Operations | Monitoring | ITSM | DevOps | Cloud

It’s the celebration time of the year! Dashbird is now an official Amazon Web Services (AWS) Advanced Technology Partner (APN). Our team has demonstrated that we can build a strong, secure and reliable AWS-based business that can benefit Amazon Web Services users. The new partner status is recognition of Dashbird ability to help companies to better monitor and troubleshoot their Lambdas by providing state of the art solution for serverless observability.

Today we’ll talk more about the cost tracking for serverless architecture. Following the cost of serverless architecture utilization it might give you insights on how and what should you change or adapt to, to be able to reduce the cost. After all, we’re all always trying to improve our performances in every field while keeping the costs to a minimum (if possible).

With Azure Virtual Machine (VM) Scale Sets you can automatically scale the number of VMs running an application based on the compute resources required. VM Scale Sets make it easier to deploy and manage a large number of Virtual Machines consistently and allow you to use and pay for the minimum resources needed at any given time, but they also introduce a few monitoring challenges.

When we talk about cloud providers, we often forget that not all data is the same — even in the same application, while we might think of this data as from a “financial application” or a “computation process”, the reality is that each data set has subsets upon subsets, and thus require specific applications to manage them.

Gatsby is currently generating a ton of buzz as the new hot thing for generating static sites. This has lead to a number of frequent questions like: A static…what now? How is GraphQL involved? Do I need to set up a GraphQL server? What if I’m not a great React developer, really more of a bad React developer?

I’ve been working on creating AWS Cognito User Pools in CloudFormation, and thought this would be a good time to share some of what I’ve learned.