NEW RESULTS
😃: An anomaly with a Median Absolute Deviation (MAD) score of 59.30408874022408 has been detected in the ""petInfo_AWS::DynamoDB::Table"" service’s ""requests_Sum"" metric. This service is a critical component of a pet adoption website’s microservices architecture..
Context:
Anomaly Details: MAD score of 59.30408874022408 in "petInfo_AWS::DynamoDB::Table" and service’s "requests_Sum" metric".
Service Importance: Vital for the website’s functionality.
Dependencies and Dependents Information:
Dependencies= None
Dependents= lambdastatusupdater_AWS::Lambda::Function, PetSearch_AWS::ECS::Fargate
Historcal Anomalies MetaData:
You can use the data from historical data to support your analysis based on the following information:{'IssueNumber': '1_22', 'Max_MAD_Score': 53.11618139045689, 'Metric_With_Max_MAD': 'requests_Sum', 'availability_Average': 100.0, 'availability_Average_MAD': 0.0, 'issue_injected': 'no_issue', 'latency_Average': 0.0340240156670034, 'latency_Average_MAD': 0.0504440811103686, 'latency_p50': 0.3548909627170117, 'latency_p50_MAD': 0.0, 'latency_p90': 0.0727247518121378, 'latency_p90_MAD': 0.0, 'latency_p95': 0.8533875161073359, 'latency_p95_MAD': 0.27226089016488986, 'latency_p99': 0.7295842821019255, 'latency_p99_MAD': 0.5376792085055938, 'microservice': 'petInfo_AWS::DynamoDB::Table', 'path': 'lambda_step_priceLessThan55 -> Evidently_AWS::Evidently', 'requests_Sum': 933.5199472257414, 'requests_Sum_MAD': 53.11618139045689, 'timestamp': '2023-04-18 21:32:00'}. In historical data there is path information of dependencies and dependents which can be used to support your analysis.
Objective:
Identify Root Cause Node:
Evaluate each dependency's role and potential issues contributing to the anomaly.
Analyze provided metrics for insights.
Pinpoint 'Primary Target Node':
Determine the most affected dependent service or declare "petInfo_AWS::DynamoDB::Table" itself if no significant impact is found.
Outcome:
Provide a Extensive analysis identifying on the following:
- Singular Root Cause Node: The specific dependency or dependent causing the anomaly.
- Primary Target Node: The node most impacted by the anomaly, or confirm "petInfo_AWS::DynamoDB::Table" if it is the root cause.
Your analysis will guide subsequent investigation and mitigation efforts.
🤖: To begin the analysis process, we first examine the given details regarding the recently identified anomaly within the "petInfo_AWS::DynamoDB::Table" service. We observe that this particular service includes a metric called "requests_Sum," which is responsible for recording the total number of requests processed over time. This specific metric shows an unusually high MAD score, specifically 59.30408874022408, indicating the presence of an outlier or disruption compared to previous norms. As this service plays a vital role in supporting the functionalities of a pet adoption website, addressing such an anomaly becomes crucial.
Next, we explore the dependencies and dependents related to the "petInfo_AWS::DynamoDB::Table" service. According to the available information, there are two dependents associated with this service - namely, "lambdastatusupdater_AWS::Lambda::Function" and "PetSearch_AWS::ECS::Fargate." Given the absence of any direct dependencies, we must concentrate our efforts on understanding how these two dependents might affect the parent service or contribute to the observed anomaly.
In order to gain deeper insights into this issue, let us consider the historical anomalies metadata provided. Here, we find several relevant metrics pertaining to past incidents. For example, we learn about the maximum MAD score achieved by the "requests_Sum" metric under issue number '1_22,' recorded as 53.11618139045689. Furthermore, we discover average values for various metrics like availability, latency (at percentiles p50, p90, p95, p99), and corresponding MAD scores. These pieces of information serve as valuable benchmarks for gauging the severity and unusual nature of the current anomaly.
One essential aspect highlighted in the context involves the path information of dependencies and dependents. By examining the path details ('lambda_step_priceLessThan55 -> Evidently_AWS::Evidently'), we attempt to discern possible points of failure or influence leading to the present disruption. Although not explicitly mentioned, it is reasonable to assume that one or both of the dependents ("lambdastatusupdater_AWS::Lambda::Function" and "PetSearch_AWS::ECS::Fargate") may follow a similar route in their operational chain, thereby potentially affecting the performance of "petInfo_AWS::DynamoDB::Table."
After thorough examination, we conclude that the root cause of the detected anomaly lies within one or more components among the listed dependents - either individually or jointly contributing to the observed spike in the "requests_Sum" metric's MAD score. While further analysis would be required to isolate the exact culprit(s), the fact remains that these dependents form integral parts of the overall ecosystem surrounding "petInfo_AWS::DynamoDB::Table." Any dysfunction in their respective operations could indirectly lead to the reported abnormal behavior.
Regarding the primary target node, our initial assessment suggests that "petInfo_AWS::DynamoDB::Table" itself experiences the highest degree of impact due to the anomaly. No other significantly affected dependent services have been indicated thus far. Consequently, we propose that future investigative and corrective measures should primarily focus on rectifying the underlying issues plaguing the specified service rather than seeking another dependent entity as the primary source of trouble.
To summarize, our extensive analysis identifies multiple dependencies closely linked to the "petInfo_AWS::DynamoDB::Table" service, which seems to be its own primary target node in this case, experiencing the brunt of the anomaly. To effectively address and resolve the ongoing issue, immediate attention towards examining the operational aspects of the dependents - "lambdastatusupdater_AWS::Lambda::Function" and "PetSearch_AWS::ECS::Fargate" - along with the internal processes of "petInfo_AWS::DynamoDB::Table" itself becomes paramount. Implementing targeted monitoring, performing detailed logs analysis, and conducting controlled experiments can help uncover the precise origins of the anomaly while ensuring timely recovery and restoration of normalcy to the system.