Scalable monitoring and alerting solution based on fully-managed cloud-native services.
Customer profile
Customer is one of the global leaders in locomotives for both freight and passenger applications worldwide.
The Challenge
As the customer moved their applications to the cloud, they faced operational challenges with monitoring their applications and platforms for availability, performance, and compliance. To address their exact requirements, the customer is looking to develop a cost effective, scalable monitoring and alerting solution based on fully-managed cloud-native services.
The Solution
We started off the engagement with an end-to-end architecture using cloud-native services that’s fully managed and works seamlessly with existing cloud services. We helped build a few core reusable design patterns using cloud managed services that can be applied in a self-service model to scale efficiently across the enterprise. We also leveraged serverless architectures to a great degree thereby maximizing cost efficiency and significantly reducing operational overhead. This resulted in a scalable monitoring and alerting solution based on fully-managed cloud-native services.
The Solution
We started off the engagement with an end-to-end architecture using cloud-native services that’s fully managed and works seamlessly with existing cloud services. We helped build a few core reusable design patterns using cloud managed services that can be applied in a self-service model to scale efficiently across the enterprise. We also leveraged serverless architectures to a great degree thereby maximizing cost efficiency and significantly reducing operational overhead. This resulted in a scalable monitoring and alerting solution based on fully-managed cloud-native services.
No items found.
More success stories
Analytics
Data Analytics
Startups
Generative AI
AI
Squid AI
Applying Generative AI to Transform Product Analytics using Natural Language
.svg)
.svg)
.svg)
