DEV Community: Ivole32

Recap Sunday #1: Marketing Progress and Backend Design Updates

Ivole32 — Sun, 24 May 2026 22:08:09 +0000

Welcome to the first edition of Recap Sunday, our new weekly series where we look back at the progress, decisions, and milestones from the previous week at QueueForge.

QueueForge has been in development for quite some time, but this marks the beginning of a new way for us to share our journey and keep you updated on what happens behind the scenes.

This week, our primary focus was on marketing and finding effective ways to introduce QueueForge to a wider audience.

To support this goal, we started implementing a structured content strategy across our social media channels and this blog.

As part of this initiative, you may have already noticed new content series such as Future Friday. Several additional formats are currently in development and will be introduced over the coming weeks.

The initial results have been encouraging. We have already seen positive changes in our analytics, reinforcing our decision to consistently share updates, insights, and behind-the-scenes content about QueueForge.

Although marketing was our primary focus this week, development continued as well. We implemented additional functionality for the core queue management system and finalized several important architectural decisions that will help us build a scalable and maintainable platform moving forward.

One of the biggest topics this week was refining how different components of the backend should communicate with each other. While much of this work is not directly visible to users, these decisions are critical for ensuring reliability, performance, and future scalability.

Highlights of the Week

Created and started executing a structured content marketing plan.
Launched the new Future Friday content series.
Observed positive engagement and growth across our channels.
Implemented additional backend functionality for queue management.
Finalized key architectural decisions for future scalability.

Looking Ahead

Next week, we plan to continue expanding our content efforts, introduce additional recurring content formats, and further develop the core QueueForge platform.

We are excited about the progress we are making and look forward to sharing more updates with you in the next edition of Recap Sunday.

See you next week,

The QueueForge Team

Stats Saturday #1: How Endless Scrolling Steals Our Time

Ivole32 — Sat, 23 May 2026 18:30:00 +0000

Welcome to the first edition of Stats Saturday. Every week we will share a few numbers from our work, the habits that helped us move forward and the things that slowed us down.

The goal is simple. By making our progress public, we want to stay accountable and continuously improve. Some weeks will look better than others, but we believe that tracking the right metrics is one of the easiest ways to identify what works and what needs attention.

How TikTok reduces our productivity

We have to admit something: we spend too much time on TikTok.

This week alone, our total screen time on TikTok reached 21 hours. That is almost an entire day spent scrolling through short videos. While entertainment and breaks are important, this amount of time clearly comes at the expense of other activities.

Those 21 hours could have been used for writing content, improving QueueForge, learning new skills or simply taking proper breaks away from a screen. Instead, much of that time disappeared into endless scrolling.

To reduce this number, we are setting a goal for next week: spend at least 14 fewer hours on TikTok. Public accountability can be a strong motivator, so we will publish our scrolling time every week in Stats Saturday and track whether we are making progress.

The objective is not to completely stop using social media. We simply want to be more intentional with our time and avoid opening an app out of habit.

Website statistics

Using our analytics platform GhostlyX, we were able to review how our recent content strategy performed.

One encouraging result is that posting consistently appears to be working. During the last seven days, the website received 13 unique visitors, representing growth of 116.7 percent compared to the previous period.

If you are reading this article on our official blog, you are part of those statistics.

Another positive metric is the bounce rate, which decreased by 22.8 percent. In practical terms, visitors are exploring more pages instead of leaving immediately after opening the first one.

However, not every number moved in the right direction. The average visit duration dropped by 55.1 percent and now stands at only 22 seconds. This suggests that while more people are discovering the site, the content is not yet keeping their attention for as long as we would like.

Over the coming weeks we will experiment with longer articles, clearer calls to action and more useful content to increase engagement and encourage visitors to spend more time on the website.

Other stats

Besides traffic and productivity metrics, here are a few additional numbers from this week:

Lines of code committed: ~500
Money spent: €0
Purchases we almost made: €9

Looking ahead

Our focus for next week is straightforward:

Reduce TikTok usage by at least 14 hours
Continue publishing content consistently
Increase average visit duration
Maintain growth in website traffic

We will share the results in the next edition of Stats Saturday. If you would like to follow our progress, consider subscribing to the newsletter and checking back next week.

Future Friday #1: Planning the First QueueForge Release

Ivole32 — Fri, 22 May 2026 18:30:00 +0000

Welcome back to another edition of Future Friday, our blog series where we share what we are currently working on, what is happening behind the scenes, and what comes next for QueueForge.

