In the 21st century, it’s quite easy to manipulate machines and computers. Our worries are no longer if something is doable, but if something can be perfected. Therefore, we mostly search for new ideas and ways to make our work impeccable. For example, if you’re using a particular software and you realize that the software is excellent, but it could be better in some ways that would allow you to work even faster, you’ll explore the alternatives.

One of the most powerful aspects of AWS is their Identity and Access Management (IAM) service. The obvious aspect of its power is that it controls who can do what with all the resources inside your AWS account. But the non-obvious side is how configurable it is. You can encode permissions that are so finely grained that a Lambda Function could, for example, be given just enough permissions to be able to read one attribute from one record for the current user of a DynamoDB Table.

We recently released the Lumigo Dynamic Dashboard to help our customers visualize metrics to monitor their environment the way they want.

With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics.

Microservices and serverless are both important topics in the world of cloud-native computing. Yet, although serverless functions and microservices architectures often go hand-in-hand, they’re distinct technologies that fill different roles in modern software environments. Here’s an overview of what microservices and serverless are, how they relate to each other, how they are different, and why you may or may not wish to deploy a serverless microservice.

Cloud-native and serverless come hand in hand. One of the initial motivations to move business workflows to the cloud was related to cutting costs related to provisioning infrastructure and elasticity that on-demand allocation of resources is offering.

I’ve learned a lot about serverless in my first full year at Stackery after joining from the Ops-focused automation company, Puppet. I’ve learned how to deploy rich CMS-backed web applications in a serverless way, how to cast incantations using CloudFormation’s intrinsic functions, but most of all I’ve learned that there’s a lot to learn in order to be successful in AWS.