🔥 The DB Grill 🔥

Oh, fantastic. A blog post on how to "efficiently" migrate HierarchyID columns. I was just thinking the other day that what the world really needs is another hyper-specific, step-by-step guide on how to forklift a proprietary data-spaghetti monster from one black box into another, all while completely ignoring the gaping security chasms you're creating. Truly, a service to the community.

Let's start with the star of the show: AWS DMS. The Database Migration Service. Or as I call it, the Data Masquerading as Secure service. You’re essentially punching a hole from your legacy on-prem SQL Server—which I’m sure is perfectly patched and has never had a single default credential, right?—directly into your shiny new Aurora PostgreSQL cluster in the cloud. You’ve just built a superhighway for data exfiltration and you’re calling it "migration."

You talk about configuring the task. I love this part. It’s my favorite work of fiction. I’m picturing the scene now: a developer, high on caffeine and deadlines, following this guide.

• Step 1: Create the DMS User. What permissions did you suggest? Oh, you didn't? Let me guess: db_owner on the source and superuser on the target, because "we need to make sure it has enough permissions to work." Congratulations, you’ve just given a single service account god-mode access to your entire company's data, past and present. The Principle of Least Privilege just threw itself out a window.

• Step 2: Configure the Endpoint. I see a lot of talk about server names and ports, but a suspicious lack of words like "TLS," "encryption-in-transit," or "client-side certificate validation." Are we just piping our entire organizational hierarchy over the wire in plaintext? Brilliant. It’s like sending your crown jewels via postcard. I’m sure no one is listening in on that traffic.

And then we get to the core of it—the HierarchyID transformation itself. This isn't a native data type in PostgreSQL. So you had to write a custom transformation rule. You wrote a script, didn't you? A clever little piece of Python or a complex SQL function that parses that binary HierarchyID string.

...configuring AWS DMS tasks to migrate HierarchyID columns...

This is where my eye starts twitching. Your custom parser is now the single most interesting attack surface in this entire architecture. What happens when it encounters a malformed HierarchyID? Does it fail gracefully, or does it crash the replication instance? Better yet, can I craft a malicious HierarchyID on the source SQL Server that, when parsed by your "efficient" script, becomes a SQL injection payload on the target?

Imagine this: '/1/1/' || (SELECT pg_sleep(999)) || '/'. Does your whole migration grind to a halt? Or how about '/1/1/' || (SELECT load_aws_s3_extension()) || '; SELECT * FROM aws_s3.query_export_to_s3(...);'. You're not just migrating data; you’re building a potential remote code execution vector and calling it a feature. Every row in that table is a potential CVE waiting to be discovered.

I can just hear the conversation with the auditors now. "So, can you walk me through your data validation and chain of custody for this migration?" Your answer: "Well, we ran a SELECT COUNT(*) on both tables and the numbers matched, so we called it a day." This entire process is a SOC 2 compliance nightmare. Where is the logging? Where are the alerts for transformation failures? Where is the immutability? You're trusting a service to perform complex, stateful transformations on your most sensitive structural data, and your plan for verification is "hope."

You’ve taken a legacy system’s technical debt and, instead of paying it down, you’ve just refinanced it on a new cloud platform with a higher interest rate, payable in the currency of a catastrophic data breach.

Thank you for publishing this. It will serve as a wonderful example in my next "How Not to Architect for the Cloud" training session. I will cheerfully ensure I never read this blog again.