Operations | Monitoring | ITSM | DevOps | Cloud

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.

Microsoft Azure has long proven it’s a force to consider in the world of cloud computing. Over the past year, Azure has made some significant steps in bridging the gap with AWS by offering new services and capabilities as well as competitive pricing.

So a while back I got an email from our finance team. I was tasked to assist with tagging resources in our AWS infrastructure and investigate which items are contributing to certain costs. I don’t know about other engineers, but these kinds of tasks are on the same realm of fun as … wiping bird poop off your windshield at a gas station. So I did the sanest thing I could think of.

DevOps, Observability, Continuous Delivery, Test in Production, Chaos Engineering, and Software Ownership are all major themes in software development today, but why? In an ideal world, we get everything right the first time, nothing breaks, no one DDOS’ us, and the weather report is “Cloudy With A Chance of Meatballs.” Reality of course is different – and better, to be honest.

This post is going to be a tad different and longer than what you are used to but I promise, it’s going to be an interesting one. We are going to build a serverless React + GraphQL Web app with Aws amplify and AppSync.

With AWS Lambda, we get scalability and resilience out-of-the-box. What’s more, AWS also provides built-in monitoring, logging and tracing support through CloudWatch and X-Ray. These built-in tools provide a good starting point but many developers eventually outgrow them as their serverless application becomes more complex. In this post, let’s take a serverless application and see how Dashbird can help you debug a serverless application.

Even in this field of work, not everything can be perfected 100%. There are always some situations and cases that will force you to go back or even remain in the present spot, despite your wish to keep going forward at your own pace. In this article, we’ll talk about the cold start impact on latency. What is it? How to fight against it? Is there a successful way of avoiding it or not?

The high-level steps for implementing chaos experiments involve: defining your application’s steady state, hypothesizing the steady state in both the control and experimental groups, injecting realistic failures, observing the results, and making changes to your code base/infrastructure as necessary based off of the results.

Since the beginning of Dashbird, we’ve been conducting user interviews with all the users that take the time to jump on a call with us. One of the most common requests we get is the ability to customise alerts - specifically, what failures you will get notified upon and the ability to set custom alert based on metrics. Today we announce a new part of Dashbird that takes care of that - an incident management platform.