Amazon Web Services (AWS) is a comprehensive cloud computing platform, providing an array of services to manage a business’s data infrastructure to help it grow and expand. With the wide range of services provided, it has multiple options to provide you with an elastic approach to optimize your costs. However, many users struggle with controlling their expenditure due to a variety of factors. Getting a complete understanding of how to reduce your AWS operational costs may be a daunting task.

Developers at Airbnb, BBC, Netflix, and Nike all share something in common: They’re using serverless computing to ship new products and features faster than ever. And they represent a growing trend. As businesses compete to quickly deliver customer value, a whopping 60% of enterprises have already adopted, or are planning to use, serverless architectures.

Share When it comes to serverless applications, their distributed nature of exponential scalability and use of potentially thousands of resources automatically begs the need for observability. Using the mass data output of an application to understand and optimize the internal states is a game-changing strategy, but only if used well. Dashbird Atlas takes serverless observability to a new level, reducing excessive noise through simple visualization of your application.

Azure storage has provided companies with a way to store almost limitless amount of data. But just like kids in a candy store this can get out of hand, and expensive. Being able to store as much data as you want is great, however it is something that can grow to a point where you are spending more on storage than you actually need.

Over the past 15 years, application architectures have evolved dramatically, from bare metal servers to virtualization technology, to elastic compute, auto scaling and containers. Recently, we’ve seen another shift to the serverless paradigm, where even the operating system is abstracted from developers and ops teams. Customers want fully-managed compute, but still want to use their existing application development tools and pipelines.

Cloud Manager allows NetApp users to manage, monitor, automate and optimize their data storage in the public cloud as well as in hybrid environments.

Enterprises have relied on public cloud providers to shift and transform their legacy workloads using hyperscale infrastructure, but it is vital to ensure that business-critical services are running optimally. Cloud events help developers and operators understand how their workloads hosted on different cloud services are performing at any given time.

Not that system monitoring has much to do with NY Fashion Week or the most avant-garde venues in London’s Soho, but they share the yearning for something new, something fruitful and original. And since we are also some kind of modern hipsters obsessed with everything cool and trendy, today we will try to review some of those new trends in monitoring, the most recent news that affect our field.

A few weeks ago, my good friend Josh Cook wrote a blog post for Power Automate about getting the error message when implementing the try/catch pattern with a Flow. We discussed if this could be used with Logic Apps, and Josh confirmed that it could, even though the Logic App documentation doesn’t cover it very well. Josh’s original Flow post is- Grabbing an error message from a failed run.

Companies are facing major difficulties as a result of the challenges posed by COVID-19, and many professionals cite automation as a key solution to business survival. However, when considering using automation to transform your service management, you need to consider how you leverage Cherwell Service Requests in partnership with automation to achieve the “holy grail” of service request automation.