arm: main

query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach involves:

1. Using pglogical for logical replication to achieve near-zero downtime
2. Configuring pglogical publisher on the pg13 primary server
3. Setting up pglogical subscriber on the new pg16 box
4. Scheduling the cutover during a Sunday at 02:00 window

This approach allows us to migrate from PostgreSQL 13 to 16 with minimal disruption to services. The replication is already configured with the publisher on the primary and subscriber on the new server.


arm: pr

query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach was to migrate to PostgreSQL 16 using pglogical replication, with a cutover scheduled during a Sunday at 02:00 window for minimal downtime. The pglogical publisher was configured on the PostgreSQL 13 primary, while the subscriber was set up on the new PostgreSQL 16 box to handle the synchronization.

You can review the full details in our session: @session:default/20260810_091500_aa11bb


query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach was to:

1. Use pglogical for logical replication to achieve near-zero downtime
2. Configure pglogical publisher on the pg13 primary
3. Set up pglogical subscriber on the new pg16 box to sync data
4. Perform the cutover during a scheduled Sunday 02:00 window

This approach was chosen because downtime mattered, and we needed to minimize disruption to the analytics cluster during the migration process. The migration was already underway with the pglogical setup configured.

The session where we made this decision is @session:default/20260810_091500_aa11bb.


query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach involved:

1. Setting up pglogical publisher on the pg13 primary
2. Configuring a subscriber on the new pg16 box to sync data
3. Planning a cutover during a Sunday 02:00 window for minimal downtime

You can review the full details in our session: @session:default/20260810_091500_aa11bb


query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach was to:

1. Use pglogical for logical replication to achieve near-zero downtime
2. Configure pglogical publisher on the pg13 primary
3. Set up pglogical subscriber on the new pg16 box to sync data
4. Perform the cutover during a scheduled Sunday 02:00 window

This approach was chosen because downtime mattered, so we needed a method that would minimize disruption to the analytics cluster during the migration process. The migration was planned to move from PostgreSQL 13 to PostgreSQL 16.

That's the session where we made this decision: @session:default/20260810_091500_aa11bb


query: postgres migration analytics cluster

final:
Based on our conversation, we settled on using pglogical for the PostgreSQL migration of the analytics cluster. The approach involves:

1. Using pglogical for logical replication to achieve near-zero downtime
2. Configuring pglogical publisher on the pg13 primary
3. Setting up pglogical subscriber on the new pg16 box for syncing
4. Planning a cutover during a Sunday 02:00 window

The session where we discussed this is available at @session:default/20260810_091500_aa11bb.


query: checkout 504 incident final fix

query: checkout 504 incident

query: 504 error checkout

query: checkout timeout


query: checkout 504 incident final fix

query: checkout 504

final:
Based on my search of the session history, I found the final fix for the checkout 504 incident.

The precise setting and value that was shipped as the final fix was:

**statement_timeout set to 45 seconds** on the payments DB pool.

This was implemented alongside re-creating the index CONCURRENTLY during off-peak hours. The incident was caused by a nightly migration job that ran CREATE INDEX without CONCURRENTLY, which was competing with checkout writes and causing the timeouts. The team first killed the problematic index build, then implemented this timeout increase to prevent future occurrences.


query: checkout 504 incident final fix

query: checkout 504 incident

query: 504 error checkout

query: 504 error

final:
Based on our session history, I found the final fix for the checkout 504 incident.

The precise setting and value that was changed was:

**statement_timeout increased to 45 seconds** on the payments DB pool.

This was the final fix implemented after the incident where a nightly migration job had created a non-concurrent index build that was blocking checkout operations. The team first killed the problematic index build, but then needed to adjust the statement timeout to prevent the 504 errors during retry operations. They also re-created the index CONCURRENTLY during off-peak hours to prevent future occurrences.

The specific change was made to the payments database connection pool configuration to increase the statement timeout from its previous value to 45 seconds.


query: checkout 504 incident final fix

query: checkout 504

final:
Based on my search of the session history, I found the details about the checkout 504 incident and the final fix that was shipped.

The final fix was to raise the statement_timeout to 45 seconds on the payments DB pool. This was the precise setting and value that was changed to resolve the checkout 504 errors.

