see in Laravel?

6 Reasons why deadlocks happen in Laravel apps

1. Jobs or requests update the same rows

2. Long transactions with multiple queries

3. Hidden locking from Eloquent

4. High concurrency on a busy queue or Horizon setup

5. Schema shape that increases lock ranges

6. Model events, mutators, and touches() adding hidden queries

Why deadlocks feel random in production

How to debug deadlocks in production

1. Pull the deadlock details from MySQL

2. Read the lock information

3. Check the order of operations

4. Try to reproduce locally

How to reduce and prevent deadlocks in Laravel

1. Keep transactions short

2. Update rows in a consistent order

3. Use row-level locks where needed

4. Add the right indexes

5. Avoid unnecessary reads inside writes

6. Implement retry logic for deadlock-prone operations

Tools that help monitor and understand deadlocks

Where this leaves you

Safe automation for MySQL index recommendations | What’s New At Releem

Community Contributions

Product Updates

Safe automation for index recommendations

Added multi-step Installation Wizard

Expanded PostgreSQL configuration recommendations

Show just the recommended configuration changes

Reports for invited users on shared servers

Removed an irrelevant security check for cloud-managed MySQL and MariaDB

Fixed deadlock analysis for names with special characters

Fixed an error when adding servers simultaneously

Releem Now Supports PostgreSQL, Azure MySQL, and Better Windows Automation

Community Contributions

Product Updates

What's New At Releem - WHM/cPanel integration is available

Community Contributions

Product Updates

Batch SQL query analysis and recommendations

Custom SQL query optimization

WHM/cPanel integration

API and WHMCS integration for hosting partners

AWS Aurora Serverless support

Deadlock export to CSV

Improved data collection performance

Uninstallation dependency fix

Duplicate index detection improvement

Expanded query parser support

Offline agent apply-task fix

What’s New At Releem - January 2026

Community Contributions

Updates to Releem Dashboard

Updates to Releem Platform

Updates to Releem Agent

Events

When “MySQL” isn’t actually MySQL

Releem 2025 Recap: Building a Database Advisor for Developer Teams

What we shipped

Thank you

What's New At Releem - November 2025

Community Contributions

Updates to Releem Dashboard

Updates to Releem Platform

Updates to Releem Agent

What’s New At Releem - October 2025

Community Contributions

Updates to Releem Dashboard

Servers Overview Bar

One-Click Apply Across Servers

Status Indicators

Automatic Restart Option

Updates to Releem Platform

GCP Cloud SQL Support