What to monitor in bedrock and opensearch in aws?

 Monitoring Amazon Bedrock and Amazon OpenSearch Service in AWS is crucial for ensuring performance, availability, and cost-effectiveness. Here's a breakdown of what to monitor in each service:

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🧠 Amazon Bedrock – What to Monitor

Since Bedrock is a fully managed service for foundation models (FMs), you have limited but critical observability and monitoring options via CloudWatch, CloudTrail, and Service Quotas.

✅ Key Metrics (via CloudWatch)

1. Invocation Metrics

   • Invocations: Total number of requests made to the model.

   • InvocationErrors: Failed invocation counts.

   • ModelLatency: Latency for successful invocations (in milliseconds).

   • ThrottledRequests: Requests rejected due to exceeding throttling limits.

   • ValidationErrors: Bad input/request payloads.

2. Throughput Metrics

   • TokensIn: Number of input tokens used.

   • TokensOut: Number of output tokens generated.

   • TotalTokens: Sum of TokensIn + TokensOut.

3. Cost and Quota Monitoring

   • Monitor TokensIn/Out to track usage-based costs.

   • Use Service Quotas to monitor limits on invocation rates or model-specific quotas.

🔔 Alerts & Best Practices

• Alert on high latency or invocation errors.

• Set thresholds for monthly token usage to control costs.

• Use CloudTrail to audit who is calling which model.

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🔍 Amazon OpenSearch – What to Monitor

Amazon OpenSearch requires deeper observability because you're managing a cluster. You should monitor cluster health, performance, security, and resource usage.

✅ Key Metrics (via CloudWatch / OpenSearch Dashboards)

1. Cluster Health

• ClusterStatus: Should be GREEN (YELLOW = replica shards missing; RED = primary shards missing).

• NumberOfNodes

• ActivePrimaryShards / ActiveShards

• UnassignedShards

2. Search and Indexing Performance

• SearchLatency: High latency can affect user experience.

• SearchRate: Requests/sec.

• IndexingLatency: Time to index documents.

• IndexingRate: Documents indexed per second.

3. Node/Instance Metrics

• JVMMemoryPressure: JVM heap pressure; should ideally be < 75%.

• CPUUtilization: High values indicate contention.

• FreeStorageSpace: Monitor EBS disk usage.

• InstanceHealth: To catch instance-level issues.

4. Storage & IOPS

• EBS metrics like BurstBalance, VolumeReadOps, VolumeWriteOps.

5. Slow Logs

• Enable and analyze slow search and slow indexing logs.

6. Security Monitoring

• Track failed logins or unauthorized access attempts.

• Audit logs (via Cognito/IAM or custom integration).

• Monitor fine-grained access control policies (if enabled).

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📈 Tools & Tips

Tool	Use
CloudWatch Dashboards	Custom dashboards for both Bedrock & OpenSearch
AWS CloudTrail	Monitor API usage for auditing
OpenSearch Dashboards	Visualize logs, search metrics
Service Quotas	Set alarms for Bedrock limits
AWS Cost Explorer	Track token usage costs (Bedrock)

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🎯 Summary

Category	Bedrock	OpenSearch
Invocation Errors	✅	✅
Latency	✅	✅
Usage Quotas	✅	❌
Token Consumption	✅	❌
CPU & Memory	❌	✅
JVM Pressure	❌	✅
Disk Space	❌	✅
Indexing/Search Performance	❌	✅
Security Events	✅ (via IAM)	✅ (with fine-grained auth)

Here are the CloudWatch namespace names for both Amazon Bedrock and Amazon OpenSearch Service:

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🧠 Amazon Bedrock

• CloudWatch Namespace:

  AWS/Bedrock
  

Example Metrics in AWS/Bedrock:

• Invocations

• InvocationErrors

• ModelLatency

• TokensIn

• TokensOut

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🔍 Amazon OpenSearch Service

• CloudWatch Namespace:

  AWS/ES
  

(Note: AWS retained ES from the older "Elasticsearch Service" name.)

Example Metrics in AWS/ES:

• ClusterStatus.green

• ClusterStatus.red

• JVMMemoryPressure

• CPUUtilization

• FreeStorageSpace

• SearchLatency

• IndexingRate