Operations | Monitoring | ITSM | DevOps | Cloud

Serverless is a quickly-maturing technology and, if you’ve followed its evolution over the past several years, you’ve likely seen a host of great (and not-so-great) documentation of its technology and practices. Now that serverless is a much more mainstream topic for reputable outfits to report on, it’s become easier to comb through serverless fact and fiction in the media.

At Skeddly we’re focused on bringing you the best in AWS help tutorials, AWS scheduler services, and AWS backup services. However, from time to time we like to reach out to other leaders in the AWS space to help you, our blog readers, stay on top of the latest developments and news within the AWS ecosystem.

This blog focuses on implementing the Dependency Injection design pattern to the Azure Functions. For a better understanding of Dependency Injection and Azure Function, Let’s take a simple Cab booking validation scenario, in which there will be a Function app implemented with the Dependency Injection that validates the user email Id that is valid or not. Before diving into the orchestration, let us know what the Dependency Injection is.

In the second of our new series of posts, Yan Cui highlights the key insights from the Amazon Builders’ Library article, Using load shedding to avoid overload, by AWS Principal Engineer (AWS Lambda) David Yanacek.

The popularity of serverless infrastructure, like AWS Lambda, is on the rise, which is easy to understand, given its promise of a cheaper price tag and less maintenance. However, as companies are lifting and shifting apps into lambda, many are discovering that it’s not that simple. Like any shift, such as moving from on-prem to the cloud, the reality is, applications need to be designed a certain way in order for you to reap the cost and efficiency benefits.

In my previous post on new approaches to managing hybrid cloud environments, I discussed the issues that commonly arise for IT operations teams. While hybrid cloud gives IT great flexibility to design infrastructure that’s uniquely suitable to diverse business and user requirements, it also brings about more complexity. Hybrid and multi-cloud businesses generate significantly more IT event data and its coming from many more places now.

Cloud migration is more than just a buzzword. According to several reports released at the beginning of 2019, almost 70% of enterprise organizations are moving their applications and infrastructure from local, self-managed hardware to one of the big cloud providers. Multiple case studies have been written about companies like Spotify, Dropbox, Gitlab, and Waze, all of which have replaced their core business infrastructures with cloud data centers.

Would you like to detect problems in your Amazon Redshift environments? Does your team need a high-level overview of what monitoring options they can choose from when they deploy Redshift nodes and clusters? First, we’ll start with one of the most important components of any monitoring strategy: performance and availability monitoring. Then, we’ll continue with monitoring Redshift configuration changes and how to meet compliance requirements with Redshift.

This blog will brief on Azure Logic App Triggers. Let us see a short introduction of what a Logic App is and how does it work before getting deep into Logic App Triggers.

Serverless can bring opportunities by making DevOps more accessible to folks new to the industry. It can also bring opportunities to folks already in the industry that want to spend more time focusing on adding business value. But many technologists, seasoned or otherwise, hear a lot about serverless but don’t always know how to get started.