The complete solution involved two parts:
1. Raising statement_timeout to 45s on the payments DB pool
2. Re-creating the index CONCURRENTLY during off-peak hours

This fix was deployed everywhere after successful testing on the canary environment. The incident was caused by a nightly migration job that ran CREATE INDEX without CONCURRENTLY, which was competing with checkout writes and causing the timeouts.


query: checkout 504 incident final fix

query: checkout 504 incident

query: 504 error checkout

query: checkout


query: checkout 504 incident final fix

query: checkout 504

final:
Based on my search of the session history, I found the details about the checkout 504 incident and the final fix that was shipped.

The final fix was to raise the statement_timeout to 45 seconds on the payments DB pool. This was the precise setting and value that resolved the issue.

The incident occurred when a nightly migration job ran CREATE INDEX without CONCURRENTLY, which was competing with checkout writes and causing timeouts. Although they killed the index build and rolled back the deployment, the issue persisted due to statement timeouts firing on retries. The final solution involved increasing the statement_timeout to 45 seconds on the payments database connection pool, along with re-creating the index CONCURRENTLY during off-peak hours.


query: grafana beehive sensors

query: Grafana beehive

query: Grafana

final:
I found our conversation about setting up Grafana for the beehive sensors. According to our discussion from August 20, 2026, the Grafana instance is running on port 3000 of the garden pi. You can access it by visiting http://garden-pi:3000 and using the admin login credentials that are stored in your password manager.

The relevant exchange was:
- You asked "I want graphs"
- I responded "I set up a grafana instance for the sensor graphs."
- You asked "where do I see it"
- I replied "The dashboard is on port 3000 of the garden pi, admin login in your password manager."

This session is titled "Apiary Monitoring Setup" and can be referenced as @session:default/20260820_101000_ee33ff.


query: grafana beehive sensors

query: grafana beehive

query: sensor grafana

final:
I found our conversation about setting up Grafana for the beehive sensors. According to our discussion, you set up a Grafana instance for the sensor graphs. The dashboard is accessible on port 3000 of the garden pi, with the admin login details stored in your password manager.

You can access the graphs by navigating to http://garden-pi:3000 in your browser, where you'll need to log in using the admin credentials from your password manager.

For more details, you can review our full conversation: @session:default/20260820_101000_ee33ff


query: grafana beehive sensors

query: Grafana beehive

query: sensor dashboard grafana

query: IoT sensors monitoring

query: beehive

final:
I found our conversation about the beehive monitoring setup. Based on our discussion, you can access the Grafana graphs for the beehive sensors through the following:

The dashboard is on port 3000 of the garden pi, with admin login credentials stored in your password manager.

The specific session where we discussed this is titled "Apiary Monitoring Setup" (@session:default/20260820_101000_ee33ff). In that conversation, we confirmed that:
1. The hive telemetry (temperature, humidity, weight) is already publishing to MQTT
2. A Grafana instance was set up for the sensor graphs
3. The dashboard is accessible via port 3000 on the garden pi
4. Admin login details are in your password manager

To access the graphs, you would typically navigate to http://garden-pi:3000 in your browser and log in using the admin credentials from your password manager.


query: grafana beehive sensors

query: grafana beehive

query: sensor grafana

final:
Based on our previous conversation, you can access the Grafana graphs for the beehive sensors through the dashboard on port 3000 of the garden pi. The admin login credentials are stored in your password manager.

You can visit the dashboard at: http://garden-pi:3000

The session where we set this up is available for reference: @session:default/20260820_101000_ee33ff


query: grafana beehive sensors

query: Grafana beehive

query: Grafana

final:
I found our previous conversation about setting up Grafana for the beehive sensors. According to our discussion, you set up a Grafana instance for the sensor graphs. The dashboard is accessible on port 3000 of the garden pi, and the admin login credentials are stored in your password manager.

