Build. Ship. Operate.

Your DevOps buddy is here.

Builds, runs, fixes, deploys and operates your software, on your machine and on your servers. It reads the real state of your systems instead of guessing, and never touches production without your say-so.

Create an account See how it works

Nothing runs without your approval
It cannot reach your credential files or compose its own commands
Uses the scripts and SSH access you already have

Production is down

site's throwing 502, it was fine yesterday

read the nginx error logchecked the vhostcause found

nginx itself is healthy. Its error log repeats connection refused to :8019, but your app is listening on :9014. The port changed in the last deploy and the vhost still points at the old one. Want me to correct it?

yes, go ahead

Done. Updated the port in your site config, ran nginx -t to check it, then reloaded. The site is answering again.

Config backed up before the change ✓ 200 OK · site back up

It won't build on my machine

fresh laptop, this project won't compile

read the build filechecked installed runtimesmismatch found

The build targets Java 8; you have 17. That's the whole failure. Shall I install Java 8? It comes from your OS package manager, and you'll see the publisher before anything downloads.

go for it

Java 8 is installed. Your 17 is untouched, both are on the machine now. I re-ran the build and it compiled.

Build re-run to confirm ✓ BUILD SUCCESS in 41s

Going live for the first time

brand new server, get this app live on it

read the projectchecked the serverplan ready

The server is bare, so this is the full path. My plan: build and run it on your machine first, so we know the app itself is fine. Then install Docker and nginx on the server, ship it over, set up the database, put nginx in front, and issue the certificate. Nine steps, about six minutes, each one shown before it runs. Shall I start?

go ahead

All done. It ran clean locally, so I shipped it. Docker and nginx are installed, your app is running behind nginx, and the certificate is issued and set to auto-renew.

Nine steps, each one shown before it ran ✓ Live at app.example.com

The server is out of space

app keeps failing to write files

checked disk usagefound the biggest offenderscause found

The disk is 94% full. Container logs are using 38 GB. One service has been looping the same error for weeks and nothing was rotating them. Want me to clear them down?

yes, but keep something recent

Cleared, keeping the last day. I also set a size limit so they cannot grow like that again. That looping error is still there if you want me to look at it next.

Rotation limit added ✓ 37 GB freed · writes healthy

See more of what it handles →

Works with the stack you already run

Docker & Compose nginx AWS Jenkins IIS Tomcat MySQL / MariaDB PostgreSQL Redis Linux Windows Server Laravel Spring Boot Node.js .NET

The honest version

The hard part was never writing the code

It's the hour lost to a container that won't start. The deploy that worked on staging. The certificate nobody renewed. The one person who knows how the server is wired.

2 days Environment setup

Environment setup that never ends

A new developer loses two days to a missing runtime and a config nobody wrote down. The project builds fine, but only for the person who set it up.

Fixed It reads the project, spots the runtime you're missing, installs the right version and gets the build green.

4 servers Incident response

Incident response by hand

Production is down and you're SSH-ing between four servers, grepping logs one at a time, trying to remember which container talks to which database.

Fixed It checks every server at once, reads the logs, and tells you the actual cause instead of a list of maybes.

1 person The bottleneck

The DevOps bottleneck

Every deploy waits on the one person who knows the runbook: an engineer on a team, or just you if you're working solo. They can't take a holiday, and if that person is you, there's no one to hand it to at all.

Fixed. Nobody has to be the runbook any more. Ask for what you need, whether that's a stuck build, a release going out or a server acting up, and it runs the infrastructure side on your word while you stay on the product.

How it works

From dev to prod, one teammate

Most tools cover one slice of this. The gaps between them are where the hours go.

Build

Reads the project, works out how it's meant to be built, installs whatever it's missing, and gets it compiling on your machine.

Run

Starts the app, stays with it while it runs, and tells you plainly if it fell over and what it said on the way down.

Fix

Reads the actual error and the actual config instead of guessing, proposes the change, and shows you the diff before anything is written.

Deploy

Puts your project on the server. If the server is new it sets it up first, and if you have a deploy script it uses that. You see the plan first, and what shipped after.

Operate

When something is off, you ask. It checks the containers, proxy, database, service or certificate, finds the cause, and fixes it once you approve.

It answers from your systems, not from memory

Ask a general AI why your container is restarting and it will invent five plausible reasons. This one runs the read-only checks itself and answers from what came back.

AI that manages your computer

Builds, runs and fixes your project on the machine in front of you, runtime installs included. Windows today.

AI that manages your servers

Over the SSH you already have: Docker and Compose, nginx, IIS, Tomcat, MySQL, PostgreSQL, Redis, services and certificates.

AI that does not invent your infrastructure

Every answer traces back to a check it ran, quoting the log line or config value it rests on.

Reads are instant. Anything that changes something stops and tells you what it is about to change, showing it as a command or a red/green diff, then waits for you.

Walk through the flow

brynko devOps Agent

Container restart loop

the checkout container keeps restarting

read container state checked health check listed ports

It restarts every 40 seconds, and it is the health check failing, not the app. The check calls /healthz on port 8080, but the app is listening on 3000, so it never passes and Docker keeps killing it.

fix it

one line in compose restarted watched 5 minutes

Done. I corrected the health check port and restarted the service. It has stayed up since, and the check is passing.

