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Table: oci_core_boot_volume_metric_read_ops_hourly - Query OCI Core Boot Volume Metrics using SQL

Oracle Cloud Infrastructure (OCI) Core Boot Volume is a persistent, block-level storage volume that you can attach to a single instance. The boot volume contains the image of the operating system running on your instance. The oci_core_boot_volume_metric_read_ops_hourly table provides data related to the read operations performed on the boot volumes, aggregated on an hourly basis.

Table Usage Guide

The oci_core_boot_volume_metric_read_ops_hourly table provides insights into the read operations metrics of OCI Core Boot Volumes. As a cloud engineer or system administrator, you can use this table to monitor and analyze the read operations on boot volumes, which can be crucial for performance tuning and troubleshooting. This table can be particularly useful in identifying volumes with high read operations, which might indicate a need for capacity planning or performance optimization.

Examples

Basic info

Analyze the settings to understand the performance of boot volumes in Oracle Cloud Infrastructure over time. This query can be used to monitor the read operations, allowing you to pinpoint any unusual activity or potential bottlenecks.

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
order by
  id,
  timestamp;

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
order by
  id,
  timestamp;

Intervals where volumes exceed 1000 average read ops

Identify instances where the average read operations on boot volumes surpass 1000 within an hour. This can help pinpoint potential areas of high workload and facilitate proactive system management.

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
where
  average > 1000
order by
  id,
  timestamp;

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
where
  average > 1000
order by
  id,
  timestamp;

Intervals where volumes exceed 8000 max read ops

Assess the instances where the maximum read operations on boot volumes exceed a threshold of 8000. This can be beneficial in identifying periods of high traffic or potential performance issues within your server infrastructure.

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
where
  maximum > 8000
order by
  id,
  timestamp;

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  oci_core_boot_volume_metric_read_ops_hourly
where
  maximum > 8000
order by
  id,
  timestamp;

Read, Write, and Total IOPS

Determine the areas in which input/output operations per second (IOPS) are occurring, providing a comprehensive view of both read and write operations. This can help optimize system performance by identifying potential bottlenecks or areas for improvement.

select
  r.id,
  r.timestamp,
  round(r.average) + round(w.average) as iops_avg,
  round(r.average) as read_ops_avg,
  round(w.average) as write_ops_avg,
  round(r.maximum) + round(w.maximum) as iops_max,
  round(r.maximum) as read_ops_max,
  round(w.maximum) as write_ops_max,
  round(r.minimum) + round(w.minimum) as iops_min,
  round(r.minimum) as read_ops_min,
  round(w.minimum) as write_ops_min
from
  oci_core_boot_volume_metric_read_ops_hourly as r,
  oci_core_boot_volume_metric_write_ops_hourly as w
where
  r.id = w.id
  and r.timestamp = w.timestamp
order by
  r.id,
  r.timestamp;

select
  r.id,
  r.timestamp,
  round(r.average) + round(w.average) as iops_avg,
  round(r.average) as read_ops_avg,
  round(w.average) as write_ops_avg,
  round(r.maximum) + round(w.maximum) as iops_max,
  round(r.maximum) as read_ops_max,
  round(w.maximum) as write_ops_max,
  round(r.minimum) + round(w.minimum) as iops_min,
  round(r.minimum) as read_ops_min,
  round(w.minimum) as write_ops_min
from
  oci_core_boot_volume_metric_read_ops_hourly as r,
  oci_core_boot_volume_metric_write_ops_hourly as w
where
  r.id = w.id
  and r.timestamp = w.timestamp
order by
  r.id,
  r.timestamp;

Query examples

blockstorage_boot_volume_top_10_read_ops_avg

Schema for oci_core_boot_volume_metric_read_ops_hourly

Name	Type	Description
_ctx	jsonb	Steampipe context in JSON form, e.g. connection_name.
average	double precision	The average of the metric values that correspond to the data point.
compartment_id	text	The ID of the compartment.
id	text	The OCID of the boot volume.
maximum	double precision	The maximum metric value for the data point.
metric_name	text	The name of the metric.
minimum	double precision	The minimum metric value for the data point.
namespace	text	The metric namespace.
region	text	The OCI region in which the resource is located.
sample_count	double precision	The number of metric values that contributed to the aggregate value of this data point.
sum	double precision	The sum of the metric values for the data point.
tenant_id	text	The OCID of the Tenant in which the resource is located.
tenant_name	text	The name of the Tenant in which the resource is located.
timestamp	timestamp with time zone	The time stamp used for the data point.
unit	text	The standard unit for the data point.

Export

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- oci

You can pass the configuration to the command with the --config argument:

steampipe_export_oci --config '<your_config>' oci_core_boot_volume_metric_read_ops_hourly