use super::{OptimizationRule, RuleContext, codes};
use crate::analyzer::k8s_optimize::config::K8sOptimizeConfig;
use crate::analyzer::k8s_optimize::parser::parse_cpu_to_millicores;
use crate::analyzer::k8s_optimize::types::{
OptimizationIssue, ResourceRecommendation, ResourceSpec, RuleCode, Severity, WorkloadType,
};
pub struct HighCpuRequestRule;
impl OptimizationRule for HighCpuRequestRule {
fn code(&self) -> &'static str {
codes::HIGH_CPU_REQUEST
}
fn description(&self) -> &'static str {
"CPU request exceeds threshold for workload type"
}
fn default_severity(&self) -> Severity {
Severity::High
}
fn check(
&self,
ctx: &RuleContext,
config: &K8sOptimizeConfig,
) -> Option<ResourceRecommendation> {
if matches!(
ctx.workload_type,
WorkloadType::Batch | WorkloadType::MachineLearning
) {
return None;
}
let cpu_request = ctx.current.cpu_request.as_ref()?;
let millicores = parse_cpu_to_millicores(cpu_request)?;
if millicores <= config.max_cpu_request_millicores as u64 {
return None;
}
let defaults = ctx.workload_type.default_resources();
let recommended = ResourceSpec {
cpu_request: Some(defaults.cpu_request.to_string()),
cpu_limit: Some(defaults.cpu_limit.to_string()),
memory_request: None,
memory_limit: None,
};
Some(ResourceRecommendation {
resource_kind: ctx.resource_kind.clone(),
resource_name: ctx.resource_name.clone(),
namespace: ctx.namespace.clone(),
container: ctx.container_name.clone(),
file_path: ctx.file_path.clone(),
line: ctx.line,
issue: OptimizationIssue::OverProvisioned,
severity: self.default_severity(),
message: format!(
"CPU request ({}) exceeds {}m threshold for {} workload. This is likely over-provisioned.",
cpu_request, config.max_cpu_request_millicores, ctx.workload_type
),
workload_type: ctx.workload_type,
current: ctx.current.clone(),
actual_usage: None,
recommended: recommended.clone(),
savings: None,
fix_yaml: recommended.to_yaml(),
rule_code: RuleCode::new(self.code()),
})
}
}