AWS

As more and more applications convert to cloud native with Kubernetes as a normalizing layer the ability to have portability between public clouds also becomes easier. Theoretically, the app can now move easily between AWS/Azure/GCP. However, a couple of issues are always in the back of developer’s minds:  Do I connect to cloud services like ML/AI, DevOps tool chains, DBs, Storage, etc? This might lock me in. Should I roll my own database or use a cloud services like CosmosDB, Azure Postgres DB, etc.

Deploying applications into the cloud is the norm. Majority of these applications are landing on AWS, GCP or Azure. In addition, more and more of these applications are also using containers and utilizing Kubernetes. Kubernetes is becoming more mainstream and the “mainstay” in many organizations. Adoption is growing, as are the number of options for Kubernetes and multiple methods to help build and manage them. There are many Kubernetes choices to deploy your containerized application:

Microservices and serverless give us as developers an incredible amount of freedom. We can choose our language and we can decide where and when to deploy our service. One of the biggest challenges, though, is figuring out how things go wrong and how to fix it.

Whether you're building apps or baking cheesecake, trusting the ingredients you work with and making sure you have a transparent process to get them into your final product is one of the most important things.

This blog walks through steps to build and secure Alexa Skills

There are many predictions from market analyst firms on the size of the global serverless architecture market and how fast it will grow. The numbers range from $18B to $21.99B in the next few years with the compound annual growth rate (CAGR) in the double digits. But is serverless only a fancy name for products like AWS Lambda and Azure Functions? What is serverless? When you build an app, everything you do generally breaks down into two large buckets.

As more and more applications convert to cloud native with Kubernetes as a normalizing layer the ability to have portability between public clouds also becomes easier. Theoretically, the app can now move easily between AWS/Azure/GCP. However, a couple of issues are always in the back of developer’s minds:  Do I connect to cloud services like ML/AI, DevOps tool chains, DBs, Storage, etc? This might lock me in.  Should I roll my own database or use a cloud services like CosmosDB, Azure Postgres DB, etc.

In this blog, I will walk you through the steps of setting up a Multi-Account log aggregation architecture in AWS

Are you using multiple AWS/Azure accounts and struggling with log management? This blog walks through advantages and tradeoffs of different ways to achieve this

News about data breaches, leaked customer information and stolen passwords for critical infrastructure are becoming very common. Many of these incidents seem to be related to mismanagement of credentials, unencrypted passwords, secrets being pushed to git repositories or secrets being hard coded within the application, leaving no room for rotation. This has led to increasing demand for Secrets Management tools like AWS Secrets Manager, HashiCorp Vault, Confidant and others. In this blog, we will look at