A reliable digital customer experience is critical to the success of digital-first businesses. Each minute of downtime can result in the loss of revenue, unsatisfied customers, and damage to reputation. However, as your uptime gets closer to 100%, it gets exponentially harder to improve and often comes at the cost of speed of innovation. A good balance between innovation (i.e., new feature releases) and maintaining an acceptable level of reliability is key to success in the digital world.

Microsoft Teams is the world-leading collaboration and productivity tool for today’s hybrid workforce, but your users’ experience with it is only as good as the network and IT environment it operates in. There is a critical visibility gap when it comes to delivering a stellar Microsoft Teams user experience to your users. Organizations lack an end-to-end picture of what problems are happening, what is causing the problems and who is affected.

One of the critical differences between distributed tracing and business activity monitoring is that distributed tracing usually assumes that your transaction executes from start to end in a reasonably short time. An example would be that your call to an API might then drop a message on a queue which a function processes and loads into a database.

Most classical, batch-oriented machine learning systems follow the paradigm of “fit and apply”. In an earlier blog post, I discussed a few patterns on how to better organize data pipelines and machine learning workflows in Splunk. In this blog, we’ll review how you can organize your machine learning model in a new way: online learning.

Almost every organization is going through digital transformation. According to IDC, direct digital transformation investment is growing globally at a compound annual growth rate of 15.5% and is expected to approach $6.8 trillion by 2023. Customers quickly embrace the benefits of a customer experience reshaped by technology. However, they have little patience when that technology doesn’t work as expected.

One of the key advantages of cloud services versus on premise deployments is the wide range of purchasing options and pricing models. While it’s an attractive advantage, it can be complicated for organizations to determine the best blend of service pricing models. The ability to define the organization’s blend of purchasing strategies and display the target versus actual performance is critical for optimizing cloud cost management efforts.

Migrating to a cloud-based phone system is compelling because it eliminates the costs and time associated with deploying and managing legacy phone system/PBX hardware and proprietary business phones. However, moving 100% of an organization’s communications infrastructure off-site can present new challenges. If the connection to the cloud is lost, a site could lose both external communications and intra-site communications.

Curious about Microsoft Azure and the best ways to connect? Azure is a hybrid Cloud Service Provider (CSP) with customized, scalable, cloud-based packages. These encompass Software as a Service (SaaS), based on subscription-based software licensing and delivery, Platform as a Service (PaaS), allowing companies to develop, deploy, manage, and update applications, and Infrastructure as a Service (IaaS), providing high-level application programming interfaces (APIs).

Monitoring the digital experience of users is a must-have these days. Ensuring the end clients are satisfied is difficult though. People are not keen to provide feedback; they just change the vendor without explanation. It is, therefore, crucial to build enough observability into a front-end application (a web page or a mobile UI) so it can tell the story of how well the user perceived the interaction within the application.