steampipe plugin install oci

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

Oracle Cloud Infrastructure's Core Boot Volume is a block storage volume that contains the image used to boot a Compute instance. These boot volumes are reliable and durable, with built-in redundancy to protect your data against failure. They also offer high performance and a large storage capacity.

Table Usage Guide

The oci_core_boot_volume_metric_write_ops_hourly table provides insights into the hourly write operations metrics of OCI Core Boot Volumes. As a data analyst or a cloud operations engineer, you can use this table to monitor and analyze the write operations performance of your boot volumes on an hourly basis. This can be particularly useful for identifying potential issues, optimizing performance, and ensuring the efficient use of resources.

Examples

Basic info

Explore the hourly write operations on boot volumes in Oracle Cloud Infrastructure. This can help assess the volume's performance over time and identify any potential issues or trends.

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

Intervals where volumes exceed 1000 average write ops

Explore instances where the average write operations exceed 1000 on an hourly basis. This can be useful for identifying potential periods of high activity or system stress.

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

Intervals where volumes exceed 8000 max write ops

Determine the instances where the maximum write operations on boot volumes exceed a set threshold. This can help in identifying potential performance issues and planning for capacity upgrades.

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

Read, Write, and Total IOPS

Analyze the performance of your boot volume by observing the average, maximum, and minimum input/output operations per second (IOPS). This can help you understand how your system is performing and where potential bottlenecks might be occurring.

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;

Schema for oci_core_boot_volume_metric_write_ops_hourly

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form.
averagedouble precisionThe average of the metric values that correspond to the data point.
compartment_idtextThe ID of the compartment.
idtextThe OCID of the boot volume.
maximumdouble precisionThe maximum metric value for the data point.
metric_nametextThe name of the metric.
minimumdouble precisionThe minimum metric value for the data point.
namespacetextThe metric namespace.
regiontextThe OCI region in which the resource is located.
sample_countdouble precisionThe number of metric values that contributed to the aggregate value of this data point.
sp_connection_nametext=, !=, ~~, ~~*, !~~, !~~*Steampipe connection name.
sp_ctxjsonbSteampipe context in JSON form.
sumdouble precisionThe sum of the metric values for the data point.
tenant_idtext=, !=, ~~, ~~*, !~~, !~~*The OCID of the Tenant in which the resource is located.
tenant_nametextThe name of the Tenant in which the resource is located.
timestamptimestamp with time zoneThe time stamp used for the data point.
unittextThe 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_write_ops_hourly