steampipe plugin install ocisteampipe plugin install oci

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

The Oracle Cloud Infrastructure (OCI) Core Boot Volume is a persistent and durable block storage volume in OCI. It provides high performance, reliability, and scalability for your applications. Boot volumes are used to boot up an instance and contain the image of the operating system running on your instance.

Table Usage Guide

The oci_core_boot_volume_metric_read_ops_daily table provides insights into the daily read operations metrics for OCI Core Boot Volumes. As a Database Administrator or a DevOps engineer, you can use this table to monitor the performance of your boot volumes, which can help in analyzing the workload and making data-driven decisions for optimizing resource allocation. Utilize it to uncover information about the read operations, such as the volume of data read from your boot volumes, and the time taken for these operations, which can be crucial for performance tuning and troubleshooting.

Examples

Basic info

Analyze the daily read operations of boot volumes in Oracle Cloud Infrastructure (OCI) to understand the range, average, total count, and specific instances of these operations. This could help in monitoring the performance and usage patterns of the boot volumes.

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

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

Intervals where volumes exceed 1000 average read ops

Analyze the intervals where the average read operations on boot volumes exceed a thousand. This analysis can help identify periods of high demand or potential performance issues.

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

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

Intervals where volumes exceed 8000 max read ops

Determine the instances where the maximum read operations on a boot volume surpass 8000, allowing you to identify potential bottlenecks or high-demand periods in your system. This can be crucial for capacity planning and optimizing system performance.

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

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

Read, Write, and Total IOPS

Determine the areas in which the input/output operations per second (IOPS) for a boot volume are at their maximum, minimum, and average. This analysis can help optimize the performance of your system 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_daily as r,
  oci_core_boot_volume_metric_write_ops_daily 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_daily as r,
  oci_core_boot_volume_metric_write_ops_daily 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_daily

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_daily