The determination of the optimal resource setup for IRS involves assessing various factors such as workload, scalability, and availability to ensure efficient, reliable, and cost-effective performance. This effort will help balance the resources in a way that meets both operational and budgetary constraints.
What's the benefit?
Optimizing the resource setup will improve the overall performance of the IRS product, ensuring better response times, reliability, and scalability while also reducing unnecessary resource consumption and costs. It allows the system to handle peak loads efficiently and minimizes the risk of downtime.
What are the Risks/Dependencies ?
Risk of resource misconfiguration, which could lead to performance bottlenecks or under-utilized systems.
Detailed explanation
The optimal resource setup for IRS requires an in-depth analysis of the current resource allocation and usage patterns. The current configuration may not be fully optimized for peak performance, which could lead to inefficiencies or higher operational costs. The new setup should take into account factors such as the number of cores, memory allocation, storage needs, and the ability to scale resources based on demand. Thread pooling, database optimization, and the usage of a managed, scalable database instance are critical factors that need adjustment to improve performance and reliability.
Current implementation
Currently, IRS uses a default resource setup that has not been thoroughly optimized for workload variability or scalability. The existing database setup may not be fully optimized for high-demand scenarios, and the thread pool configurations may not efficiently handle peak loads.
Proposed improvements
The improvements proposed include identifying and documenting the optimal number of cores, memory, and storage for IRS , along with configuring thread pools to handle concurrent tasks more efficiently. Additionally, database settings will be tuned for performance under defined workloads, and IRS will shift to a managed, scalable database instance to better handle variable loads and ensure availability.
Feature Team
Contributor
Cofinity-X @rogocof
Cofinity-X @mkanal
Committer
@ds-jhartmann
@ds-mwesener
@ds-lcapellino
User Stories
As a team,
I want to determine the optimal resource setup for the IRS application,
So that the application performs efficiently, reliably, and cost-effectively, taking into account various factors such as workload, scalability, availability, and budget constraints.
Acceptance Criteria
[ ] Optimal resource setup for irs is known (cores, memory, storage requirements) including documentation and proof why we use this setup
[ ] Optimal Thread Pooling and thread pool configurations
[ ] Database settings are optimized for defines scenario
[ ]IRS uses a managed scalable database instance
Test Cases
Test Case 1
Verify that the IRS application is running with the optimal resource setup in terms of CPU cores, memory, and storage.
Steps
Deploy IRS with the defined optimal resource setup (e.g., number of cores, memory, storage).
Simulate various workload scenarios, including peak and low usage periods.
Monitor system performance and resource utilization during each scenario.
Expected Result
IRS performs efficiently without resource overutilization or underutilization.
Response times remain within acceptable limits across different workloads.
No resource exhaustion (e.g., CPU or memory) occurs during peak loads, and resource consumption scales down appropriately during low usage.
Test Case 2
Verify that the thread pooling configuration efficiently handles concurrent requests and scales based on the workload.
Steps
Configure thread pools as per the proposed optimal settings.
Simulate multiple concurrent API requests with varying load levels (light, moderate, heavy).
Monitor system performance and response times.
Expected Result
IRS handles concurrent requests efficiently without delays or performance degradation.
Thread pooling dynamically adjusts to accommodate varying request volumes, preventing thread starvation or overflow.
Resource usage (CPU and memory) remains within optimal limits during heavy loads.
Architectural Relevance
The following items are ensured (answer: yes) after this issue is implemented:
[ ] This feature aligns with our current architectural guidelines
[ ] The impact on the overall system architecture has been assessed. The Feature does not require changes to the architecture or any existing standard? Please take a look here on the overarching architecture
[ ] Potential risks or conflicts with existing architecture has been assessed
Justification:(Fill this out, if at least one of the checkboxes above cannot be ticked. Contact the Architecture Management Committee to get an approval for the justification)
Additional information
[x] I am aware that my request may not be developed if no developer can be found for it. I'll try to contribute a developer (bring your own developer)
Overview
Explain the topic in 2 sentences
The determination of the optimal resource setup for IRS involves assessing various factors such as workload, scalability, and availability to ensure efficient, reliable, and cost-effective performance. This effort will help balance the resources in a way that meets both operational and budgetary constraints.
What's the benefit?
Optimizing the resource setup will improve the overall performance of the IRS product, ensuring better response times, reliability, and scalability while also reducing unnecessary resource consumption and costs. It allows the system to handle peak loads efficiently and minimizes the risk of downtime.
What are the Risks/Dependencies ?
Risk of resource misconfiguration, which could lead to performance bottlenecks or under-utilized systems.
Detailed explanation
The optimal resource setup for IRS requires an in-depth analysis of the current resource allocation and usage patterns. The current configuration may not be fully optimized for peak performance, which could lead to inefficiencies or higher operational costs. The new setup should take into account factors such as the number of cores, memory allocation, storage needs, and the ability to scale resources based on demand. Thread pooling, database optimization, and the usage of a managed, scalable database instance are critical factors that need adjustment to improve performance and reliability.
Current implementation
Currently, IRS uses a default resource setup that has not been thoroughly optimized for workload variability or scalability. The existing database setup may not be fully optimized for high-demand scenarios, and the thread pool configurations may not efficiently handle peak loads.
Proposed improvements
The improvements proposed include identifying and documenting the optimal number of cores, memory, and storage for IRS , along with configuring thread pools to handle concurrent tasks more efficiently. Additionally, database settings will be tuned for performance under defined workloads, and IRS will shift to a managed, scalable database instance to better handle variable loads and ensure availability.
Feature Team
Contributor
Committer
User Stories
As a team, I want to determine the optimal resource setup for the IRS application, So that the application performs efficiently, reliably, and cost-effectively, taking into account various factors such as workload, scalability, availability, and budget constraints.
Acceptance Criteria
Test Cases
Test Case 1
Verify that the IRS application is running with the optimal resource setup in terms of CPU cores, memory, and storage.
Steps
Expected Result
Test Case 2
Verify that the thread pooling configuration efficiently handles concurrent requests and scales based on the workload.
Steps
Expected Result
Architectural Relevance
The following items are ensured (answer: yes) after this issue is implemented:
Justification: (Fill this out, if at least one of the checkboxes above cannot be ticked. Contact the Architecture Management Committee to get an approval for the justification)
Additional information