In our previous blog post, we introduced the QueueForge MVP and provided an overview of the first features currently being developed. Since then, our focus has remained on continuing development and turning the planned functionality into a stable and usable product.

Over the next weeks, we will continue working on the MVP, improving existing components, refining the user experience, and preparing the platform for its first users.

While development remains our primary focus, we have also started discussing another important topic internally: how the first version of QueueForge should be released.

Planning the rollout

Launching a new platform is not only about building features. It is also about finding the right way to introduce the product to users and gather meaningful feedback.

For that reason, we are currently evaluating different release approaches for QueueForge.

Private Beta with a limited number of testers
Public Beta available to all interested users
Full public launch after an initial testing phase
A staged rollout combining multiple release phases

Each option offers different advantages. A smaller beta can provide focused feedback and allow us to react quickly to issues, while a broader public release can help us validate the platform under real-world conditions.

At the moment, no final decision has been made. We are reviewing the available options and discussing which approach best supports both product quality and user experience.

Decision coming soon

One of our goals for the coming weeks is to finalize our release strategy and establish a clear roadmap for the first public version of QueueForge.

Once a decision has been reached, we will publish the details and explain exactly how users will be able to access the platform, participate in testing phases, and follow the journey toward the first official launch.

We believe that careful planning now will help create a smoother experience later and allow us to gather valuable feedback as QueueForge continues to evolve.

What's next

For now, development of the MVP continues. We are excited about the progress being made and look forward to sharing more details as both the product and release plans take shape.

Future Friday will continue to provide regular updates on development progress, technical decisions, and important milestones as we move closer to the first release.

Inside the QueueForge MVP | Queue Monitoring Platform

Ivole32 — Tue, 19 May 2026 15:21:10 +0000

Inside the QueueForge MVP

People following QueueForge may have asked themselves what the first QueueForge MVP will look like and what problems the platform is being built to solve.

Today we want to share the current direction of the project, the first planned features, and what the MVP is expected to focus on during the first release.

QueueForge is a platform for hosting and debugging message queue systems. The goal is to make queue systems easier to observe and understand during development and production.

Working with asynchronous systems can quickly become difficult once applications start communicating across multiple services. Messages can fail silently, queues can become overloaded, and debugging issues often requires checking logs across several systems.

The QueueForge MVP is being built to simplify this process by providing a single interface for monitoring queue activity and viewing important queue information in real time.

The first version

The first version of QueueForge will focus on monitoring, visibility, and debugging.

Queue statistics in a single dashboard
Basic monitoring for message throughput
Consumer and producer activity tracking
Simple dead letter queue visibility
Alerting for queue related events
Connection through a custom QueueForge SDK

The dashboard is being designed to stay simple and easy to understand. Instead of exposing large amounts of infrastructure data, the focus is on showing the information developers actually need while debugging queue systems.

This includes queue activity, message counts, consumer status, throughput statistics, and dead letter queue information.

QueueForge SDK

Communication between production applications and QueueForge will be handled through a custom SDK.

The SDK will allow applications to send queue metrics and debugging information directly to the QueueForge backend.

The current goal is to keep the SDK lightweight and simple to integrate into existing applications without requiring major infrastructure changes.

The SDK will also act as the main connection layer between applications and the QueueForge dashboard.

Current focus

Although features, interfaces, and technical decisions may still change during development, the current focus is building the dashboard, defining the SDK API, improving the internal architecture, and creating the foundation for future monitoring and debugging features.

Another important goal of the MVP is keeping the platform simple to use. Many existing tools expose infrastructure metrics but make debugging queue related problems unnecessarily difficult.

QueueForge is being built with a focus on developer experience and usability from the beginning.

What's next

A deeper look into the QueueForge SDK and the technical architecture behind the platform will be shared in future posts.

If you want to follow development updates and future technical deep dives, consider subscribing to the QueueForge newsletter.

Outages QueueForge Could Have Prevented #1 | Transactional Queue Failu

Ivole32 — Thu, 07 May 2026 12:07:05 +0000

Outages QueueForge Could Have Prevented #1 — The Transactional Queue Failure That Silently Lost 21,500 User Actions

In January 2026, Sean Hammond published a detailed writeup about a queue-related outage that caused thousands of user actions to silently disappear.

The engineering team behind Hypothesis had a system architecture that looked completely reasonable on paper:

Save data to Postgres
Push a background job to RabbitMQ
Index the data asynchronously into Elasticsearch

The system worked for years.

Until RabbitMQ failed.

Suddenly, users started creating annotations that appeared to save successfully but later vanished from the application.

Not because Postgres lost data.

