[feat:podCount] Recommendations API endpoint implementation#1963
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mbvreddy wants to merge 7 commits into
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[feat:podCount] Recommendations API endpoint implementation#1963mbvreddy wants to merge 7 commits into
mbvreddy wants to merge 7 commits into
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Reviewer's GuideImplements a new v1 REST servlet /kruize/api/v1/recommendations for listing and generating recommendations using the new schema (including pod_count and nested resources), wires it into the analyzer server context, updates related API version constants, and extends metrics instrumentation to time the new endpoint and bump list/update recommendation API versions to v3.0. Sequence diagram for the new v1 recommendations POST endpointsequenceDiagram
actor Client
participant RecommendationsResource
participant RecommendationEngine
participant HttpServletResponse
participant MetricsConfig
Client->>RecommendationsResource: doPost(request, response)
RecommendationsResource->>MetricsConfig: meterRegistry()
activate RecommendationsResource
Note over RecommendationsResource: Timer.Sample timerBRecommendationResource = Timer.start(...)
RecommendationsResource->>RecommendationsResource: request.getParameter(EXPERIMENT_NAME / INTERVAL_START_TIME / INTERVAL_END_TIME / JOB_ID)
RecommendationsResource->>RecommendationsResource: determine target using KruizeDeploymentInfo.local
RecommendationsResource->>RecommendationEngine: new RecommendationEngine(experimentName, intervalEndTimeStr, intervalStartTimeStr)
alt target == LOCAL
RecommendationsResource->>RecommendationEngine: validate_local()
else target == REMOTE
RecommendationsResource->>RecommendationEngine: validate()
end
alt validation succeeds
RecommendationsResource->>RecommendationEngine: prepareRecommendations(calCount, target, bulkJobID)
RecommendationEngine-->>RecommendationsResource: KruizeObject
alt kruizeObject.validation_data.success
RecommendationsResource->>RecommendationsResource: Utils.DateUtils.getTimeStampFrom(...)
RecommendationsResource->>HttpServletResponse: sendRecommendationsResponse(..., List.of(kruizeObject), ..., SC_CREATED)
else validation_data failure
RecommendationsResource->>HttpServletResponse: sendErrorResponse(..., kruizeObject.validation_data.errorCode, ...)
end
else validation fails
RecommendationsResource->>HttpServletResponse: sendErrorResponse(..., SC_BAD_REQUEST, errorMessage)
end
RecommendationsResource->>MetricsConfig: timerBRecomendationResource.tag(...).register(meterRegistry())
MetricsConfig-->>RecommendationsResource: timerRecomendationResource
RecommendationsResource->>MetricsConfig: timerBRecommendationResource.stop(timerRecomendationResource)
deactivate RecommendationsResource
RecommendationsResource-->>Client: HTTP 201/4xx with JSON body
File-Level Changes
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Contributor
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Hey - I've found 3 issues, and left some high level feedback:
- The new KRUIZE_RECOMMENDATION_API_VERSION.LATEST value uses "v1.0" while other version constants (e.g., CURRENT_LIST_RECOMMENDATIONS_VERSION/CURRENT_UPDATE_RECOMMENDATIONS_VERSION) use "v3.0" or non-
v-prefixed formats; consider aligning the version string format and retaining explicit version enum values if anything else relies on them. - The new recommendation metrics (timerRecomendationResource and timerBRecomendationResource) are declared but not shown being initialized like the other timers in MetricsConfig; ensure they are wired up consistently so the POST handler cannot hit a null builder or timer at runtime.
- The new RecommendationsResource class header lists copyright year 2026, which is in the future compared to the rest of the project; consider updating this to match the current year convention used elsewhere.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The new KRUIZE_RECOMMENDATION_API_VERSION.LATEST value uses "v1.0" while other version constants (e.g., CURRENT_LIST_RECOMMENDATIONS_VERSION/CURRENT_UPDATE_RECOMMENDATIONS_VERSION) use "v3.0" or non-`v`-prefixed formats; consider aligning the version string format and retaining explicit version enum values if anything else relies on them.
