Operations | Monitoring | ITSM | DevOps | Cloud

Want to know what actually goes on under the platform and behind the screens at Dashbird? We recently sat down for a Q&A with our CTO, Marek Tihkan, on leading and managing an engineering team. Today, we speak to Alex, one of the engineers on the Development team and the brain and elbow grease behind our newly launched Dashbird Atlas real-time 3D map of your entire serverless environment.

A key metric for measuring how well you handle system outages is the Mean Time To Recovery or MTTR. It’s basically the time it takes you to restore the system to working conditions. The shorter the MTTR, the faster problems are resolved and the less impact your users would experience and hopefully the more likely they will continue to use your product! And the first step to resolve any problem is to know that you have a problem.

We’ve noticed interesting threads floating around the internet asking how would you explain serverless to a toddler. As it happens, we just turned three years old and to mark the occasion, we decided to take up the challenge and wrote a bedtime story, for serverless enthusiasts of all ages, about how serverless came to be, from the very beginning. It is a magical tale of the ingenious, life-changing journey that got us to a new universe called Serverless.

This blog explains a peculiar issue faced when Azure Durable Functions are deployed using Azure DevOps. In case you need to know what Azure Durable Functions are, please refer to Microsoft’s documentation on Durable Functions here as the explanation of it, is not under the scope of this blog. Durable functions work best when built with versions .NET Core 2.2 and above. After developing and testing a durable function, it can be deployed to Azure in many ways.

Some time ago, an ex-colleague of mine at DAZN received an alert through PagerDuty. There was a spike in error rate for one of the Lambda functions his team looks after. He jumped onto the AWS console right away and confirmed that there was indeed a problem. The next logical step was to check the logs to see what the problem was. But he found nothing. And so began an hour-long ghost hunt to find clues as to what was failing and why there were no error messages.

Stackery is focused on helping developers leverage the power of AWS managed services. Our secure delivery platform is used to ship Lambda functions, HTTP Gateways, Aurora database clusters, and many more services which you can view usage of in Anna’s blog on the topic. Recently, I noticed an emerging workload running on our platform: the JAMstack. That’s a term for web applications composed primarily of JavaScript, APIs, and Markup.

Another year of empowering DevOps teams has passed and what a year it’s been! I’d like to take a moment to reflect on the journey, the milestones and challenges this past year encompassed. The last year has been our most transformational to date. We’ve had a huge amount of ups and downs and I’m incredibly proud to say that we got through it and our organization is more resilient, more aligned in our vision and closer as a result.

We’re pleased and honored to be part of the Serverless revolution - continuously innovating to make processes and day-to-day tasks for serverless users more efficient, seamless and enjoyable. So let’s get right into the new and exciting stuff now! Earlier this year, Dashbird launched the very well-received Insights Engine designed to encourage a proactive approach when building and operating serverless applications.

Step Functions is a managed service by AWS that implements the Finite-state Machine (FSM) model. You coordinate multiple AWS services into serverless workflows so you can build and update apps quickly. Using Step Functions, you can design and run workflows that stitch together services such as AWS Lambda and Amazon ECS into feature-rich applications. You can read Wikipedia’s definition of a Finite-state Machine, but I think you’ll like the next section more. Keep on reading.