Because the queue failed at exactly the wrong moment.

The Architecture That Failed

Their request flow looked roughly like this:

Client Request
    ↓
Write annotation to Postgres
    ↓
Commit transaction
    ↓
Enqueue indexing job in RabbitMQ
    ↓
Return 200 OK

The critical flaw was subtle.

The database transaction and the queue publish operation were completely separate systems with no shared transactional guarantee.

So when RabbitMQ stopped responding:

Postgres commits still succeeded
Queue publish operations failed
The API still returned success responses
Elasticsearch never received indexing jobs

The result was catastrophic:

More than 21,500 annotations existed in Postgres but never appeared in Elasticsearch.

Since Hypothesis relied on Elasticsearch for reads, users experienced this as missing or deleted data.

This is one of the most dangerous categories of outages: silent inconsistency.

The Distributed Systems Problem Behind It

This outage is effectively a real-world version of the Two Generals Problem.

You cannot perfectly coordinate two distributed systems if communication between them can fail.

In practice, the system ended up in this state:

Database commit succeeded
BUT
Queue publish maybe failed

Once this happens, retries alone are not enough unless the architecture was specifically designed for recovery.

Most queue systems still leave this edge case entirely to application developers.

Most teams only discover the flaw after production traffic triggers the exact failure mode.

Why These Failures Are So Dangerous

This outage was not caused by scaling problems, malformed requests, or traffic spikes.

It was caused by a missing reliability guarantee between persistence and asynchronous execution.

Failures like this often create:

Ghost writes
Missing events
Broken search indexes
Orphaned jobs
Impossible-to-debug race conditions

The most dangerous part is that systems often appear healthy while users are actively losing data.

Some requests work perfectly.

Others silently disappear forever.

The Fix: Transactional Job Queues

Hypothesis eventually redesigned the architecture around a transactional queue stored directly inside Postgres.

Instead of:

DB transaction
THEN
external queue publish

They changed the flow to:

BEGIN;

INSERT annotation;
INSERT job;

COMMIT;

Now the write operation and the queued work existed inside the same atomic transaction.

Either both succeeded.

Or neither existed.

That architectural change eliminated the entire category of consistency bugs.

Why More Teams Are Moving Toward Transactional Queues

Increasingly, engineering teams are rediscovering the same principle:

Reliability comes from transactional guarantees, not retries.

Retries help.

Dead-letter queues help.

Backoff strategies help.

But none of them solve the core issue if queue publishing is not transactionally coupled to the state change that created the work.

This is why more systems are moving toward:

Transactional outboxes
Postgres-backed queues
Durable event logs
Exactly-once delivery systems
Atomic enqueue patterns

The industry is slowly realizing that queues are not just infrastructure.

They are part of the application’s consistency model.

What QueueForge Could Have Prevented

This is exactly the category of outage that modern queue tooling should detect before production users notice.

A platform like QueueForge could surface warning signals such as:

Successful database commits paired with failed enqueue attempts
Queue publish latency spikes
Growing transaction-to-job mismatch rates
Missing downstream consumers
Jobs never reaching processing pipelines
Consistency drift between systems

The dangerous part of the outage was not that RabbitMQ failed.

Infrastructure failures happen constantly.

The dangerous part was that the application kept acknowledging success while silently dropping critical background work.

That is the exact failure mode teams need visibility into.

The Bigger Lesson

Queues are usually marketed as scalability infrastructure.

But the hardest queue problems are rarely about throughput.

They are about correctness.

The moment an architecture says:

"Save data now, process later"

it introduces a distributed consistency problem.

If that boundary is not explicitly designed for, production will eventually find it.

Usually after years of “it has always worked fine.”

Usually at 3 AM.

And usually after thousands of records have already gone missing.

Can AI actually make a SaaS platform safer?

Ivole32 — Fri, 24 Apr 2026 22:45:20 +0000

I wanted to test that before even launching QueueForge.

Most startups treat security as a later problem. I am trying to do the opposite.

Even pre MVP, we already built a layered security system:

AI scans for vulnerabilities before deployments
Automated tools catch dependency risks continuously
Manual reviews and a public security program add a human layer

AI already helped us catch real small issues early, which is exactly the point.

It is not about being perfect. It is about not being blind.

I wrote a deep dive on how we approach security from day one.

https://queueforge.dev/blog/how-we-keep-queueforge-safe

Do you think early stage startups underestimate security?

