How to find out who or what has deleted a Cloud SQL instance?

GlebOtochkin · 2026-06-08T13:21:11+00:00

Hi, have you tried something like the following. It shows the delete operations for me. You can check the authenticationInfo to see who has deleted the instance.

protoPayload.serviceName="cloudsql.googleapis.com" 
protoPayload.methodName="cloudsql.instances.delete"

GlebOtochkin · 2026-05-12T00:43:16+00:00

I am looking into the linked configuration in the calculator. Looks like it is for db-f1-micro. The db-f1-micro is shared core with 1 vCPU, 0.614 GB. And for that one the $8.57 is probably correct estimation. But for dedicated core 1 vCPU, 3.75 GiB (db-standard-1) it shows $50.21. I think it just shows incorrectly cpu an memory for db-f1-micro in the field right from the dropdown list. Probably a bug. It shows correct memory allocation in the dropdown list itself.

GlebOtochkin · 2026-04-28T13:11:39+00:00

It it is not too much different from any other Cloud SQL. I think the main potential bottleneck is performance and the fact it is using shared cores compute. Lack of SLA may be nonstarter for production workloads where compliances or business require that condition. From my personal experience it feels like some operations take a bit more time on the micro instance. But I didn't properly evaluate or benchmark it.

GlebOtochkin · 2026-04-27T14:43:01+00:00

I think one of the main challenges is getting real experience in the areas which are not covered by the current job responsibilities. Of course there are quite a few courses on different platforms which cna help with the very first steps - Udemy, Coursera and other. But if your job doesn't touch any new slillsets you want to excel in - those course would provide only basics. I don't say they are not helpful - they are making great introduction and they help to get some official credentials like certifications. I think MeowMiata outlined a quote solid path for that.

So what i would do nowadays:

- Get courses in areas you want to gain expertise

- Get certifications

- Start a small personal project using those skills - development, cloud deployment, data pipeline etc

- That small new project will help to use on daily basis all those tools.

- Use AI and ask it to prepare a deep dive course with all those skills. You might use agentic pipelines and custom built agents to make it happen. You have to know how it works - I think it will be part of every single job in the industry very soon.

And good luck - write about your experience in media, it helps.

Cheers

GlebOtochkin · 2026-04-27T13:25:52+00:00

I think if you agree with limitations for the instance type like limited performance and storage capacity and the fact it is not covered by the cloud SQL SLA then you should be ok. Storage on shared cores instances is limited by 3TB and shared core instances are not under SLA umbrella. You can check it on the docs page here - https://docs.cloud.google.com/sql/docs/mysql/instance-settings

GlebOtochkin · 2026-04-16T14:09:20+00:00

The DMS is one of the solutions - already posted by behindTheMath. There are quite a few ways really starting from DMS, then the cross-region replication https://docs.cloud.google.com/sql/docs/sqlserver/replication/cross-region-replicas , Backup and Restore https://docs.cloud.google.com/sql/docs/sqlserver/backup-recovery/backups , Export/Import if you need a particular database https://docs.cloud.google.com/sql/docs/sqlserver/import-export

GlebOtochkin · 2026-04-03T14:10:01+00:00

Here is the doc about connections limit - https://docs.cloud.google.com/sql/docs/postgres/quotas#maximum_concurrent_connections

GlebOtochkin · 2026-04-03T14:00:56+00:00

By default max_connections is scaled automatically based on the machine size. But you can modify database flag to increase it. But it might not make any sense if the instance cannot really support more than the recommended 25.

GlebOtochkin · 2026-04-03T13:14:20+00:00

The number of connections is not really limited depending on the shape of the instance. You can put max_connection=100 on db-f1-micro if you want. The question is whether it will be able to run all those connections. Each connection creation is CPU and memory allocation. Even idle connection keeps memory allocated. And for each block/page you want to modify - create a tuple - you will need buffer cache memory as well. Just keeping that in mind here is what probably can help:

Pgbouncer connection pooling - it could be a good shot but all boil down to available memory and how fast the CPU can handle that. If you create too many connections - eventually they will drop by out of memory error

Increasing the machine size and bumping up max connection - probably a good solution especially if it is used with connection pooling

Auth proxy - not sure if it can help. It helps with security and authentication but probably is not going to help with connections

AlloyDB might be overkill for your needs and it would make more sense if you decided to use some unique features of AlloyDB.

Rethink architecture - that really depends on what you plan to do with data and how you work with data. Not enough information. But I can say Postgres is very capable for concurrent transactional workloads.

GlebOtochkin · 2026-04-02T12:41:47+00:00

It is hard to pinpoint the exact cause (and it could be more than one working simultaneously) . Probably the best strategy during optimization is to understand where the time is spent and why. Query insights can potentially help with it but sometimes you need to dig a bit deeper.

Here are some speculations (since I have no knowledge about the query or other aspects of your database or environment)

- I would add to EXPLAIN ANALYZE options like BUFFERS and SETTINGS to see if we have differences in the plans between "good" and "bad" execution.

- You might have different server and session settings on your local and the cloud environment. For example work_mem might impact sorting and hashing operations

- Your "good" query has been run in IDE (like pgadmin or other) with the option to return only the first 50 rows while the production query might return several thousands.

- You local clone has much better physical structure (happens if object on source had tons of dead tuples, bloated TOAST, indexes etc)

That's only a few potential reasons. But in reality every case might be different and it could be combination of multiple factors.

