Viewing metrics and logs from Azure

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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:

Sign in to the Azure portal.
Select Resource Groups.
Select the resource group corresponding to the region where you choose to deploy your BigAnimal cluster. You see resources included in that resource group.
Select the resource of type Log Analytics workspace with the prefix log-workspace-.
Select the logs in the menu on the left in the General section.
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.

Table name	Description	Logger
PostgresLogs_CL	Logs of the customer clusters databases (all Postgres-related logs)	`logger = postgres`
PostgresAuditLogs_CL	Audit logs of the customer clusters databases	`logger = pgaudit or edb_audit`

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

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.

Table name	Description
DpMetrics_CL	Metrics streams from BigAnimal Prometheus

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.

Name	Description
instance	IP address of the host the metric originated from
postgresql	BigAnimal postgres cluster identifier, e.g., `p-abcdef012345`
role	Postgres instance role: primary or standby replica
datname	Postgres database name (where applicable)
pod	k8s pod name
aks_cluster_name	AKS cluster name

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:

Sign in to the Azure portal.
Search for workbooks.
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.
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).
Select Open Workbook in the workbook details to launch an interactive workbook with various metrics for your deployed clusters.

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Metrics details

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