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Sondeon

For the CTO and the head of data

Read-only database audit and database health check Your database runs fine on test data. What about real customers?

We review your databases in read-only mode and tell you what would bring them down the day real customers arrive, with the evidence for each point.

You get the report with the risk indicators and a baseline to compare against. Scope and timeline are in writing before we start.

Patch panel with arched cables bathed in green light, with the left half of the image in black

Updated on

Who it is for

  • You are taking a system designed with AI to production
  • Screens get slower every month and nobody knows why
  • Data is growing and nobody has reviewed indexes or connections

You don't need it if the system is a trial with little data that is not going to grow.

When the database goes down, everything goes down

With test data everything responds instantly. With thousands of customers and years of data you get the queries that take seconds because of a missing index and the connections that run out at peak. It almost always gives warning first, if someone is looking. According to CIO Dive, reporting on an S&P Global Market Intelligence survey (2025), organizations scrapped on average 46% of their AI proofs of concept before they reached production.

46%

AI proofs of concept scrapped before production

S&P Global Market Intelligence, 2025

What the database audit covers

  • Connections: shape, stability and limits
  • Slow queries, with their real parameters
  • Schema, indexes, views and routines against the code
  • Locks, concurrency and configuration against real memory
  • Redis memory and keys
  • Elasticsearch health, indexes and disk
  • RabbitMQ queues and consumers

More than 200 control points

Technologies covered

  • PostgreSQL
  • MySQLControl points not counted yet
  • Redis
  • Elasticsearch
  • RabbitMQ

Trademarks and logos belong to their respective owners. Their use here is descriptive only and implies no commercial relationship or sponsorship.

How it works

  1. Meeting and written scope

    In 30 minutes we look at which engines you use and how much you expect to grow. Then you get in writing what is reviewed, what is left out and the timeline.

  2. Read-only review

    We read the structure, the queries and the configuration of each engine. The review changes nothing in your running system.

  3. Report and results meeting

    You get the risk indicators with their evidence and a baseline, and we go through it with your team. The next review is compared against it.

What we need from you

  • A read-only user on each engine
  • Read access to the code that uses the database
  • One person on your team to answer questions

How we work

What you get

  1. Technical report: the risk indicators and the evidence for each one
  2. Baseline to compare against in the next review
  3. List of findings, each with its priority
  4. One-page executive summary for leadership

How a finding arrives

Priority: Medium

Order search by customer with no index

Where
PostgreSQL, orders table
Evidence
The execution plan scans the whole table on every search
Impact
The orders screen slows down as soon as the data grows

An example of the report format, not a client's.

Shall we talk about your case?

A 30-minute meeting to see what you have and what to review first.

Book a free meeting

Expert review, automated tool or the AI itself

All three are useful, each for one thing. AI brings the volume and people bring the judgment: that is why our review uses an automated AI tool and senior developers supervise it.

See the full comparison

Hands drawing a diagram of screens joined by arrows with a marker on a small whiteboard, next to white headphones

Who reviews

The review is done by a team of senior developers, with many hours of development and of finding the mistakes AI makes when it codes. We know more than 1,200 review points. The automated AI tool goes through them, and people verify, direct and review.

Team of senior developers

José María Salido, founder of Sondeon, answers for it

  • AI brings the volume: it goes through the known review points
  • People bring the judgment: they verify every finding before it goes into the report
  • The result is explained in a meeting with your team
Who answers for it: José María Salido, on LinkedIn

Frequently asked questions

Which database engines do you review?

We review PostgreSQL, Redis and compatible engines (Valkey, Dragonfly, KeyDB), Elasticsearch or OpenSearch, and RabbitMQ. Other engines are looked at case by case in the meeting.

Does the review affect my running system?

No. The review only reads: it changes no data, tables or configuration. The changes we propose go in the report so you decide which ones are applied.

What do you need to get started?

A read-only user on each engine and read access to the code that uses the database. What we ask for is written into the scope before we start.

Do you do database optimization or PostgreSQL tuning?

We measure first: slow queries, indexes that are missing or that nothing uses, locks and memory. The fix is separate and only if you ask: your team applies it with the report, or we do with the changes you approve.

How much does a database audit cost, and how long does it take?

The 30-minute meeting is free. The rest depends on how many engines are included and on the size of the data. We go over it in that meeting, and you get the scope and timeline of our health check in writing before we start.

What is a database audit, and how often should you do one?

It is a review of how the database is set up and how it responds: indexes, slow queries, locks, memory and queues. It is not the log of who did what inside the engine. Our health check is read-only and runs before going to production and every three months, because data grows.

Other services

  • Mobile app review

    Flutter apps built with AI, tested on real iOS and Android phones by command and with touch gestures, together with their backend.

  • Public website review

    Your website's performance, visibility in search engines and in AI assistants (SEO and GEO), accessibility and security, measured on the real page.

  • Backend and API review

    The server side behind your app or your website: what the API exposes, what it protects, what headers it serves and what ends up in its logs.

  • Deployment server review

    The server your system will run on, reviewed before you go live: who has access, what runs on it and which limits break as you grow.

  • Infrastructure monitoring

    The Linux machines your system runs on, measured every few seconds, so you see a full disk or a stopped container before your users do.

  • API monitoring

    Every call to your API measured, with its latency, its error and the screen that requested it, so you know which endpoint to optimize before traffic grows.

All services

Request your free meeting

Fill in the form and we email you to set a day and a time. It is 30 minutes to see what you have and what to review first.

What should we control?

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