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Abd Alrhman Alloush
Abd Alrhman Alloush

Posted on • Originally published at 1datacloud.ai

Stop Switching Between AWS Console, GCP Console, and DBeaver

#database #cloud #aws #devops

If you manage databases across AWS and GCP, your daily routine probably looks something like this:

  1. Open AWS Console → navigate to RDS → find the instance you want
  2. Realize it's actually on GCP → open GCP Console → navigate to Cloud SQL
  3. Need to inspect the schema → open DBeaver, find the right connection profile, connect
  4. Your colleague asks about a MongoDB Atlas cluster → open a fourth tab

By the time you've found what you need, you've spent 10 minutes just navigating, before doing any actual work.

This is console fatigue. And it's quietly burning hours every week across every DevOps and platform team running multi-cloud infrastructure.

TL;DR

We built 1DataCloud — a unified dashboard that connects AWS, GCP, MongoDB Atlas, and on-prem databases in one place. No agents. No scripts. Just connect your IAM role or service account and see everything. Try it free →

The Real Cost of Console Switching

It's not just the time. It's the context-switching tax.

Every time you jump between AWS Console, GCP Console, DBeaver, and MongoDB Atlas, you lose the thread. You forget what you were looking for. You miss something. You open another ticket to ask someone who "knows where that database lives."

Here's what a typical multi-cloud team is actually dealing with:

  • No single inventory. There's no one place that lists every database instance across all your accounts and providers. AWS has its own view. GCP has its own view. Atlas is entirely separate.
  • No unified metadata. Want to know the engine version, region, instance class, and connection count for all your RDS and Cloud SQL instances at once? You're running queries manually across multiple consoles.
  • No shared context. When a new engineer joins, how do they know what databases exist? They get a tour. Or they find out by asking around. Or they discover something exists when it breaks.

This gets worse as your infrastructure scales. More accounts, more regions, more engines — and the problem compounds.

What a Unified Dashboard Actually Looks Like

When we set out to build 1DataCloud, the goal was simple: one place to see everything, without installing anything on your database nodes.

Here's what it gives you:

One inventory across all clouds

Connect your AWS account (via IAM role or access key), your GCP project (via service account), MongoDB Atlas (via API key), or an on-prem database (via connection string). 1DataCloud discovers all your supported instances automatically.

You end up with a single list showing every database across every provider — engine type, region, size, status, configuration — in one view.

AWS us-east-1    |  prod-mysql-rds       |  MySQL 8.0   |  db.r6g.large   |  running
AWS eu-west-1    |  analytics-redshift   |  Redshift     |  ra3.xlplus     |  running
GCP us-central1  |  orders-cloud-sql     |  PostgreSQL   |  db-n1-std-4    |  running
GCP asia-east1   |  spanner-prod         |  Spanner      |  —              |  running
Atlas            |  user-data-cluster    |  MongoDB 7.0  |  M30            |  running
On-prem          |  legacy-mysql         |  MySQL 5.7    |  —              |  running
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Auto-discovery — connect once, see everything

You don't have to manually add each instance. Connect the account, and 1DataCloud discovers what's there. New instances show up automatically.

Filter and group by cloud provider, region, engine type, or tags. Useful when you need to answer "how many PostgreSQL instances are we running in eu-west-1 across all providers?"

Schema exploration without DBeaver

Click any instance and you can browse its tables, columns, data types, indexes, and relationships — all fetched read-only through the cloud API. No need to open a separate DB client, manage connection profiles, or handle VPN tunneling just to look at a schema.

No agents. No installation.

This was a hard requirement for us. We didn't want to ask DevOps teams to deploy anything on their database nodes or set up sidecar processes. Everything is read-only and API-based. If you have an IAM role for RDS, you're already set up.

Who This Actually Helps

DBAs — stop juggling multiple consoles just to answer "what's running and where."

Platform/DevOps engineers — onboard new databases in minutes, not days. No agents, no scripts, nothing to maintain.

Engineering managers — shared visibility without creating a bottleneck. Anyone on the team can see the inventory.

New engineers — instead of a tribal knowledge tour, they open the dashboard and see everything that exists.

The Setup

Connecting takes about 2 minutes:

  1. Sign up at dashboard.1datacloud.ai
  2. Add your AWS access key or IAM role, GCP service account, Atlas API key, or on-prem connection string
  3. 1DataCloud fetches your instances and shows them in the unified inventory

That's it. No configuration files. No agents. No infrastructure changes.

What's Next

The dashboard is the foundation. Once you have a single inventory with schema metadata, you can do more with it — like querying any database in plain English using Query1AI, which generates SQL automatically from your question and executes it read-only.

But that's a separate post.

If your team is managing databases across more than one cloud and you're tired of the console maze, give 1DataCloud a try. It's free to start.

👉 1datacloud.ai

Have a multi-cloud database setup that's particularly painful to manage? Drop it in the comments — genuinely curious what patterns you're dealing with.

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