Clojure->Python CUTOVER: Step 0 — land the stack + promote edge->stable (PROD DEPLOY)

cdk/launchTemplates.ts

@@ -58,6 +58,27 @@ export default (
       `export SERVICE=${service}`,
       instanceSize ? `export INSTANCE_SIZE=${instanceSize}` : '',
       CLOUDWATCH_LOG_GROUP_NAME ? `echo "${CLOUDWATCH_LOG_GROUP_NAME}" | sudo tee ${persistentConfigDir}/log_group_name.txt` : '',
+
+      // --- CloudWatch Agent: config + start, on EVERY instance ---
+      // The agent is installed above for all tiers, but until now only the
+      // ollama user-data configured and started it, so only the GPU box
+      // published memory. Memory is the binding resource on the math and delphi
+      // tiers (all three idle at 0.5-1.3% CPU), so without this there is no
+      // evidence on which to right-size them.
+      //
+      // Guarded with `|| true` because this function runs under `set -e`: a
+      // metrics agent must never be able to abort an instance boot. The
+      // nvidia_gpu section of the config collects nothing where there is no
+      // GPU, so this is a no-op difference for ollama.
+      'echo "Configuring CloudWatch Agent..."',
+      `aws s3 cp ${cwAgentConfigAsset.s3ObjectUrl} ${cwAgentTempPath} || echo "CW agent config download failed; continuing"`,
+      `sudo mkdir -p $(dirname ${cwAgentConfigPath}) || true`,
+      `sudo mv ${cwAgentTempPath} ${cwAgentConfigPath} || true`,
+      `sudo chmod 644 ${cwAgentConfigPath} || true`,
+      `sudo chown root:root ${cwAgentConfigPath} || true`,
+      'sudo systemctl enable amazon-cloudwatch-agent || true',
+      'sudo systemctl start amazon-cloudwatch-agent || echo "CW agent failed to start; continuing"',
+
       'exec 1>>/var/log/user-data.log 2>&1',
       'echo "Finished User Data Execution at $(date)"',
       'sudo mkdir -p /etc/docker',
@@ -102,26 +123,11 @@ ollamaUsrData.addCommands(
 
   // Start Ollama-specific setup
   'echo "Starting Ollama specific setup..."',
-  'echo "Configuring CloudWatch Agent for GPU metrics..."',
-
-  // --- Download CW Agent config from S3 Asset ---
-  `echo "Downloading CW Agent config from S3..."`,
-  // Use aws cli to copy from the S3 location provided by the asset object
-  // The instance needs NAT access (which it has) and S3 permissions (granted above)
-  `aws s3 cp ${cwAgentConfigAsset.s3ObjectUrl} ${cwAgentTempPath}`,
-  // Ensure target directory exists and move the file into place
-  `sudo mkdir -p $(dirname ${cwAgentConfigPath})`,
-  `sudo mv ${cwAgentTempPath} ${cwAgentConfigPath}`,
-  `sudo chmod 644 ${cwAgentConfigPath}`,
-  `sudo chown root:root ${cwAgentConfigPath}`, // Ensure root ownership
-  'echo "CW Agent config downloaded and placed."',
 
-  // --- Enable and Start the CloudWatch Agent Service ---
-  'echo "Enabling CloudWatch Agent service..."',
-  'sudo systemctl enable amazon-cloudwatch-agent',
-  'echo "Starting CloudWatch Agent service..."',
-  'sudo systemctl start amazon-cloudwatch-agent',
-  'echo "CloudWatch Agent service started."',
+  // NOTE: the CloudWatch agent's config download and `systemctl start` used to
+  // live here. They now run in the shared usrdata() above, for every tier, so
+  // this block would be a duplicate. The GPU metrics are unaffected: the same
+  // config file carries the nvidia_gpu section.
 
   // --- Mount EFS using standard NFSv4.1 ---
   // Use the manually constructed EFS DNS name

delphi/CLAUDE.md

@@ -16,7 +16,7 @@ this avoids the confusion of having anything called a "cid", the joke was "conve
 
 ## helpful background
 
-this was built in two parts, the pca/kmenas/repness and the umap/narrative, and these are combined in the run_delphi.sh script.
+this was built in two parts, the pca/kmenas/repness and the umap/narrative, and these are combined in the run_delphi.py script.
 
 ## Local Python Environment
 
@@ -175,7 +175,7 @@ AWS_SECRET_ACCESS_KEY=dummy
 AWS_REGION=us-east-1
 ```
 
-These are configured in run_delphi.sh for all DynamoDB operations.
+These are configured in run_delphi.py for all DynamoDB operations.
 
 ### DynamoDB Job Queue System
 
@@ -191,13 +191,13 @@ Delphi now includes a distributed job queue system built on DynamoDB:
 2. **Processing Jobs**: Start the job poller service:
 
    ```bash
-   ./start_poller.sh
+   python start_poller.py
    ```
 
 3. **Table Management**: To reset the job queue:
 
    ```bash
-   aws dynamodb delete-table --table-name DelphiJobQueue --endpoint-url http://localhost:8000 && \
+   aws dynamodb delete-table --table-name Delphi_JobQueue --endpoint-url http://localhost:8000 && \
    docker exec -e PYTHONPATH=/app polis-dev-delphi-1 python /app/create_dynamodb_tables.py --endpoint-url http://host.docker.internal:8000
    ```
 
@@ -210,7 +210,7 @@ Delphi now includes a distributed job queue system built on DynamoDB:
 ### Table Creation
 
 - Primary script: `/create_dynamodb_tables.py` - Creates BOTH Polis math and EVōC tables
-- This script is used in `run_delphi.sh` and now integrated into `umap_narrative/run_pipeline.py`
+- This script is used in `run_delphi.py` and now integrated into `umap_narrative/run_pipeline.py`
 
 ### Schema Definitions
 
@@ -242,7 +242,7 @@ Delphi now includes a distributed job queue system built on DynamoDB:
 - `Delphi_CollectiveStatement` - Collective statements generated for topics
 
 > **Note:** All table names now use the `Delphi_` prefix for consistency.
-> For complete documentation on the table renaming, see `/Users/colinmegill/polis/delphi/docs/DATABASE_NAMING_PROPOSAL.md`
+> Table definitions in `create_dynamodb_tables.py` are the canonical reference for names and schemas.
 
 ## Reset Single Conversation
 
@@ -281,7 +281,7 @@ See [RESET_SINGLE_CONVERSATION.md](docs/RESET_SINGLE_CONVERSATION.md) for detail
 After identifying the correct conversation ZID, run the Delphi pipeline directly with:
 
 ```bash
-./run_delphi.sh --zid=[ZID]
+python run_delphi.py --zid [ZID]
 ```
 
 Additional options include:
@@ -297,7 +297,7 @@ For production environments, use the job queue system:
 1. Start the poller service on your worker machine:
 
    ```bash
-   ./start_poller.sh
+   python start_poller.py
    ```
 
 2. Submit a job from any machine with access to DynamoDB:
@@ -323,13 +323,6 @@ For production environments, use the job queue system:
    docker exec -e PYTHONPATH=/app polis-dev-delphi-1 python /app/create_dynamodb_tables.py --endpoint-url http://host.docker.internal:8000
    ```
 
-   Or use the reset_database.sh script to recreate all tables:
-
-   ```bash
-   # Reset all tables (both Polis math and EVōC tables)
-   ./reset_database.sh
-   ```
-
 2. **Testing specific pipeline stages**:
 
    ```bash