- The new recommendation metrics (timerRecomendationResource and timerBRecomendationResource) are declared but not shown being initialized like the other timers in MetricsConfig; ensure they are wired up consistently so the POST handler cannot hit a null builder or timer at runtime.
- The new RecommendationsResource class header lists copyright year 2026, which is in the future compared to the rest of the project; consider updating this to match the current year convention used elsewhere.
## Individual Comments
### Comment 1
<location path="src/main/java/com/autotune/analyzer/services/RecommendationsResource.java" line_range="91" />
<code_context>
+public class RecommendationsResource extends HttpServlet {
+ private static final long serialVersionUID = 1L;
+ private static final Logger LOGGER = LoggerFactory.getLogger(RecommendationsResource.class);
+ private static int requestCount = 0;
+
+ @Override
</code_context>
<issue_to_address>
**issue (bug_risk):** Static requestCount is not thread-safe in a multi-threaded servlet environment
Because servlet instances are shared across threads, `++requestCount` in `doPost` can race and produce incorrect counts under load. If you need this counter, make it thread‑safe (e.g., use `AtomicInteger.incrementAndGet()`), or remove it to avoid misleading metrics and data races.
</issue_to_address>
### Comment 2
<location path="src/main/java/com/autotune/analyzer/services/RecommendationsResource.java" line_range="343-345" />
<code_context>
+ for (KubernetesAPIObject kubernetesAPIObject : listRecommendationsAPIObject.getKubernetesObjects()) {
+
+ // Handle container recommendations
+ if (kubernetesAPIObject.getContainerAPIObjects() != null) {
+ for (ContainerAPIObject containerAPIObject : kubernetesAPIObject.getContainerAPIObjects()) {
+ ContainerRecommendations recommendations = containerAPIObject.getContainerRecommendations();
+ processRecommendations(recommendations.getData().values());
+ }
</code_context>
<issue_to_address>
**issue (bug_risk):** Missing null-check for container/namespace recommendations can lead to NPEs
In `sendRecommendationsResponse`, `containerAPIObject.getContainerRecommendations()` (and similarly `kubernetesAPIObject.getNamespaceAPIObject().getNamespaceRecommendations()`) are dereferenced without a null check. If recommendations are absent, `processRecommendations(recommendations.getData().values())` will throw. Please guard these calls (or treat missing recommendations as empty) before accessing `getData()`.
</issue_to_address>
### Comment 3
<location path="src/main/java/com/autotune/analyzer/services/RecommendationsResource.java" line_range="135-144" />
<code_context>
+ }
+
+ List<KruizeObject> kruizeObjectList = new ArrayList<>();
+ try {
+ if (null != experimentName) {
+ experimentName = experimentName.trim();
+ try {
+ if (rmTable) {
+ new ExperimentDBService().loadExperimentAndRecommendationsFromDBByName(mKruizeExperimentMap, experimentName);
+ } else {
+ new ExperimentDBService().loadLMExperimentAndRecommendationsFromDBByName(mKruizeExperimentMap, experimentName, bulkJobID);
+ }
+ } catch (Exception e) {
+ LOGGER.error("Loading saved experiment {} failed: {} ", experimentName, e.getMessage());
+ }
+
</code_context>
<issue_to_address>
**suggestion (bug_risk):** Database load failures are logged but reported back as "invalid experiment name" to the client
In the `experimentName != null` branch of `doGet`, if `loadExperimentAndRecommendationsFromDBByName` throws, we only log the exception and then fall through, so the client can still get `INVALID_EXPERIMENT_NAME`. This masks DB/infra failures as user input errors. Consider returning an appropriate 5xx response on DB load failure instead of continuing to the "invalid experiment name" path.
