June | 2020
Imagine you are the IT manager responsible for managing your customer’s on-demand video service. The application has module for purchasing various subscriptions, authentication, content catalogs, user data and the content files. Users may use a multitude of devices to access this content from anywhere in the world once the authentication is established. The application uses the standard three-tier architecture that has been running fine in IaaS mode on cloud. A recent event that led to a sudden spike in demand for VOD services has made the customer rethink the whole application architecture. The application designers propose a true cloud-native architecture with components that utilize Platform-as-a-Service (PaaS) in public cloud. The customer likes the idea since it gives them the opportunity to add rich features to their application, enhance the user experience by providing custom recommendations enabled by analytics, and align their capacity and spend with the demand. The proposed architecture will have services like Containers, API gateway, NoSQL DB’s, Cognito, Lambda functions, RDS, Mobile Analytics, SQS, SNS and Elasticache. You still have to manage the service, however, instead of well-established server-centric parameters, you now have event logs, file data and process information to create a map of your application health.
This is now a common problem service providers face when customers opt for application transformation in serverless and microservices architectures. The distributed, message-driven and loosely coupled application architecture of cloud services means the way we look at service management needs to move beyond the server-centric approach.
How is cloud monitoring different
The cloud-native transformation of an application could enable it to scale from few container or Lambda instances to few thousand and back within a short time, generate data that is a mix of structured and unstructured, and provide customers the power to use true pay-per-use model. The platform services themselves are highly available and data backed up in multiple places by default, so the up/down status monitoring or traditional redundant architecture is not required. For the IT manager, this poses problems of choosing which services and parameters to monitor, which tools to use, how to bring it all together in a unified application view and, measurement and charging for services delivered. Some of the challenges in implementing this approach are:
Service operations need to make some fundamental changes in the approach to provide the true and integrated picture of the entire IT estate. This requires rethink of our traditional ideas of application architecture and the functional value of each of its components.
Service model for the future
The traditional service delivery model needs to change to reflect the new reality of on-demand and fluctuating consumption, spread over multiple independent services. The changes required are not limited to a new set of shiny tools the managers should acquire, rather, cover the entire service management lifecycle.
People: The composition and skillset of the operations team needs to reflect the blurring boundaries between application and infrastructure in the Infrastructure-as-a-code (IaaC) world by
Tools: The arsenal of tools needs to expand to cover services beyond servers and storage. Some examples are
Pricing: Aligning the service delivery price with the service consumption is perhaps the biggest challenge for the service providers. While the underlying management tool cost can be managed since these work on volume of data generated and processed, the resource deployment cannot move linearly up or down with the service consumption.
The services landscape in the cloud especially around PaaS, is still evolving. The rapid pace of innovation and launch of new services makes it even more complicated to track, evaluate and integrate the management methods into the existing operations framework. To stay ahead, we need to bring the learnings of CI/CD model into our operations framework to quickly adapt our service offerings and delivery model in line with the market demand.
References
https://Stackify.com/monitoring-microservices-a-5-step-guide
https://thenewstack.io/the-hows-whys-and-whats-of-monitoring-microservices/
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