How we keep QueueForge safe

Ivole32 — Fri, 24 Apr 2026 22:22:41 +0000

QueueForge is a SaaS platform for hosting and debugging queue systems. We have a major responsibility to make our product secure and usable without our users having to worry about it. Even though we haven't launched our first MVP yet, we already feel this responsibility. It is not just the product we have to keep safe; it also includes our marketing website, the newsletter, our infrastructure, and our internal tools.

We want to give our future customers a quick dive into security at QueueForge and explain how we combine AI, human expertise, and automated analysis into a cohesive security concept.

How QueueForge uses AI for security

We use AI to scan our code for vulnerabilities and to identify potential exploit scenarios. We run these AI scans before every major deployment and after significant changes to the codebase. Through this scanning, we found multiple small misconfigurations in our reverse proxy and some in our admin dashboard. It is important to remember that these vulnerabilities could not have caused harm, as their impact was low or they were located in internal tools. This is a positive result: if the system finds small problems, it is capable of finding major ones too. We understand that AI cannot replace real people, but it effectively helps us improve the security of our product and website.

How QueueForge uses automated tools for security

We use automated tools to find vulnerabilities in dependencies and "low-hanging fruit" that can be detected through pattern recognition. We use services we trust, though we prefer not to disclose the specific providers. In addition to these tools, we perform npm audit and pip-audit scans every one to three days.

How QueueForge involves humans and the community

QueueForge does not rely solely on automated tools or AI to secure our services. We also perform manual searches for vulnerabilities, specifically before every major deployment that adds new functionality. We implement a "secure by design" concept, though it is common knowledge that this approach alone is not enough. Another key element is our public security research program, where anyone can participate. You can find it at https://queueforge.dev/security. Although we have not received a report yet, we believe this will help us in the future.

Stay up to date

If you want to stay informed about development progress, upcoming features, and announcements, you can subscribe to the newsletter. This is the easiest way to follow updates and new articles from QueueForge.

The Idea Behind QueueForge

Ivole32 — Wed, 22 Apr 2026 18:14:12 +0000

I recently published a blog post explaining what my new project QueueForge is. Even small steps like this help move the product forward.

Read the full article here: https://queueforge.dev/blog/what-is-queueforge

What is QueueForge

Ivole32 — Tue, 21 Apr 2026 19:52:45 +0000

Introducing QueueForge

You might wonder what QueueForge is. The idea is simple.

QueueForge is a SaaS platform for hosting queue systems. It focuses on a problem many developers face when working with queues: debugging. Issues such as missing messages, lost messages, or delays in worker processing can be difficult to trace. QueueForge is being developed to help make these issues easier to understand and resolve.

How will QueueForge work?

QueueForge is planned to provide an interface that is easy to understand and supports developers with different levels of experience. It will include an SDK for deeper integration, as well as an API and other connection options for working with existing queue systems.

Stay up to date

Introducing the QueueForge Blog and RSS Feed

Ivole32 — Sun, 22 Mar 2026 00:48:46 +0000

We have added a new blog to the QueueForge marketing website. The goal of this blog is to improve how we communicate with our users, customers, and the wider community. Through the blog we will share product updates, technical insights, announcements, and other important information about QueueForge.

Alongside the blog we have also implemented an RSS feed. This allows anyone to easily follow new posts using their preferred RSS reader. Whenever we publish a new article, update, or announcement it will automatically appear in the feed so you can stay informed without needing to manually check the website.

The blog will become our central place for sharing updates about new features, infrastructure improvements, and development progress. We believe this will help us communicate more transparently and keep the community informed about what we are building.

Stay up to date

If you want to stay informed about new features, releases, and important announcements, we encourage you to subscribe to our newsletter. This is the easiest way to make sure you never miss important updates or new articles from QueueForge.

What problems do you face with queue systems?

Ivole32 — Tue, 17 Mar 2026 20:45:31 +0000

I’m currently building QueueForge (https://queueforge.dev) and I’d love to learn from people who work with queue-based systems.

If you use message queues in production, what are the biggest challenges you run into?

Is it debugging failures, understanding retries, observability, scaling consumers, or something else?

I’m especially interested in real-world problems engineers face when operating queues in production.

QueueForge Website Launch

Ivole32 — Tue, 17 Mar 2026 20:43:19 +0000

I have just published the new marketing website for QueueForge. (https://queueforge.dev)

QueueForge is a project I am currently building around observability and tooling for queue based systems. The site now includes an overview of the idea, the planned features, and a newsletter for updates.

I would really appreciate any feedback on the website, including design, clarity, messaging, or anything that could be improved.

If you have a moment, feel free to check it out and share your thoughts or subscribe to the newsletter.