Suggested implementation:
```java
try {
if (rmTable) {
new ExperimentDBService().loadExperimentAndRecommendationsFromDBByName(mKruizeExperimentMap, experimentName);
} else {
new ExperimentDBService().loadLMExperimentAndRecommendationsFromDBByName(mKruizeExperimentMap, experimentName, bulkJobID);
}
} catch (Exception e) {
LOGGER.error("Loading saved experiment {} failed", experimentName, e);
// Database/infra failure – return 5xx instead of continuing to "invalid experiment name" handling
response.sendError(HttpServletResponse.SC_INTERNAL_SERVER_ERROR,
"Failed to load experiment from database. Please try again later.");
return;
}
```
1. Ensure this code is inside the `doGet` method that has a `HttpServletResponse response` parameter; if the parameter is named differently, update `response` accordingly.
2. Make sure `javax.servlet.http.HttpServletResponse` is imported in this file if it is not already.
3. If `doGet` currently declares `throws IOException`, no further changes are needed; otherwise either add `throws IOException` to the method signature or wrap `response.sendError(...)` in a try/catch that handles `IOException`.
4. If this resource is not a `HttpServlet` but uses a different response abstraction (e.g. JAX-RS `Response`), adapt the catch block to build and return an appropriate 5xx `Response` object instead of using `HttpServletResponse`.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
mbvreddy
changed the title
Contributor
There was a problem hiding this comment.
Hey - I've found 3 issues, and left some high level feedback:
- The static
requestCountfield inRecommendationsResourceis incremented without any synchronization, which can lead to race conditions under concurrent load; consider using anAtomicIntegeror avoiding a mutable static counter. - The
doPostJavadoc mentions selecting the target via a"target"query parameter, but the implementation derivestargetsolely fromKruizeDeploymentInfo.local; either wire in the query parameter or update the Javadoc to reflect the actual behavior. - For metrics consistency, the GET handler in
RecommendationsResourcecurrently uses the sharedtimerBListRecwhile POST uses the newtimerBRecomendationResource; consider using the new recommendation-specific timer for both methods or clearly separating metrics for legacy vs v1 endpoints.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The static `requestCount` field in `RecommendationsResource` is incremented without any synchronization, which can lead to race conditions under concurrent load; consider using an `AtomicInteger` or avoiding a mutable static counter.
- The `doPost` Javadoc mentions selecting the target via a `"target"` query parameter, but the implementation derives `target` solely from `KruizeDeploymentInfo.local`; either wire in the query parameter or update the Javadoc to reflect the actual behavior.
- For metrics consistency, the GET handler in `RecommendationsResource` currently uses the shared `timerBListRec` while POST uses the new `timerBRecomendationResource`; consider using the new recommendation-specific timer for both methods or clearly separating metrics for legacy vs v1 endpoints.
## Individual Comments
### Comment 1
<location path="src/main/java/com/autotune/utils/KruizeConstants.java" line_range="45" />
<code_context>
public static enum KRUIZE_RECOMMENDATION_API_VERSION {
- V1_0("1.0"),
- LATEST("1.0");
+ LATEST("v1.0");
private final String versionNumber;
</code_context>
<issue_to_address>
**issue (bug_risk):** Changing the enum values and removing `V1_0` may break callers and introduces a different version string format.
This change removes `V1_0("1.0")` and changes the remaining value to `LATEST("v1.0")`. That means:
1) Any code referencing `KRUIZE_RECOMMENDATION_API_VERSION.V1_0` will no longer compile.
2) The version string has changed from `"1.0"` to `"v1.0"`, while other APIs already use `"v2.0"` / `"v3.0"`. If any clients or comparisons rely on the old `"1.0"` value, this will be a breaking change.
Consider keeping `V1_0("1.0")` for compatibility and adding a new constant for the `v`-prefixed form, or verify and update all consumers before making this change.
</issue_to_address>
### Comment 2
<location path="src/main/java/com/autotune/utils/MetricsConfig.java" line_range="19-22" />
<code_context>
public class MetricsConfig {
- public static Timer timerListRec, timerListExp, timerCreateExp, timerUpdateResults, timerUpdateRecomendations;
+ public static Timer timerListRec, timerListExp, timerCreateExp, timerUpdateResults, timerUpdateRecomendations, timerRecomendationResource;
public static Timer timerLoadRecExpName, timerLoadResultsExpName, timerLoadExpName, timerLoadRecExpNameDate, timerLoadBulkJobId, timerUpdateBulkJobId, timerBoxPlots, timerUpdateExpDate;
public static Timer timerLoadAllRec, timerLoadAllExp, timerLoadAllResults;
</code_context>
<issue_to_address>
**nitpick (typo):** Consider correcting the spelling in the new timer names to avoid confusion and make metrics easier to query.
