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Refactoring Applications for Cloud Migration: What, When, And How

Refactor your legacy applications to make use of the cloud

Enterprises migrating their applications to the cloud often face difficulty in choosing the right cloud migration approach that is line with their business goals and constraints. Here are a bunch of questions that can help you with this:

  • What are your business goals?
  • What are your application capacities?
  • What is the estimated cost for your cloud migration process?

Answering these questions, and then selecting the best suitable cloud migration path, will guarantee the long-term success of your enterprise with the migration approach you choose.

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How to Design an Optimal Microservice Architecture

Learn how to design an optimal microservice architecture.

Microservices architecture is being fast adopted by enterprises to create flexible, scalable applications that can be iterated fast, with high fault tolerance and low downtimes. How do you build the right microservices architecture?

While the exact architecture will vary, there are certain best practices that help design effective and optimal microservices architecture.

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Choosing the Right Cloud Migration Approach

A guide to packing up and migrating to the cloud.

In recent times, almost every company has become a technology company out of necessity. The fear of being left out, and giving an advantage to their competitors, has led them to adopt ways to become flexible, scalable and innovative.

One such means is by migrating to the cloud. With about 2.5x quintillion new bytes of data being generated every day, it is only reasonable that the companies adapt to a solution that is comparatively speedy, less costly, and not limited to an on-premise infrastructure.

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Data Lake vs Data Warehouse: Do You Need Both?

Most enterprises today have a data warehouse in place that is accessed by a variety of BI tools to aid in the decision-making process. These have been in use for several decades now and have served enterprise data requirements quite well. 

However, as the volume and types of data being collected expand, there’s also a lot more that can be done with that data. Most of these are use cases that an enterprise might not even have identified yet, and they won’t be able to do that until they have had a chance to actually play around with the data. 

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How to Set Up a Data Lake Architecture With AWS

Before we get down to the brass tacks, it’s helpful to quickly list out what the specific benefits we want an ideal data lake to deliver. These would be:

  • The ability to collect any form of data, from anywhere within an enterprise’s numerous data sources and silos. From revenue numbers to social media streams, and anything in between.
  • Reduce the effort needed to analyze or process the same data set for different purposes by different applications.
  • Keep the whole operation cost efficient, with the ability to scale up storage and compute capacities as required, and independent of each other.

And with those requirements in mind, let’s see how to set up a data lake with AWS

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4 Advantages to Building Cloud-Native Applications With AWS

The State of Cloud-Native Security Report 2018 states that 62% of enterprises today choose to go for cloud-native applications for more than half of their new applications. And this number is set to grow by 80% over the next three years. This is no surprise given the fact that most organizations are already heavily invested in their chosen cloud platform, and would like to use it up to its full potential.

Cloud-native applications are essentially those created specifically for the cloud and designed to leverage the gamut of resources available on the cloud. Being "cloud-native" means that an application has a vast operational landscape, capable of being available from wherever the cloud is instead of being tied down to a physical location. 

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Using Machine Learning to Remotely Log Asset Performance

For global manufacturing enterprises or other industries that rely on automated machinery across locations, the ability to keep tabs on asset performance becomes crucial. While manual supervision has worked well in such scenarios, there is a definite opportunity to optimize costs here. That's by enabling virtual monitoring and logging of asset performance data. 

Our team recently built a solution for this use case using machine learning solutions from AWS. It was designed to remotely capture video on machine performance and create logs of when the asset/machine was in operation and for how long. 

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The Basics of Voice Search Optimization

Search is changing, and so is the way consumers choose to engage with businesses local or global. There is a distinct move away from screens and keyboards and into voice-based interactions. Voice-search is becoming a fast-growing habit across consumer segments and fundamentally transforming how people and businesses transact on the internet.

Voice Search Is Picking up Pace

Consider this: