This case study delves into AIM Consulting’s recent work with a leading provider of bioscience models to implement a rapid cloud optimization solution to address issues in their Azure production environment.
This solution would prove valuable for other organizations that have recently started their cloud journey but are struggling to gain insights and visibility into their cloud environment or maximize value from their investment.
Case Study Contents:
- Challenge: Instability in Organization’s Azure Cloud
- Approach: Assessment to Identify Cloud Instability Solutions
- Process: Re-Engineering, Dashboard Development
- Results: Stability Fixes, Efficiency Gains in Cloud
What AIM Consulting did:
- Cloud services strategy
- Application performance profiling and analysis
- Application performance optimization
- Python code optimization
- Real-time monitoring for application components
- Team enablement
Technologies implemented for the client:
- Microsoft Azure
- Azure VMs
- Azure Service Bus
- Azure Container Instances
- Azure Postgres
- Azure Monitor
- Azure Monitor Agent
- Kusto Query Language (KQL)
Challenge: Instability in Organization’s Azure Cloud
A leading provider of bioscience models for use in drug discovery and life science research relied heavily on their Azure cloud platform to support the complex computational needs of their scientific research.
However, their platform was not meeting the organization’s needs and was becoming increasingly unstable, and critical issue alert capabilities were not in place. The issues were occurring most frequently in their production environment so any infrastructural changes (compute, service bus, caching) or additional monitoring agents needed to be monitored and rolled back quickly if adverse impacts were detected.
To address these issues, the organization partnered with AIM Consulting, a leading provider of cloud solutions and services.
Our experts at AIM worked closely with the client’s team to understand their unique needs and challenges, with the goal of identifying and resolving cloud systems-based instability triggers while providing deeper insights into the cloud systems’ health through Azure Monitor and alerting on identified issues.
Approach: Assessment to Identify Cloud Instability Solutions
Our experts conducted a thorough assessment of the organization’s Azure Cloud Architecture including service and asset inventory. This thorough evaluation enabled our team to identify areas for improvement and potential solutions.
Leveraging the results of the initial assessment, we worked with the organization to implement a more robust and scalable monitoring solution. This included a new dashboard, updated alerts, improved log analytics, compute platform changes, and implementation artifacts (including source code, configuration and/or templates).
Another key aspect of the project was providing greater insight into the performance and issues of their Azure environment. We provided advice on which compute platforms fit the specific use cases being addressed.
Process: Re-Engineering, Dashboard Development
Our experts performed an initial Azure component inventory and configuration, which led to a key finding that the organization could save 50-70% of their compute spend by correcting some less-than-optimal provisioning and licensing in their infrastructure.
We also recommended Project Roadmap approaches on how to effectively move from a monolithic architecture to an Event-Driven Architecture.
In addition to that re-engineering, we developed an architectural diagram of the organization’s systems and integrations. We also provided directions on how to set up and maintain systems and application monitoring tools within Azure.
Our consultants worked with project stakeholders to develop a dashboard that provides real-time plus analytical data to investigate stability issues.
As yet another instrumental piece of the process, our experts conducted knowledge transfer to the Azure infrastructure team, ensuring they were equipped with the necessary skills and capabilities to sustain the change to the organization’s cloud.
Results: Stability Fixes, Efficiency Gains in Cloud
The partnership between the bioscience research models provider and AIM Consulting proved to be a great success. The improvements made to the Azure platform significantly improved the stability and performance of the organization’s research operations.
In addition to the stability fixes and efficiency gains, new alerts were put in place to let the client know when issues were occurring in their environment so that the team could react swiftly and get ahead of the problem.
The team now has better stability in their main application, as well as a path forward for making future infrastructure decisions. The solution gives the organization’s team peace of mind and allows them to focus on their research without worrying about the stability of their platform.
The results of this case study illustrate how a knowledgeable cloud solutions provider can help a company improve and stabilize its cloud platform, ensuring it better supports its business needs.
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