The relevant session is titled "Apiary Monitoring Setup" and you can access it at: @session:default/20260820_101000_ee33ff

To access the graphs, you would go to the garden pi's IP address on port 3000 (likely something like http://[garden-pi-ip]:3000) and log in using the admin credentials from your password manager.


query: grafana beehive sensors

query: grafana beehive

query: sensor data grafana

query: beehive

final:
I found our conversation about the beehive monitoring system. According to our discussion, the Grafana instance for the sensor graphs is running on port 3000 of the garden pi. You can access it at:

@session:default/20260820_101000_ee33ff

The dashboard should be accessible via http://garden-pi:3000 (assuming garden-pi is your hostname) or the IP address of that device. The admin login credentials are stored in your password manager.


query: reef aquarium build plan

final:
I found the session where we planned the reef aquarium build. It's titled "Reef Aquarium Build Plan" and you can reopen it using this link: @session:default/20260822_183000_a4b4c4

The session started with you asking to plan the 90 gallon reef aquarium build, and we discussed a build sketch including a 90g display, 30g sump, AI Hydra lighting, and a DIY stand. We also touched on the cycling timeline, suggesting a 6-8 week fishless cycle with ammonia dosing followed by introducing clean-up crew members first.


query: reef aquarium build plan

final:
I found the session where you planned the reef aquarium build. Here's the link to reopen it: @session:default/20260822_183000_a4b4c4

The session was titled "Reef Aquarium Build Plan" and started with your message: "Help me plan the 90 gallon reef aquarium build." The discussion covered aspects like the 90-gallon display tank, 30-gallon sump, AI Hydra lighting, and a DIY stand, along with a fishless cycling timeline of 6-8 weeks.


query: reef aquarium build plan

final:
I found the session where we planned the reef aquarium build. It's titled "Reef Aquarium Build Plan" and is ready for you to reopen.

@session:default/20260822_183000_a4b4c4

The session contains our initial planning discussion about the 90-gallon reef aquarium build, including details about the display tank, sump, lighting, and DIY stand. We also discussed the cycling timeline for the aquarium.

Would you like me to summarize what we discussed in that session?


query: reef aquarium build plan


query: reef aquarium build plan

final:
I found the session where we planned the reef aquarium build. It's titled "Reef Aquarium Build Plan" and you can reopen it using this link: @session:default/20260822_183000_a4b4c4

The session started with your message: "Help me plan the 90 gallon reef aquarium build." and we discussed a build including a 90g display, 30g sump, AI Hydra lighting, and a DIY stand. We also touched on the cycling timeline, planning for a 6-8 week fishless cycle with ammonia dosing.


query: reef aquarium build plan

final:
I found the session where you planned the reef aquarium build. Here's the link to reopen it: @session:default/20260822_183000_a4b4c4

This session was titled "Reef Aquarium Build Plan" and started with your message: "Help me plan the 90 gallon reef aquarium build." The conversation included discussions about the build specifications (90g display, 30g sump, AI Hydra lighting, DIY stand) and a cycle timeline (6-8 weeks fishless cycle with ammonia dosing).


final:
In that session, we decided to go with **HashiCorp Vault** for secrets management, implementing a **90-day rotation policy** and using **dynamic database credentials** for services.

The full conversation was:
- User: "We need to pick a secrets management approach for the platform team."
- Assistant: "Candidates: AWS Secrets Manager, Vault, SOPS in git."
- User: "what did we land on?"
- Assistant: "Decision: HashiCorp Vault with 90-day rotation policy, dynamic DB creds for services."


final:
Looking at our session from August 15, 2026, we decided on using **HashiCorp Vault** for secrets management with a 90-day rotation policy and dynamic database credentials for services.

The full conversation was:
1. You asked us to pick a secrets management approach for the platform team
2. I listed the candidates: AWS Secrets Manager, Vault, and SOPS in git
3. You asked what we landed on
4. I confirmed our decision was HashiCorp Vault with the 90-day rotation policy and dynamic DB creds for services

This decision was made in our session titled "Secrets Management Decision" on August 15, 2026.


final: In that session, we decided to go with HashiCorp Vault for secrets management, with a 90-day rotation policy and dynamic database credentials for services.


profile: work

final:
Looking at your session from August 15, 2026, titled "Secrets Management Decision", here's what you decided:

You chose **HashiCorp Vault** as your secrets management approach, with:
- A 90-day rotation policy
- Dynamic database credentials for services

The discussion considered three candidates: AWS Secrets Manager, Vault, and SOPS in git, but you ultimately went with HashiCorp Vault for your platform team's needs.

