Operations | Monitoring | ITSM | DevOps | Cloud

Ever wondered what’s under the hood of your neighbors’ car, the situation in their wallet or the configuration of their serverless stack? Well wonder no more! Today we will bring you the statistics of Dashbird so you could compare your Lambda functions with others. Unfortunately, the car and the wallet thingy you should figure out on your own. Let’s start… (I hope you like charts)

Cloud environments are becoming increasingly complex, with applications and even infrastructures changing constantly. Despite their dynamic nature, these environments must be monitored constantly for teams to ensure the stability, security, and performance of workloads running in them. Tracking these infrastructure changes is one of the most important—and one of the most difficult—parts of maintaining a cloud environment.

I was recently called upon to secure an Nginx web server with HTTPS, and my goal was to set this up with a certificate obtained from AWS Certificate Manager. It took me a while to figure out how to get everything configured and working. Hopefully someone else who is attempting to do the same thing will read this and I can save you some time!

One of the great promises of serverless has always been that it would free developers to focus on writing code without having to give too much consideration to the underlying infrastructure. But the advantages presented by the instantly, infinitely scalable nature of serverless come with limitations and unique considerations that you need to take into account.

These days, a major part of most IT budgets is the cloud bill. But unlike server-bound infrastructure budgeting, cloud bills can be unpredictable and highly variable from month to month. However, if organizations embrace cloud cost optimization to regulate cloud bills and avoid surprises, they’ll find themselves with considerable found money that can be reinvested into other areas.

Monitoring an Azure environment can be a challenging task for even the most experienced and skilled team. Applications deployed on Azure are built on top of an architecture that is distributed and extremely dynamic. But all is not doom and gloom. Azure users have a variety of tools they can use to overcome the different challenges involved in monitoring their stack, helping them gain insight into the different components of their apps and troubleshoot issues when they occur.

If you are hosting your application with Heroku, and find yourself faced with an unexplained error in your live system. What would you do next? Perhaps you don’t have a dedicated DevOps team, so where would you start your investigation? With Scout APM of course! We are going to show you how you can use Scout to find out exactly where the problem lies within your application code.

A while back, I wrote about how you can shave latency off every AWS SDK operation by enabling HTTP keep-alive, like this. It had the desired effect and I saw lots of people apply this technique in their projects. But it also resulted in the same 10 lines of code being copied and pasted everywhere! I began thinking about ways to distribute an optimized version of AWS SDK so everyone can benefit.

The typical AWS bill, otherwise known as the AWS Cost and Usage Report, includes line items that are useful to both finance and DevOps. However, many of the metrics that are within engineers’ and cloud architects’ control aren’t so simple to discover. To make cost a first-class operational metric for DevOps, teams need visibility into the data that’s relevant to engineering activity.