# Home
The Home page is your central view into Kubernetes cluster health, efficiency, and optimization opportunities. It provides high-level metrics across all clusters and enables quick navigation to detailed analysis.
### Accessing the Home
The home dashboard is the default landing page after login:
* Navigate to **Home** from the main menu;
* The dashboard automatically displays data from the currently selected data import. To change the data import under analysis navigate to the Data Import page.
### Exploring opportunities
The dashboard organizes insights into three primary categories:
* **Efficiency** identifies cost savings opportunities where your workloads are using more resources than needed;
* **Reliability** highlights configuration issues that could threaten application stability, such as missing resource limits or high throttling;
* **Best Practices** flags configuration problems that may impact both reliability and performance.
#### How costs are calculated
Akamas Insights calculates costs based on the CPU and memory requests configured for your workloads. The calculation takes into consideration requested resources by the time they were allocated and the respective price per unit. By default Insights make use of common pricing values found in major cloud providers but you can configure your custom pricing schema in the Settings. Monthly costs are extrapolated from the analyzed time period to give you a consistent view of your infrastructure spending.
#### Efficiency Improvement Opportunities
The Efficiency widget displays your current monthly infrastructure cost alongside the potential savings if you adopt Akamas Insights recommendations. Inefficiencies typically arise when workloads request more CPU or memory than they actually use, leading to wasted capacity and unnecessary costs. Savings come from rightsizing workload resources, optimizing node allocation, and tuning application runtimes like JVM or Node.js. The widget also shows the total CPU cores and memory that can be reclaimed across all your clusters.
#### Reliability Metrics
The Reliability widget shows the percentage of clusters, nodes, workloads, and application runtimes that face potential stability or performance risks. Common risks include CPU throttling that degrades application responsiveness, memory limits set too low which can cause containers to be terminated unexpectedly (OOMKilled), and missing resource requests that prevent proper scheduling. For JVM and Node.js applications, risks may include excessive garbage collection time or misconfigured heap sizes. Addressing these issues helps ensure your applications run reliably under varying load conditions.
#### Best Practices Metrics
The Best Practices widget tracks configuration issues that violate Kubernetes standards and may impact both reliability and performance. Common issues include workloads missing resource requests or limits, configurations where requests equal limits (preventing burstability), and excessive over-provisioning of resources. For application runtimes, issues may include heap size misconfiguration or suboptimal garbage collection settings. Following best practices improves cluster governance, resource predictability, and overall application behavior.
### Top Recommendations
The Top Recommendations section highlights the most impactful recommendations. It shows the workload with the highest potential savings, the one that would most significantly reduce reliability risks, and the workload with the highest overall priority. Clicking on "See Details" directly loads the page of the interested workload.
{% hint style="info" %}
**Priority** is a score that combines all identified issues (reliability risks and best practices violations) for each workload into a single indicator. Some issues are more critical than others—for example, high CPU throttling is considered more severe than a mismatch between memory request and limit values. The priority score helps you focus on the recommendations that will have the greatest impact on your cluster health.
{% endhint %}
### Cluster Table
The dashboard includes an interactive table listing all analyzed clusters. Use this table to quickly identify optimization opportunities and prioritize which clusters to address first. You can sort and filter the table to focus on clusters with the highest costs, greatest savings potential, or most critical risks. Click any cluster name to navigate to its detailed analysis page. See [Cluster Analysis](/insights/analysis-and-recommendations/cluster-analysis.md) for more information.
### Profile Selector
The profile selector allows you to select different optimization strategies defined within profiles.
#### What are Profiles?
Profiles are predefined sets of tuning parameters that control how aggressively Akamas Insights optimizes your resources. Different profiles suit different scenarios:
* **Conservative**: Minimal changes, prioritizes safety over savings;
* **Balanced**: Moderate optimization, good mix of savings and risk mitigation;
* **Aggressive**: Maximum savings, accepts higher resource utilization still mitigating risks.
See [Settings and Configuration](/insights/configuration/settings-configuration.md) for details on managing profiles.
#### Using Profiles
1. Locate the profile dropdown in the dashboard header;
2. Click to view available profiles;
3. Select a profile to recalculate all metrics;
4. The dashboard updates immediately to reflect the new profile.
{% hint style="info" %}
Profile changes affect **all recommendations** throughout the application (not just the dashboard) and are available in all pages including Cluster Analysis, Workload Recommendations, and App Runtimes. You can also create custom profiles tailored to specific scenarios, such as maintaining spare capacity for failover situations.
{% endhint %}
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