Python list comprehensions offer a concise method of interacting with each element of a list. Even though they’ve been available since Python 2.0, their syntax often demotivates people from using them. This article aims to introduce List Comprehensions in a friendly way and offer you one more Python feature to add to your scripting toolbox.
Two years ago, Pusher started building an internal Kubernetes based platform. As we transitioned from a single product to multiproduct company, we wanted to help our product teams spend less time worrying about shared concerns such as infrastructure and be able to focus more on writing business logic for our products. Over this period, our platform team have solved many of the problems that Kubernetes doesn’t solve out of the box. Until recently, we had not solved the problem of configuration.
Serverless applications require a whole new approach to development workflow. In this article, Lumigo Director of Engineering Efi Merdler-Kravitz details the guiding principles and tools used at a 100% serverless company to ensure the most efficient workflow possible. We are not going to talk about product development flow (no product managers were harmed during the making of this post!).
This week’s AWS Summit in New York was an exciting one for both AWS and PagerDuty. The AWS team rolled out Amazon EventBridge, a set of APIs for AWS CloudWatch Events that makes it easy for AWS SaaS partners to inject events for their customers to process in AWS. PagerDuty is excited to continue and deepen our long partnership with AWS by supporting EventBridge as a launch partner.
If you're running in the cloud and ever struggle to predict, report on, or attribute your cloud costs, you may want to consider a new kind of role: A Financial Cloud Operations Manager. While a traditional cloud operations manager may sit on the DevOps team or report to an engineering lead, a financial cloud ops manager’s reporting structure is slightly different.
I hear it all the time when talking to future BigPanda customers; “I’m not sure BigPanda can really help me correlate all these alerts together because our CMDB is very immature.” Or sometimes, they don’t even have a CMDB, and incorrectly assume this disqualifies them from meaningful noise reduction and alert correlation. I’m happy to tell you the same thing I tell the folks who are looking at BigPanda for the first time. “No CMDB? No problem!”.
If you happen to be running multiple clusters, each with a large number of services, you’ll find that it’s rather impractical to use static alerts, such as “number of pods < X” or “ingress requests > Y”, or to simply measure the number of HTTP errors. Values fluctuate for every region, data center, cluster, etc. It’s difficult to manually adjust alerts and, when not done properly, you either get way too many false-positives or you could miss a key event.
There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketers stepped in. Widespread overuse of the terms AI/ML in marketing have managed to thoroughly confuse the meanings of these words.
This is a companion post to a recent webinar with an OpsRamp partner, Flycast Partners. Check out the recorded webinar on YouTube and slides on SlideShare for the potential impacts of ITSM and ITOM silos and how a modern ITOM platform can help improve bi-directional collaboration and reduce mean-time-to-resolution.
