Table: oci_core_boot_volume_metric_write_ops - Query OCI Core Boot Volume Metrics using SQL
Boot Volume in OCI 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 within the availability domain. The write operations metrics provide insights into the write operations performed on the boot volume.
Table Usage Guide
The oci_core_boot_volume_metric_write_ops
table provides insights into write operations metrics of boot volumes in OCI. As a system administrator or a DevOps engineer, explore details of write operations on boot volumes through this table, including the number of operations, average size, and total bytes written. Utilize it to monitor and optimize the performance of boot volumes, ensuring efficient operation of your Compute instances in OCI.
Examples
Basic info
Explore which boot volumes in your OCI Core have the highest activity by analyzing write operations. This can help determine where potential bottlenecks or high usage might be occurring.
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opsorder by id, timestamp;
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opsorder by id, timestamp;
Intervals where volumes exceed 1000 average write ops
Analyze the intervals where the average write operations exceed 1000 for boot volumes. This is useful for identifying periods of high activity and potential performance issues.
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opswhere average > 1000order by id, timestamp;
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opswhere average > 1000order by id, timestamp;
Intervals where volumes exceed 8000 max write ops
Explore instances where the maximum write operations on boot volumes exceed a certain threshold. This can help in identifying potential bottlenecks or performance issues in the system.
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opswhere maximum > 8000order by id, timestamp;
select id, timestamp, minimum, maximum, average, sum, sample_countfrom oci_core_boot_volume_metric_write_opswhere maximum > 8000order by id, timestamp;
Read, Write, and Total IOPS
Gain insights into the input/output operations of your boot volume by assessing both read and write operations. This allows you to monitor and optimize the performance of your storage system over time.
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_minfrom oci_core_boot_volume_metric_read_ops as r, oci_core_boot_volume_metric_write_ops as wwhere r.id = w.id and r.timestamp = w.timestamporder 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_minfrom oci_core_boot_volume_metric_read_ops as r, oci_core_boot_volume_metric_write_ops as wwhere r.id = w.id and r.timestamp = w.timestamporder by r.id, r.timestamp;
Schema for oci_core_boot_volume_metric_write_ops
Name | Type | Operators | Description |
---|---|---|---|
_ctx | jsonb | Steampipe context in JSON form. | |
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. | |
sp_connection_name | text | =, !=, ~~, ~~*, !~~, !~~* | Steampipe connection name. |
sp_ctx | jsonb | Steampipe context in JSON form. | |
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_write_ops