Operations | Monitoring | ITSM | DevOps | Cloud

Founded by twin sisters in San Francisco well before the city became the focal point of tech, Benefit has been a refreshing and innovative answer to cosmetics customers for over 40 years. The company is a major player in this competitive industry, with a presence at over 2,000 counters in more than 30 countries and online. In recent years, Benefit has undergone a swift digital transformation, with a popular eCommerce site in addition to their brick-and-mortar stores.

The whole internet is abuzz over GitHub Actions, if by ‘whole internet’ you mean ‘the part of the internet that is obsessed with serverless ops’ and by ‘abuzz’ you mean ‘aware of‘. But Actions are a bit surprising! GitHub is a company that has famously focused on doing a single thing extremely well. As the ranks of developer-tooling SaaS companies swells by the day, you would think GitHub would have long ago joined the fray.

Applying consistent tags to your cloud resources can help improve the way you organize and manage your cloud environment. For example, tagging based on environment and application enables you to quickly identify all production resources supporting a specific application. Maybe you want to target automation processes at these resources or exclude them from a specific access role. Tags enable you to do that easily and manage your cloud environment in a way that makes sense for your business.

Last week, AWS announced a fantastic new feature for AWS CloudFormation, CloudFormation Drift Detection. Drift detection allows you to determine whether the AWS resources controlled by your CloudFormation stacks have drifted from their original configuration. This can happen if you manually adjust properties of your AWS resources. Today, we’re excited to announce a new action to report on your CloudFormation drifted stacks: CloudFormation Stack Drift Report.

To make serverless architectures more observable, we’re excited to introduce the new Cloud Functions view in Datadog. You can now search, filter, and explore all your AWS Lambda functions in one central view, and dive straight into detailed performance data that is scoped to a single function. The Cloud Functions view brings together Lambda metrics and logs with distributed request traces from your functions, which are now available in Datadog thanks to our new integration with AWS X-Ray.

With the increasing popularity and adoption of native cloud and serverless systems organizations are starting to demand that DevOps better understand - and manage - cloud costs. This shouldn’t come as a surprise.

We have a running joke at Stackery regarding our tiny little gong that’s used to mark the occasion when we get a new customer. And while I’m all about the sales team celebrating their successes (albeit with a far-too-small gong), I felt like the dev team needed its own way to commemorate major product releases and iterations.

I set out to find a credit mechanism or hard-coded limit in packets per second in AWS EC2. After all my findings set out in this series so far, I had one more test to perform around t2.unlimited. I wanted to see how “unlimited” it is and the difference it makes in packet throughput on capable instance types. This post is about my findings.