Operations | Monitoring | ITSM | DevOps | Cloud

Sometimes it may not be easy to debug Azure Functions deployed on Azure since we cannot do inline debug through the Azure Portal. An option for us is to write information to the Logs console in key parts of our code to get insights into what’s happening inside our Function. We can do that using the following sentence: Another option, especially if we are developing our Azure Functions inside Visual Studio, is to run the Function locally.

Earlier this year we released our report on the cost of cloud. Through this white paper we discovered the complexities of cloud costs for businesses and alternatives beyond the hyperscalers. This white paper saw 1,000 cloud developers surveyed about the management of their cloud services, and the degree of costs associated with it. From this analysis, we were able to come up with 5 key takeaways outlining the degree to which hyperscalers are overpromising and under-delivering.

Distributed caching is an important aspect of cloud based applications, be it for on-premises, public or hybrid cloud environments. It facilitates incremental scaling, allowing the cache to grow and incorporate the data growth. In this blog we will explore distributed caching on cloud and why it is useful for environments with high data volume and load.

As cloud technology has matured, hybrid and multi-cloud approaches have become commonplace. Enterprises have discovered that not all applications are suitable for the public cloud, meaning on-premise data centres are still active, and each public cloud has its own strengths and weaknesses, driving businesses to mix-and-match to suit their needs. This results in interoperability challenges for multi-cloud environments.

Enterprises today want real-time business insights to make decisions that improve operational efficiency and customer engagement and present newer revenue opportunities. However, the promise of the data-driven business falls short due to gaps in data management. These gaps exist because data in the modern enterprise doesn’t exist only behind firewalls and within organizational premises.

Organizations receive high monthly bills from cloud providers with no way of determining why the number changes from month to month or how to accurately predict future spend. More importantly, there is little information to provide visibility if cloud resources are being deployed efficiently or if spend is correlated to business performance.

Azure is the public cloud computing platform of Microsoft and it offers: Azure comprises more than 600 cloud services and supports varied operating systems, databases and developer tools. And the best part (in our opinion)? Splunk On-Call integrates with Microsoft Azure to help on-call teams improve incident response for Azure-based environments.

On the heels of several exciting developments about Splunk Cloud Platform announced at.conf22, I am excited to share today that Data Manager now supports onboarding of Microsoft Azure data sources, effective immediately.

Today I’m going to speak about another important Best practice, Tips, and Tricks that you need to know before you start to develop your Logic App solutions: Choose properly your developer tools.

In this blog post series, we will be comparing different services in AWS, GCP and Azure. We'll go into detail in each of the resources and understand the differences between providers, something you need to be aware if you are looking into switching clouds. Some examples will be given using Terraform, the Infrastructure as Code (IaC) market leader. If you want to know more about different IaC tools and how they compare, check our other blog post - Terraform vs Pulumi vs CloudFormation.