The new field `timerRecomendationResource` (and similarly named metrics) use `Recomendation` with one `m`, which is inconsistent with standard spelling and other concept names. If possible, please rename these to use `Recommendation` to keep metric identifiers consistent and easier to query.
Suggested implementation:
```java
public static Timer timerListRec, timerListExp, timerCreateExp, timerUpdateResults, timerUpdateRecommendations, timerRecommendationResource;
```
```java
public static Timer.Builder timerBListRec, timerBListExp, timerBCreateExp, timerBUpdateResults, timerBUpdateRecommendations, timerBUpdateExpDate, timerBRecommendationResource;
```
To fully apply this rename, you should:
1. Update all usages of `timerUpdateRecomendations` to `timerUpdateRecommendations` across the project (e.g., metric registration, timers, and any references where this field is used).
2. Update all usages of `timerRecomendationResource` to `timerRecommendationResource`.
3. Update all usages of `timerBRecomendationResource` to `timerBRecommendationResource`.
4. If the metric names are set via strings (e.g., `Timer.builder("...")` or with tags), ensure those string metric identifiers also use the corrected "recommendation" spelling to keep metrics consistent in your monitoring system.
</issue_to_address>
### Comment 3
<location path="src/main/java/com/autotune/analyzer/services/RecommendationsResource.java" line_range="91" />
<code_context>
+public class RecommendationsResource extends HttpServlet {
+ private static final long serialVersionUID = 1L;
+ private static final Logger LOGGER = LoggerFactory.getLogger(RecommendationsResource.class);
+ private static int requestCount = 0;
+
+ @Override
</code_context>
<issue_to_address>
**issue (bug_risk):** Using a plain static int for `requestCount` is not thread-safe in a servlet environment.
Because servlets are accessed by multiple threads, `++requestCount` in `doPost` is a racy update and can produce incorrect counts. If this counter is only loosely informative, consider removing it; otherwise use a thread-safe alternative like `AtomicInteger` or integrate it with your metrics system.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
Contributor
Author
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Please find below the API response with this change. GET kruize/api/v1/recommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl 'http://172.18.0.2:31900/kruize/api/v1/recommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:25:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:25:09.410Z",
"current": {
"replicas": 7,
"resources": {
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:25:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T02:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T20:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:25:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:25:09.410Z",
"current": {
"replicas": 5,
"resources": {
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T20:25:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T02:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T20:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v1.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]POST kruize/api/v1/recommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl -X POST 'http://172.18.0.2:31900/kruize/api/v1/recommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0&interval_end_time=2026-06-16T20:19:35.661Z'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:10:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:10:09.410Z",
"current": {
"replicas": 7,
"resources": {
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:10:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:10:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:10:09.410Z",
"current": {
"replicas": 5,
"resources": {
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T20:10:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v1.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]POST /updateRecommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl -X POST 'http://172.18.0.2:31900/updateRecommendations?experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0&interval_end_time=2026-06-16T20:19:35.661Z'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:10:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:10:09.410Z",
"current": {
"replicas": 7,
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:10:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:10:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:10:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:10:09.410Z",
"current": {
"replicas": 5,
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T20:10:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:10:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.75,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v3.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]GET /listRecommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl 'http://172.18.0.2:31900/listRecommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:25:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:25:09.410Z",
"current": {
"replicas": 7,
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:25:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T02:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T20:25:09.410Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "v1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:25:09.410Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:25:09.410Z",
"current": {
"replicas": 5,
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T20:25:09.410Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T02:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T20:25:09.410Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v3.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
] |
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
