Unlocking Kubernetes efficiency: How Ocean elevates observability

Running Kubernetes at scale is powerful, but it’s also famously complex. Between fluctuating workloads, unpredictable cloud costs and the constant pressure to maintain performance, engineering teams often find themselves drowning in operational overhead. Ocean, Flexera’s container optimization solution, changes that equation by automating infrastructure decisions so teams can focus on building, not firefighting.

But automation alone isn’t enough. Modern teams need visibility—clear, trustworthy insights into how their clusters behave, how scaling decisions are made and how those decisions impact both performance and cost.

That’s where Ocean’s deep integration with Prometheus, Grafana and Datadog becomes a true differentiator.

Why observability matters more than ever

Kubernetes environments generate a massive amount of operational data: CPU/GPU and memory usage, pod lifecycle events, node health, autoscaling triggers and more. Without a strong observability stack, this data becomes noise instead of insight.

Many organizations already rely on at least one of the major observability pillars:

• Prometheus for metrics scraping
• Grafana for visualization
• Datadog for unified enterprise monitoring

Ocean doesn’t replace these tools—it enhances them. By exposing rich optimization and scaling metrics, Ocean plugs directly into existing observability pipelines, giving teams the transparency they need to trust and validate automation. As a pre-requisite to achieve the above, Ocean Metric Exporter should be enabled when installing the controller.

Enabling Ocean Metrics Exporter when installing Ocean Controller

Ocean + Prometheus: metrics you can trust

Ocean exposes a comprehensive set of metrics that Prometheus can scrape natively. These include:

• Node lifecycle events
• Autoscaling decisions
• Resource utilization
• Workload placement efficiency
• Cost‑related optimization data

Because these metrics follow standard Prometheus conventions, teams can integrate Ocean into their existing monitoring workflows without adopting new tools or dashboards.

By default, Ocean Metrics Exporter exposes scaling data only. To add cost and rightsizing metrics, values should be set by updated to include this information:

helm upgrade spot-ocean-metric-exporter spot/ocean-metric-exporter --reuse-
values --set "metricsConfiguration.categories={scaling,cost_analysis,rightsizing}" -n 
spot-system

This provides accessible metrics in the format teams already use.

Ocean + Grafana: visualizing optimization in real time

Prometheus provides the data—Grafana brings it to life. Ocean’s metrics can be visualized in Grafana to show:

• Efficiency improvements
• Cost savings over time
• Node provisioning patterns
• Pod distribution and bin‑packing
• Scaling behavior during peak load
• Historical performance trends

This gives engineering, DevOps, SRE and FinOps teams the ability to validate Ocean’s decisions, not just trust them blindly.

Grafana dashboard exposing Ocean metrics

Ocean + Datadog: Enterprise observability through simple annotations

For organizations standardizing on Datadog, Ocean integrates seamlessly through metrics exporter annotations. This lightweight approach allows Datadog to ingest Ocean’s optimization and autoscaling metrics without additional agents or custom pipelines.

With Datadog, teams can:

• Correlate Ocean events with application‑level telemetry
• Visualize optimization trends in existing dashboards
• Monitor events based on Ocean’s scaling or node lifecycle behavior
• Maintain a single observability plane across infrastructure and workloads

This is especially valuable for enterprises that rely on Datadog for logs, traces, APM and security monitoring. Ocean fits naturally into that ecosystem.

 

Datadog dashboard exposing Ocean metrics

To allow Datadog to access and display Metrics exporter metrics, the following annotations need to be added to Metrics Exporter Deployment:

spec: 
..... 
template: 
 metadata: 
  annotations: 
   kubectl.kubernetes.io/restartedAt: "2026-02-16T11:05:53Z" 
   prometheus.io/port: "5050" 
   prometheus.io/scrape: "true"

The “/metrics” endpoint is already set by default so no need to add it to the annotations above.

In addition, DataDog agent installation should include the following two parameters to allow the agent to scrape metrics exposed by Metrics Exporter:

spec: 
... 
 features: 
  prometheusScrape: 
   enabled: true 
   enableServiceEndpoints: true

The cost impact: visibility that drives savings

Ocean already reduces cloud spend by optimizing node selection, bin‑packing workloads, rightsizing and leveraging Spot instances. But observability amplifies these savings by enabling teams to:

• Identify underutilized workloads
• Validate that automation is producing measurable cost reductions
• Detect misconfigurations that lead to unnecessary scaling
• Track cost trends in real time
• Provide transparent, auditable data for FinOps teams

In short, observability turns optimization into measurable ROI.

Teams that combine Ocean with Prometheus, Grafana or Datadog consistently report:

• Faster optimization cycles
• Better Spot utilization
• Fewer over‑provisioned nodes
• Clearer cost accountability

Automation saves money. Observability proves it.

Closing thoughts on these tools

Ocean by Flexera is already known for simplifying Kubernetes operations and reducing cloud costs through intelligent automation. But its real power emerges when paired with the observability tools teams already trust.

By integrating seamlessly with Prometheus, Grafana and Datadog, Ocean provides the transparency needed to understand, validate and maximize the impact of its optimization engine.

If you’re running Kubernetes in production, this combination isn’t just helpful—it’s transformative.

Learn how Flexera can help

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