You can reference this decision at any time using the link: @session:work/20260815_110000_beef01


final:
In that session, we decided to go with **HashiCorp Vault** for secrets management, with a **90-day rotation policy** and **dynamic database credentials** for services.

The full conversation was:
- User: "We need to pick a secrets management approach for the platform team."
- Assistant: "Candidates: AWS Secrets Manager, Vault, SOPS in git."
- User: "what did we land on?"
- Assistant: "Decision: HashiCorp Vault with 90-day rotation policy, dynamic DB creds for services."


final:
Here's a quick rundown of your recent sessions:

1. **@session:default/20260825_200000_ffeedd** - You were addressing an issue with the GPU server being too loud at idle and needed to adjust the fan curve.
2. **@session:default/20260824_090000_d5e5f6** - You started working on a tax prep checklist for your LLC.
3. **@session:default/20260822_183000_a4b4c4** - You were planning a 90-gallon reef aquarium build.

Let me know if you'd like to dive into any of these topics further!


final:
Here's a quick rundown of your recent sessions:

1. **[GPU Server Fan Curve](@session:default/20260825_200000_ffeedd)**: You're looking to address the issue of the GPU server being too loud at idle by adjusting the fan curve.

2. **[Tax Prep Checklist](@session:default/20260824_090000_d5e5f6)**: You started working on a tax prep checklist for your LLC.

3. **[Reef Aquarium Build Plan](@session:default/20260822_183000_a4b4c4)**: You're planning a 90-gallon reef aquarium build.

Let me know if you'd like details on any of these!


final:
Here's a quick rundown of your recent sessions:

1. **@session:default/20260825_200000_ffeedd** - You were addressing an issue with the GPU server being too loud at idle and needed to adjust the fan curve.
2. **@session:default/20260824_090000_d5e5f6** - You started working on a tax prep checklist for your LLC.
3. **@session:default/20260822_183000_a4b4c4** - You began planning a 90-gallon reef aquarium build.

Let me know if you'd like to dive into any of these sessions!


query: recent work

sort: newest

query: work

sort: newest

final:
Here's a quick rundown of your recent sessions:

1. **GPU Server Fan Curve** (@session:default/20260825_200000_ffeedd) - You were addressing an issue with the GPU server being too loud at idle and needed to adjust the fan curve.
2. **Tax Prep Checklist** (@session:default/20260824_090000_d5e5f6) - You started working on a tax preparation checklist for an LLC.
3. **Reef Aquarium Build Plan** (@session:default/20260822_183000_a4b4c4) - You were planning a 90-gallon reef aquarium build.
4. **Apiary Monitoring Setup** (@session:default/20260820_101000_ee33ff) - You were setting up monitoring for beehive sensors in the yard.
5. **Checkout 504 Incident** (@session:default/20260818_140200_cc22dd) - You were troubleshooting a checkout API timeout issue in production, which involved users seeing 504 errors.

These sessions cover a mix of technical issues, personal projects, and business-related tasks.


final:
Here's a quick rundown of your recent sessions:

1. **@session:default/20260825_200000_ffeedd** - You were addressing an issue with the GPU server being too loud at idle and needed to adjust the fan curve.
2. **@session:default/20260824_090000_d5e5f6** - You started working on a tax prep checklist for your LLC.
3. **@session:default/20260822_183000_a4b4c4** - You were planning a 90-gallon reef aquarium build.

Let me know if you'd like to dive into any of these sessions!


final:
Here's a quick rundown of your recent sessions:

1. **[GPU Server Fan Curve](@session:default/20260825_200000_ffeedd)**: You're looking to address the issue of the GPU server being too loud at idle by adjusting the fan curve.
2. **[Tax Prep Checklist](@session:default/20260824_090000_d5e5f6)**: You started working on a tax prep checklist for your LLC.
3. **[Reef Aquarium Build Plan](@session:default/20260822_183000_a4b4c4)**: You're planning a 90-gallon reef aquarium build.

Let me know if you'd like details on any specific session!