Contributor
Author
GET kruize/api/v1/recommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl 'http://172.18.0.2:31116/kruize/api/v1/recommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T21:03:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T21:03:19.866Z",
"current": {
"replicas": 7,
"resources": {
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T21:03:19.866Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T03:03:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T09:03:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T15:03:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T21:03:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T21:03:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T21:03:19.866Z",
"current": {
"replicas": 5,
"resources": {
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T21:03:19.866Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T03:03:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T09:03:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T15:03:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T21:03:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 25.0,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v1.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]POST kruize/api/v1/recommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl -X POST 'http://172.18.0.2:31116/kruize/api/v1/recommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0&interval_end_time=2026-06-16T20:19:35.661Z'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:18:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:18:19.866Z",
"current": {
"replicas": 7,
"resources": {
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:18:19.866Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:18:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:18:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:18:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:18:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
"median": 0.9299999999999999,
"q3": 0.9299999999999999,
"max": 0.9299999999999999,
"format": "cores"
},
"memoryUsage": {
"min": 28.357142857142858,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.25,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.25,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
},
{
"container_image_name": "kruize/tfb-db:1.15",
"container_name": "tfb-server-0",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:18:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:18:19.866Z",
"current": {
"replicas": 5,
"resources": {
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 5,
"min": 5,
"max": 5
}
},
"monitoring_start_time": "2026-06-15T20:18:19.866Z",
"recommendation_engines": {
"cost": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 5,
"confidence_level": 0.0,
"config": {
"resources": {
"requests": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 1.03,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
}
},
"variation": {
"resources": {
"requests": {
"cpu": {
"amount": -1.07,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": -0.47,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:18:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T08:18:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T14:18:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
},
"2026-06-16T02:18:19.866Z": {
"cpuUsage": {
"min": 0.3276923076923076,
"q1": 1.03,
"median": 1.03,
"q3": 1.03,
"max": 1.03,
"format": "cores"
},
"memoryUsage": {
"min": 50.6,
"q1": 198.5,
"median": 198.5,
"q3": 198.5,
"max": 198.5,
"format": "MiB"
}
}
}
}
},
"medium_term": {
"duration_in_hours": 24.25,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
},
"long_term": {
"duration_in_hours": 24.25,
"notifications": {
"120001": {
"type": "info",
"message": "There is not enough data available to generate a recommendation.",
"code": 120001
}
}
}
}
}
}
}
}
]
}
],
"version": "v1.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]POST /updateRecommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl -X POST 'http://172.18.0.2:31116/updateRecommendations?experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0&interval_end_time=2026-06-16T20:19:35.661Z'
[
{
"cluster_name": "cluster-one-division-bell",
"experiment_type": "container",
"kubernetes_objects": [
{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
"namespace": "default_0",
"containers": [
{
"container_image_name": "kruize/tfb-qrh:1.13.2.F_et17",
"container_name": "tfb-server-1",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:18:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:18:19.866Z",
"current": {
"replicas": 7,
"requests": {
"cpu": {
"amount": 1.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.5,
"format": "cores"
},
"memory": {
"amount": 100.0,
"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
"duration_in_hours": 24.0,
"notifications": {
"112101": {
"type": "info",
"message": "Cost Recommendations Available",
"code": 112101
},
"112102": {
"type": "info",
"message": "Performance Recommendations Available",
"code": 112102
},
"321001": {
"type": "notice",
"message": "Pod count is derived from CPU usage metric data",
"code": 321001
}
},
"metrics_info": {
"pod_count": {
"avg": 7,
"min": 7,
"max": 7
}
},
"monitoring_start_time": "2026-06-15T20:18:19.866Z",
"recommendation_engines": {
"cost": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
},
"performance": {
"pods_count": 7,
"confidence_level": 0.0,
"config": {
"requests": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.9299999999999999,
"format": "cores"
},
"memory": {
"amount": 238.2,
"format": "MiB"
}
}
},
"variation": {
"requests": {
"cpu": {
"amount": -0.17000000000000015,
"format": "cores"
},
"memory": {
"amount": 187.98999999999998,
"format": "MiB"
}
},
"limits": {
"cpu": {
"amount": 0.42999999999999994,
"format": "cores"
},
"memory": {
"amount": 138.2,
"format": "MiB"
}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
