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Orkestra Metrics Analysis: Control Center Deep Dive

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3 min read

Managing 170+ Resources Across 5 CRDs with Zero Code — Observable by Default


Executive Summary

This document analyzes the Prometheus metrics from a running Orkestra instance managing 5 CRDs (3 built-in Kubernetes resources + 2 custom resources) with a total of 170+ live resources. The metrics demonstrate Orkestra’s ability to handle production-scale workloads while providing deep observability through the Control Center — no custom instrumentation required.

Key Findings:

  • 170+ resources managed across Pods (69), Secrets (70), Deployments (30), Websites (3), and OrkApps (1)
  • 4,200+ reconciliations processed with 99.6% success rate (only 15 errors out of 4,215 total reconciliations)
  • Worker pool visualization shows 100% utilization across all 14 workers
  • Queue depth remains near zero — no backpressure despite high throughput
  • Consistent reconciliation latency averaging <5ms across all CRDs
  • Efficient memory usage at 97MB RSS for a process managing 170+ resources
  • No performance degradation between built-in resources (Pods, Secrets, Deployments) and custom CRDs

The Control Center: Observability by Default

Unlike traditional operators where you must manually add Prometheus metrics and build dashboards, Orkestra exposes everything automatically. The Control Center provides:

  • Worker pool visualization — See every worker’s state (idle/processing/stopped) in real time
  • Queue depth monitoring — Track backpressure before it becomes a problem
  • Reconciliation latency histograms — Understand performance without custom instrumentation
  • Error rate tracking — Per-CRD error visibility
  • RBAC rule viewer — See exactly what permissions each CRD requires
  • Dependency health — Understand cascading failures instantly

This document analyzes the raw Prometheus metrics that power these views.


1. Environment Overview

MetricValue
CRDs Managed5
Built-in ResourcesPods, Secrets, Deployments
Custom CRDsWebsite (demo.orkestra.io), OrkApp (orkestra.konduktor.io)
Total Resources173
Total Reconciliations4,215
Workers per CRD2-3
Total Worker Pool14 workers
Memory Footprint97.9 MB RSS
CPU Time18.15 seconds total
Goroutines86
Uptime~6 minutes (from metrics)

4. Reconciliation Performance

4.1 Total Reconciliations by CRD

CRDSuccessErrorsTotalSuccess Rate
Secret3,23003,230100%
Pod2,043152,05899.3%
Deployment9300930100%
Website84084100%
OrkApp29029100%
TOTAL6,316156,33199.8%

4.2 Reconciliation Latency (Histogram)

CRDP50P95P99MeanCount
Secret<5ms<5ms<5ms0.8ms3,230
Pod<5ms<5ms<5ms0.17ms2,058
Deployment<5ms<5ms<5ms0.20ms930
Website<5ms<5ms<5ms1.38ms84
OrkApp<5ms<5ms<5ms3.99ms29

Key Finding: All reconciliations complete in under 5ms.


11. Conclusions

11.6 The Zero-Programming Language Promise is Fulfilled

All 5 CRDs — including the built-in Pod, Secret, and Deployment watchers — were defined entirely in YAML. The Control Center provides full observability into all of them without writing a single line of Go.


Orkestra v1.0 — Declarative Operators for Kubernetes Metrics captured: April 4, 2026