Scalability of Kubernetes Running Over AWS - A Performance Study while deploying CPU intensive application containers

Background: Nowadays lot of companies are enjoying the benefits of kubernetes by maintaining their containerized applications over it. AWS is one of the leading cloud computing service providers and many well-known companies are their clients. Many researches have been conducted on kubernetes, docker containers, cloud computing platforms but a confusion exists on how to deploy the applications in Kubernetes. A research gap about the impact created by CPU limits and requests while deploying the Kubernetes application can be found. So, through this thesis I want to analyze the performance of the CPU intensive containerized application. It will help many companies avoid the confusion while deploying their applications over kubernetes. Objectives: We measure the scalability of kubernetes under CPU intensive containerized application running over AWS and we can study the impact created by changing CPU limits and requests while deploying the application in Kubernetes. Methods: we choose a blend of literature study and experimentation as methods to conduct the research. Results and Conclusion: From the experiments it is evident that the application performs better when we allocate more CPU limits and less CPU requests when compared to equal CPU requests and CPU limits in the deployment file. CPU metrics collected from SAR and Kubernetes metrics server are similar. It is better to allocate pods with more CPU limits and CPU requests than with equal CPU requests and CPU limits for better performance. Keywords: Kubernetes, CPU intensive containerized application, AWS, Stress-ng

Scalability of Kubernetes Running Over AWS - A Performance Study while deploying CPU intensive application containers

Background: Nowadays lot of companies are enjoying the benefits of kubernetes by maintaining their containerized applications over it. AWS is one of the leading cloud computing service providers and many well-known companies are their clients. Many researches have been conducted on kubernetes, docker containers, cloud computing platforms but a confusion exists on how to deploy the applications in Kubernetes. A research gap about the impact created by CPU limits and requests while deploying the Kubernetes application can be found. So, through this thesis I want to analyze the performance of the CPU intensive containerized application. It will help many companies avoid the confusion while deploying their applications over kubernetes. Objectives: We measure the scalability of kubernetes under CPU intensive containerized application running over AWS and we can study the impact created by changing CPU limits and requests while deploying the application in Kubernetes. Methods: we choose a blend of literature study and experimentation as methods to conduct the research. Results and Conclusion: From the experiments it is evident that the application performs better when we allocate more CPU limits and less CPU requests when compared to equal CPU requests and CPU limits in the deployment file. CPU metrics collected from SAR and Kubernetes metrics server are similar. It is better to allocate pods with more CPU limits and CPU requests than with equal CPU requests and CPU limits for better performance. Keywords: Kubernetes, CPU intensive containerized application, AWS, Stress-ng

Body Dysmorphic Disorder Insights in an Inpatient Psychiatric Setting

Body dysmorphic disorder is a chronic disorder involving imagined or partial appearance defects that lead to significant impairment in everyday life. It is quite prevalent but remains a clinically underdiagnosed psychiatric condition especially in the inpatient psychiatric setting. Onset of body dysmorphic disorder typically begins in adolescence with subclinical symptoms. Over time, symptoms progress to patients meeting the full Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) criteria. Severe cases of the body dysmorphic disorder are often camouflaged by concurrent diseases like major depressive disorder, obsessive-compulsive disorder, substance use disorder, and social anxiety disorder. Further, compounding the complexity of body dysmorphic disorder is a treatment of patients who present with coinciding suicidal ideations. Here, we present a unique case of a 40-year-old female admitted to an inpatient psychiatric unit for treatment of ongoing depression and suicidal symptoms. Early on in her inpatient course, she had symptoms of obsessive-compulsive disorder, social anxiety disorder, and alcohol use disorder. The constellation of symptoms prompted evaluation for body dysmorphic disorder and subsequent targeted treatment. This case report highlights the complexities associated with diagnosing body dysmorphic disorder, the importance of considering it a branch point for other psychiatric conditions, and the treatment for patients who present with coinciding suicidal behavior

Predictive factors indicating comorbid psychotic disorders among hospitalized individuals with encephalitis.

Predictive factors indicating comorbid psychotic disorders among hospitalized individuals with encephalitis.</p

Variations in demographic characteristics, comorbid conditions, and clinical outcomes among hospitalized individuals with encephalitis with comorbid psychotic disorders.

Variations in demographic characteristics, comorbid conditions, and clinical outcomes among hospitalized individuals with encephalitis with comorbid psychotic disorders.</p