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Originally posted by sravani-64 December 23, 2024
Hi team,
As a part of developing Aerospike integration dashboards, we need to create a query using conditional operators such as IF, OR. But we are not able to replicate the exact query as similar to Grafana. Grafana's query:
(sum( # Running individual exporter for each node in a cluster
(avg by (ns) ( aerospike_namespace_ns_cluster_size {job="$job_name", } ))
== bool
(count by (ns) (aerospike_namespace_ns_cluster_size {job="$job_name", } ))
)> bool 0) * # migration check with RX metric
(sum((sum by (ns) (aerospike_namespace_migrate_rx_partitions_remaining + aerospike_namespace_migrate_tx_partitions_remaining) != bool 0))
== bool 0) * # Consistent Effective Replication factor across all nodes
(sum(
min by (ns) (aerospike_namespace_effective_replication_factor {job="$job_name", })
== bool
max by (ns) (aerospike_namespace_effective_replication_factor {job="$job_name", })
) > bool 0)
Discussed in #19300
Originally posted by sravani-64 December 23, 2024
Hi team,
As a part of developing Aerospike integration dashboards, we need to create a query using conditional operators such as IF, OR. But we are not able to replicate the exact query as similar to Grafana.
Grafana's query:
(sum( # Running individual exporter for each node in a cluster
(avg by (ns) ( aerospike_namespace_ns_cluster_size {job="$job_name", } ))
== bool
(count by (ns) (aerospike_namespace_ns_cluster_size {job="$job_name", } ))
)> bool 0) * # migration check with RX metric
(sum((sum by (ns) (aerospike_namespace_migrate_rx_partitions_remaining + aerospike_namespace_migrate_tx_partitions_remaining) != bool 0))
== bool 0) * # Consistent Effective Replication factor across all nodes
(sum(
min by (ns) (aerospike_namespace_effective_replication_factor {job="$job_name", })
== bool
max by (ns) (aerospike_namespace_effective_replication_factor {job="$job_name", })
) > bool 0)
Query tried in Datadog:
{
"title": "Cluster - Historical - Usage Bytes",
"type": "query_value",
"requests": [
{
"formulas": [
{
"formula": "((count_nonzero(query1) / count_nonzero(query2)) * (abs(count_nonzero(query3) + count_nonzero(query4)) + 1) * (count_nonzero(query5) / count_nonzero(query6)) * (query7 / query8) / query9) - (query10 * 39)"
}
],
"queries": [
{
"name": "query1",
"data_source": "metrics",
"query": "avg:aerospike.aerospike_namespace_ns_cluster_size{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query2",
"data_source": "metrics",
"query": "count:aerospike.aerospike_namespace_ns_cluster_size{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query3",
"data_source": "metrics",
"query": "sum:aerospike.aerospike_namespace_migrate_rx_partitions_remaining{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query4",
"data_source": "metrics",
"query": "sum:aerospike.aerospike_namespace_migrate_tx_partitions_remaining{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query5",
"data_source": "metrics",
"query": "min:aerospike.aerospike_namespace_effective_replication_factor{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query6",
"data_source": "metrics",
"query": "max:aerospike.aerospike_namespace_effective_replication_factor{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query7",
"data_source": "metrics",
"query": "sum:aerospike.aerospike_namespace_data_used_bytes{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query8",
"data_source": "metrics",
"query": "avg:aerospike.aerospike_namespace_effective_replication_factor{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query9",
"data_source": "metrics",
"query": "avg:aerospike.aerospike_namespace_data_compression_ratio{$aerospike_cluster}",
"aggregator": "last"
},
{
"name": "query10",
"data_source": "metrics",
"query": "sum:aerospike.aerospike_namespace_master_objects{$aerospike_cluster}",
"aggregator": "last"
}
],
"response_format": "scalar",
"conditional_formats": [
{
"comparator": ">=",
"value": 0,
"palette": "white_on_green"
}
]
}
],
"autoscale": true,
"text_align": "center",
"custom_links": [],
"precision": 2,
"timeseries_background": {
"type": "area",
"yaxis": {
"include_zero": true
}
}
}
But the above Datadog query does not fetch the required output, can someone please help in understanding the usage of conditional functions in Datadog queries?
Thank you
cc @ @gandham-santhosh @srikanth-6520 @raj-Optit @VENKATA-SIVA-OPTIT
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