Viewing metrics and logs from Azure

BigAnimal sends all metrics and logs from Postgres clusters to Azure. You can view metrics and logs directly from Azure.

Azure log analytics

When BigAnimal deploys workloads on Azure, the logs from the Postgres clusters are forwarded to the Azure Log Workspace. To query BigAnimal logs, you must use Azure log analytics and Kusto query language.

Query Postgres cluster logs

All logs from your Postgres clusters are stored in the Customer Log Analytics workspace. To find your Customer Log Analytics workspace:

1. Sign in to the Azure portal.

2. Select Resource Groups.

3. Select the resource group corresponding to the region where you choose to deploy your BigAnimal cluster. You see resources included in that resource group.

4. Select the resource of type Log Analytics workspace with the prefix log-workspace-.

5. Select the logs in the menu on the left in the General section.

6. Close the dashboard with prebuilt queries, which brings you to the KQL editor.

The following tables containing BigAnimal logs are available in the Customer Log Analytic workspace.

Logs are split into structured fields matching those of the Postgres csvlog format with a record_ prefix and a type suffix. For example, the application_name is in the record_application_name_s log field. The pg_cluster_id_s field identifies the specific Postgres cluster that originated the log message.

You can use the KQL Query editor to compose your queries over these tables. For example:

PostgresLogs_CL
| project record_log_time_s, record_error_severity_s, record_detail_s
| sort by record_log_time_s desc

PostgresAuditLogs_CL
| where logger_s == "pgaudit"
| project record_log_time_s, record_error_severity_s, record_audit_statement_s
| sort by record_log_time_s desc

PostgresAuditLogs_CL
| where logger_s == "edb_audit"
| project record_log_time_s, record_error_severity_s, record_message_s
| sort by record_log_time_s desc

Using BigAnimal's cloud account

To access your Postgres cluster logs, when using BigAnimal's cloud account, generate a SAS token from BigAnimal and use it to download the logs.

1. In the BigAnimal portal, select Clusters, select your cluster, and select the Monitoring & Logging tab.

2. Select Generate Token and copy the SAS token. The SAS token is a sensitive value, so don't make it publicly available. The following is a sample SAS token:

   Toggle WrapCopy

   https://blobsamples.blob.core.windows.net/?sv=2022-11-02&ss=b&srt=sco&sp=rwlc&se=2023-05-24T09:51:36Z&st=2023-05-24T01:51:36Z&spr=https&sig=<signature> 

3. Enter the azcopy command to download the Postgres logs from BigAnimal. For example:

   Toggle WrapCopy

   azcopy copy '$TOKEN' . --recursive
   INFO: Scanning...
   INFO: Any empty folders will not be processed, because source and/or destination doesn't have full folder support
   
   Job aa4b74a0-bc92-be4e-551c-47aec1c1cfc3 has started
   Log file is located at: /Users/sample_user/.azcopy/aa4b74a0-bc92-be4e-551c-47aec1c1cfc3.log
   
   100.0 %, 5 Done, 0 Failed, 0 Pending, 0 Skipped, 5 Total, 2-sec Throughput (Mb/s): 0.5375
   
   
   Job aa4b74a0-bc92-be4e-551c-47aec1c1cfc3 summary
   Elapsed Time (Minutes): 0.0333
   Number of File Transfers: 5
   Number of Folder Property Transfers: 0
   Number of Symlink Transfers: 0
   Total Number of Transfers: 5
   Number of File Transfers Completed: 5
   Number of Folder Transfers Completed: 0
   Number of File Transfers Failed: 0
   Number of Folder Transfers Failed: 0
   Number of File Transfers Skipped: 0
   Number of Folder Transfers Skipped: 0
   TotalBytesTransferred: 134416
   Final Job Status: Completed
   $ tail p-a1b2c3d4d5/kubernetes-logs/p-a1b2c3d4d5/2023/09/26/13/19/azure_customer_postgresql_cluster.var.log.containers.p-a1b2c3d4d5-1_p-a1b2c3d4d5_postgres-c798aa19ea0481c8d9575f025405b3ad9212816ca7e928f997473055499a692c.log
   {"@timestamp":"2023-09-26T13:19:19.572442Z","level":"info","ts":"2023-09-26T13:19:19Z","logger":"wal-archive","msg":"Archived WAL file","logging_pod":"p-a1b2c3d4d5-1","walName":"pg_wal/000000010000000000000006","startTime":"2023-09-26T13:19:18Z","endTime":"2023-09-26T13:19:19Z","elapsedWalTime":1.060413255,"stream":"stdout","logtag":"F","message":"{\"level\":\"info\",\"ts\":\"2023-09-26T13:19:19Z\",\"logger\":\"wal-archive\",\"msg\":\"Archived WAL 

Metrics

BigAnimal collects a wide set of metrics about Postgres instances into the DpMetrics_CL log analytics table. Most of these metrics are acquired directly from Postgres system tables, views, and functions. The Postgres documentation serves as the main reference for these metrics.

Available metrics

The following tables in the Customer Log Analytic workspace contain metrics specific to BigAnimal.

You can use the KQL Query editor in the Log Workspace view to compose queries over these tables.

The forwarded Prometheus metrics use structured JSON fields, particularly the Message and Message.labels fields. To query these fields, you need to use the KQL function todynamic() in your queries.

Currently, all metrics forwarded from Prometheus are in the DpMetrics_CL table. This might change in a future release.

The available set of metrics is subject to change. Metrics might be added, removed or renamed. Where feasible, we will change the metric name when the meaning or type of an existing metric changes.

Metrics labels

All Postgres metrics share a common labeling scheme. Entries generally have at least the following labels.

When querying for labels, for best performance, apply filters that don't require inspecting labels (for example, filters by metric name) before label-based filters.

The labels field of a metrics entry is a nested field under the JSON-typed Message field. To query the field for individual values, you JSON parse the Message field and dot reference (m.labels) the labels property. Some uses of values might require explicit casts to another type, for example, tostring(...).

Example usage:

DpMetrics_CL
| where Message has "cnp_"
| extend m = todynamic(Message)
| where m.labels.role == "primary"
| project postgres_cluster_id = tostring(m.labels.postgresql), metric_name = m.name, metric_value = m.value

For a detailed list of available metrics, see metrics.

Workbooks

You can view logs from your Postgres clusters using Azure Workbooks. See Azure Monitor Workbooks.

To access Azure Workbooks:

1. Sign in to the Azure portal.

2. Search for workbooks.

3. Filter the search results as needed. For example, you might need to filter by subscription if your account has more than one and the location that corresponds with the region where you deployed your cluster. You can either use the filter controls or search to narrow the search results.

4. Select the workbook link in the Name column to open the workbook details. Names have the format ${GUID} (xxx-rg-${region}-management-xxx-customer), for example, 62b6d449-e0e5-480a-9809-cae2ff6510e9 (123-rg-australiaeast-management-abcd-customer).

5. Select Open Workbook in the workbook details to launch an interactive workbook with various metrics for your deployed clusters.

• On this page
• Azure log analytics
• Metrics
• Workbooks