"2026-06-16T20:18:19.866Z": {
"cpuUsage": {
"min": 0.14,
"q1": 0.9299999999999999,
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},
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}
},
{
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"container_name": "tfb-server-0",
"recommendations": {
"version": "1.0",
"notifications": {
"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
"2026-06-16T20:18:19.866Z": {
"notifications": {
"111101": {
"type": "info",
"message": "Short Term Recommendations Available",
"code": 111101
}
},
"monitoring_end_time": "2026-06-16T20:18:19.866Z",
"current": {
"replicas": 5,
"requests": {
"cpu": {
"amount": 2.1,
"format": "cores"
},
"memory": {
"amount": 50.21,
"format": "MiB"
}
},
"limits": {
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},
"memory": {
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}
}
},
"recommendation_terms": {
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"notifications": {
"112101": {
"type": "info",
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"code": 112101
},
"112102": {
"type": "info",
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"code": 112102
},
"321001": {
"type": "notice",
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"code": 321001
}
},
"metrics_info": {
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},
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},
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},
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}
}
},
"notifications": {}
}
},
"plots": {
"datapoints": 4,
"plots_data": {
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"cpuUsage": {
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"q1": 1.03,
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},
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},
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},
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},
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}
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}
}
}
}
}
}
]
}
],
"version": "v3.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
]GET /listRecommendationsYour Hidden Content Here
root@kruize01:~/workarea/github/autotune/tests/scripts/remote_monitoring_tests/rest_apis# curl 'http://172.18.0.2:31116/listRecommendations?rm=true&experiment_name=quarkus-resteasy-kruize-min-http-response-time-db_0'
[
{
"cluster_name": "cluster-one-division-bell",
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{
"type": "deployment",
"name": "tfb-qrh-deployment_0",
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{
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"container_name": "tfb-server-1",
"recommendations": {
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"111000": {
"type": "info",
"message": "Recommendations Are Available",
"code": 111000
}
},
"data": {
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}
},
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},
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}
},
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},
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},
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}
},
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},
"memory": {
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"format": "MiB"
}
}
},
"recommendation_terms": {
"short_term": {
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"notifications": {
"112101": {
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"code": 112101
},
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},
"321001": {
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"code": 321001
}
},
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}
},
"monitoring_start_time": "2026-06-15T21:03:19.866Z",
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},
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},
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},
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},
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},
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}
}
]
}
],
"version": "v3.0",
"experiment_name": "quarkus-resteasy-kruize-min-http-response-time-db_0"
}
] |
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
khansaad
requested changes
Jun 17, 2026
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
Contributor
|
@mbvreddy Can you please address the two sourcery comments, they are critical |
Contributor
Author
|
ok @dinogun |
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
dinogun
reviewed
Jun 19, 2026
| for (ContainerAPIObject containerAPIObject : kubernetesAPIObject.getContainerAPIObjects()) { | ||
| ContainerRecommendations recommendations = containerAPIObject.getContainerRecommendations(); | ||
| if (recommendations != null) { | ||
| processRecommendations(recommendations.getData().values()); |
Contributor
There was a problem hiding this comment.
getData() can still be null for both getContainerRecommendations() and getNamespaceRecommendations(). Better would be to check
if (recommendations != null && recommendations.getData() != null) {
processRecommendations(recommendations.getData().values();
}
Signed-off-by: Bhaktavatsal Reddy <bhamaram@in.ibm.com>
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Description
Please describe the issue or feature and the summary of changes made to fix this.
Fixes # (issue)
Type of change
How has this been tested?
Please describe the tests that were run to verify your changes and steps to reproduce. Please specify any test configuration required.
Test Configuration
Checklist 🎯
Additional information
Include any additional information such as links, test results, screenshots here
Summary by Sourcery
Introduce a new v1 recommendations REST API endpoint and wire it into the analyzer, along with related metrics and versioning updates.
New Features:
Enhancements: