Microservices For Scalable and Maintainable Data Pipelines in The Cloud




Wissen Team


July 2, 2024

A sluggish global economy may put a dent in tech spending by enterprises worldwide. But, even in times of uncertainty, businesses cannot miss out on IT investments that can drive growth significantly. What they need to focus on is to pick out technologies that offer measurable business value as ROI. 

In this context, one area that should be on your radar is technology that helps you uncover better value from enterprise data. Surveys with top leaders of Fortune 1000 businesses point out that 91.9% of respondents have seen measurable business value generated from their investments in data technologies.

Data is the fuel that powers the modern digital economy. Enterprises must be equipped to handle millions or even billions of data points across multiple business systems simultaneously in their operational landscape. In other words, they must embrace a highly scalable data infrastructure to handle dynamic workload spikes effectively all through the year. Traditional data pipeline architecture may not support such flexibility. The best option would be to build your organization’s data assets on the cloud. Hence enterprises need to look at modern approaches like microservices to create and maintain their data pipelines seamlessly in the cloud.

Microservice Approach for Data Pipelines

With the microservice approach, enterprises can design their data pipelines as a service that has independent existence, scalable resource adoption capabilities, and granular deployment abilities.

Such a scalable architecture can help in improving the data pipeline’s performance, reliability, and flexibility. Such features are critical to ensuring a responsive data infrastructure for modern digital experiences that your consumers leverage from the business. The diversity of data that a business handles today is also a major factor that draws attention to the microservices approach. Modern business systems may have to handle transactional data, real-time unstructured data, datasets with deep granular subcomponents, and much more. Building your data pipeline as a cloud service with microservice architecture ensures that it can be configured and optimized in multiple ways to cater to different demands for data processing.

Roadmap for a Data Pipeline with Microservices

Now that you know how a microservice architecture works with a data pipeline, let us explore the most feasible roadmap for your business to build a data pipeline that can scale effortlessly:

  • Identify Data Sources

Before going into the depths of microservice implementations, enterprises must first be aware of what kinds of data they will be dealing with. For example, an eCommerce website must manage transactional data, a ride-sharing app may have to deal with geospatial data for optimal routing, a music or movie streaming service will have to deal with large data pieces needing extra storage capacity, etc.

Getting a clear picture of the data landscape in your digital services will help in planning the right modular service architecture to handle different requirements.

  • Build Modular Data Services

Once the right number of data sources are identified, the next step will be to build your business data pipeline as a collection of independent services. Each service can be configured to handle specific data processes like storage, ingestion, or analytical processing.

This modular approach will help in the easy maintenance and scalability of your data assets over time in alignment with business growth. Different data processing tasks can be distributed across different groups or clusters of data services as well. They can collaboratively process and handle large data streams and provide bi-directional data control to different business systems. This will also help in achieving horizontal scale within your data initiatives.

  • Focus on Proactive Monitoring

Your business's data pipeline needs proactive monitoring to prevent any performance, reliability, and security failure. By using multiple monitoring, logging, and alerting tools and methods, each microservice of your data pipeline should be constantly supervised for any suspicious behavior.

In the event of an anomaly or drop in performance, the respective administration team should be immediately informed about the incident and remedial measures should be deployed quickly. This will help in minimizing downtime and prevent any security risks for different data pipeline services.

  • Do Autonomous Resource Provisioning

Adding to the proactive monitoring requirements, it is also important to equip your data pipeline with dynamic resource allocation to meet demand. The resource could be storage, computing power, load balancers, etc.

An intelligent data pipeline should be created with autonomous resource provisioning to ensure your business can continue catering to rapidly changing customer expectations across digital channels.

The bottom line

Going the microservice way for cloud data pipelines offers enterprises a host of benefits when building their digital ecosystem. From on-demand scalability without limits to improved performance and reliability, enterprises can truly unlock the full potential of their modern digital channels with a powerful microservice architecture for their data pipeline. However, the road to achieving success is not an easy one.

Enterprises need the right guidance, roadmaps, strategies, and technologies to ensure that their experiments with a microservice-based data pipeline guarantee ROI. This is where a technology partner like Wissen can help make a huge difference. Get in touch with us to know more.