Fixed · container healthy

Database timing out

the orders page has been timing out since this morning

read database status connection counts slow queries

Postgres is at 98 of its 100 connection limit and refusing new ones. It is not query load, the queries are fast. Your app opens a pool per worker, and the workers went from 4 to 12 this morning, so it is asking for far more connections than the database allows.

can you sort that out

pool size to 4 restarted workers rechecked connections

Done. I set the pool size to 4 per worker and restarted them, so 12 workers now ask for 48 rather than 96. Connections are sitting at 41 and the orders page is responding normally again.

Fixed · 41 of 100 connections

The app keeps dying

the reports service dies every afternoon

read exit codes checked memory limit usage history

It is being killed, not crashing. Exit code 137 means it hit its memory limit, which is set to 512 MB. It climbs past that during the afternoon export job.

give it more room

512 MB to 1 GB restarted re-ran the export

Raised the limit from 512 MB to 1 GB and restarted it. I ran the export job again to be sure: it peaked at 680 MB and finished clean.

Stable · export completed

What it can do

Deep where it counts

Not a thin wrapper over a shell. Each area has real tooling behind it, with its own guardrails.

Docker, without memorising the flags

Inspect containers, read logs, check stats, restart services and run Compose stacks, just by describing what you want.

Your reverse proxy, explained and fixed

Test configs before they go live, read the right log, and reload safely, on nginx, IIS or Tomcat.

Ship it, and know what shipped

Run your existing deploy scripts, watch the output live, and get a straight answer about whether it worked.

Ask your database what is wrong

Read-only checks and queries over your existing SSH connection, with credentials encrypted at rest.

Wildcard HTTPS, sorted in one step

Issue trusted, auto-renewing certificates, wildcards included, and get the paths handed straight back.

Your AWS account, in plain English

Read EC2, S3, Elastic IPs and EBS, spot what is quietly costing you money, and make changes only after you approve them.

Ask Jenkins what went wrong

Read jobs, builds, the queue and console logs, find out why a build failed, and trigger or stop builds with your approval.

It runs on your machine too

Build, run and fix projects on your own computer, including installing the runtime the project needs.

A real file editor for your Linux servers, no nano required

Browse your Linux servers as a file tree and edit files in a real editor with syntax highlighting, find and replace and search across the whole box. Over the SSH access you already have, with nothing installed on the server.

How it connects

It reaches your servers the way you do

Over the SSH access your team already has. Nothing is installed on the server, and there is no new door to leave open.

The keys stay with you

The agent runs on your computer and connects over the SSH access you already have, as a user you control and can revoke. Nothing is installed on the server.

Reads go straight through

Logs, config files, container state, ports, service status. Reading cannot break anything, so it never stops to ask and answers come back in seconds.

Changes stop at the gate

Every write, restart, install or delete waits for a person. You see what it is about to change before it happens, and the change is reversible afterwards.

Built for production

Handing an AI your servers should feel safe

We started from the assumption that it will occasionally be wrong, and made that survivable. Scoped access, approval gates and reversible changes.

Read the security model

Approve before anything changes

Reads run freely. Every write, restart or delete tells you what it is about to change, shows it, and waits.

Reversible by default

File edits are snapshotted before they are written. Deleted folders are archived first. One click to undo.

Credentials are out of reach

Private key material is never sent to the model, and directories like .ssh and .aws are refused wherever they sit on disk.

Everything is audited

Every action, who approved it and what came back is written to a log you can read.

Questions

Straight answers

What does it actually do?

It works the whole path from your laptop to production: gets a project building and running locally, fixes what is broken, runs your deploy scripts, then keeps the result healthy across Docker, nginx or IIS, databases, services and certificates. You describe the outcome; it does the legwork and shows you every command first.

How is this different from asking ChatGPT?

A chatbot guesses from memory. This connects to your actual machines, runs read-only checks, and answers from what your systems report right now. When it suggests a fix, it has already read the log and the config, and it can apply that fix for you once you approve it.

Will it break production?

Nothing destructive happens without you clicking approve. Reads are free and fast; every write, restart or delete shows you what it is about to change first. It also cannot compose its own commands, only fill parameters into shapes we defined, and credential directories such as .ssh and .aws are refused wherever they are on disk. File changes are backed up and reversible, and everything is written to an audit log.

Do I need to change how we deploy?

No. It runs the deploy scripts you already have. There is no new pipeline to adopt, no YAML to rewrite, and no agent to install on every server. It connects over the SSH you already use.

Does it work with Windows servers?

Yes. Windows and Linux both, with IIS and Tomcat alongside nginx. It detects the OS on connect and uses the right commands for that machine.

Do I have to be a DevOps engineer to use it?

No. That is largely the point. Developers use it to get unstuck without waiting on ops; ops teams use it to stop answering the same questions. It explains what it found in plain language, not just raw output.

Get started

Give your team back the afternoon

Set it up against one server and try it on something that is already annoying you. You will know inside an hour whether it earns its place.

Create an account See pricing