Operations | Monitoring | ITSM | DevOps | Cloud

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.

In the first article in our new series, Yan Cui highlights the key insights from the Amazon Builders’ Library article, Timeouts, retries and backoff with jitter, by AWS Senior Principal Engineer Marc Brooker.

There are scenarios where we want to de-couple logic across multiple logic apps. Generally, this is a straight forward endeavor, unless the downstream logic app has a long-running process. When this does occur, the client (or publisher) will experience an HTTP timeout if the request takes more than 2 minutes. This scenario is captured within the Azure Logic Apps documentation.