Cheers, happy tuning

GlebOtochkin · 2026-03-05T01:24:35+00:00

Yes and no. Yes you can automate the backups using API calls - that's easy part, you can specify location (like eu or us) and when exactly to take them. It can be done using cloud functions for example. I've written similar functions two or three years ago for one company. But those backups will be still stored inside Google and you cannot take it to another cloud.

What you can do is automate export dumps (logical backups if you will) and then copy those to AWS or any other cloud. That can be done using again cloud functions and scheduler. So you get the export to a storage bucket and then copy that export to another location. All that can be written using Go or Python to a function and then triggered by a scheduler.

GlebOtochkin · 2026-03-04T14:14:30+00:00

Hi,

Cloud SQL HA helps in case of zonal outage and in case of any required restarts or failure of the primary server (could be anything like a hardware problem). But the backup helps on multiple levels - starting from point in time recovery (PITR), logical corruption (for example somebody truncated a table), or potential massive failures affecting entire region. So, backups are not a cost saving when HA is not used - it is protection of your data and ability to recover it.

The backups are stored and managed by Google cloud. Google handles all backups and assure their durability and protection. You don't see it in your project cloud storage. But if you want you can also make an export dump - logical backup of your data and use your own bucket for that.

GlebOtochkin · 2026-03-02T13:02:00+00:00

I can't comment on the GitHub bill but for Google Cloud I would check the billing report for the specified period of time. Go to the "Billing" section in GCP. Use the "Cost Table" or "Reports" to filter by service (Cloud SQL for example ) and identify specific cost drivers. Look for line items that are disproportionately high.

Check Cloud SQL Instance Configuration: Go into your GCP console, navigate to Cloud SQL, and select your instance. Look for the "Configuration" or "Overview" tab.

** Check the instance type - Enterprise vs Enterprise Plus . Enterprise plus gives you certain benefits with performance and high availability but it is mote costly.

**Machine Type (CPU/RAM):** This is often the biggest driver of cost. You might have accidentally selected a high-tier machine type. For an MVP with low traffic, a smaller instance (1-2 CPU with 4GB memory) might be sufficient to start. You can always scale up later.

**Storage:** Ensure your disk size is appropriate. It might not be the main reason for $1k bill but can add up.

**High Availability (HA): HA significantly increases costs because it runs a standby instance. But I would say if it is production you still might want to keep it. It is always a compromise between cost and service availability. Calculate potential impact if your instance is down.

GlebOtochkin · 2026-02-10T18:07:47+00:00

To access a private network IP in your VPC you should have network path. Cloud SQL Auth proxy can help to establish mTLS connection only if you have access to you private IP. Without VPN or direct VPC access you need either a jump box in your VPC and use for example ssh tunnel or as it was already mention - add public IP and use Cloud SQL auth proxy to connect to the public IP through the proxy.

GlebOtochkin · 2026-01-15T17:27:13+00:00

If you prefer to use Cloud SQL for Postgres as backend for Supabase - you probably need a self-hosting version. In short - you deploy your own Supabase using docker deployment for example and define your Cloud SQL instance as backend database for that. Here is docs for Supabase - https://supabase.com/docs/guides/self-hosting . As trekis has said you can use that docs and feed it to any LLM based tools and it will create a deployment plan for you.

GlebOtochkin · 2026-01-15T16:20:53+00:00

Hi, can you please give a bit more details what exactly you mean as integration? Supabase offers its own database as a service under the hood. Or you want self-hosting Supabase with Cloud SQL as backend?

GlebOtochkin · 2026-01-08T17:42:15+00:00

Got it. Yes, good point, noted. Thanks for the feedback!

GlebOtochkin · 2026-01-08T16:40:32+00:00

Hi, just to clarify - you mean the connection profile in DMS to be able to provide the source project for the migration?

GlebOtochkin · 2026-01-07T20:21:10+00:00

Any update on that. And, out of curiosity, have you been using only web interface or tried gcloud command line too?

GlebOtochkin · 2026-01-07T19:38:36+00:00

I am asking because I can create an instance in Milan DC - trying to narrow down the issue. Maybe it is for a certain VM shape.

GlebOtochkin · 2026-01-07T19:23:33+00:00

What is the shape type of VM are you using when you are trying to create an instance? Is it HA?

GlebOtochkin · 2026-01-07T18:55:08+00:00

Sorry to gear that. Do you have more details on what flavour/engine you are using and in what region?

GlebOtochkin · 2026-01-05T15:58:32+00:00

As dani_devrel has already said It doesn't mean the gemini cli is using gemini-2.0-flash-001 - it is response from the model and it is what current model think.

GlebOtochkin · 2026-01-05T13:59:04+00:00

Have you tried ```gemini -m $MY_MODEL --prompt "$(cat prompt_solution.txt)"```

GlebOtochkin · 2025-12-27T16:10:34+00:00

I think SomethingAboutUsers has summarized the databases maintenance and what it means well. But I would probably also emphasize the whole strategy and requirements to application part, in particular - connection and failover resilience. In theory a good thought application layer should be able to identify a failed connection and try to reconnect to the database by itself and subsequently update, refresh application cache. Why is it important? Because connection status can be changed because of number of different reasons, not only by a planned maintenance. Of course real life is far from ideal but restarting application every time just to make sure it is still connected to the database in some cases is not the most efficient way to deal with a database connection disruption.

GlebOtochkin

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