Synthetic monitoring is one holistic technique within the wide world of IT monitoring and application performance monitoring (APM) and it’s focused on web performance. Synthetic monitoring emulates the transaction paths between a client and application server and monitors what happens. The goal of synthetic monitoring is to understand how a real user might experience an app or website. In this article, let’s go deep with this topic.

How do you come to grips with all of the code engineers are committing, pushing, merging, and deploying within your organization? Have you started even looking at that data? If not, you’re missing out on a crucial source of productivity, security, and Software Development Life Cycle (SDLC) data. But how can you get a handle on all of that code-related activity?

The advent of the data mesh has changed the way organizations manage and utilize data. It’s not expected to go away anytime soon. Data mesh, in short, is a popular approach to data management in the enterprise. Its primary goal is to empower teams, especially cross-functional ones. In this article, we'll delve into what data mesh is and explore its key principles. We'll also discuss some benefits of implementing this modern data mesh approach in your organization.

You want your networks to operate seamlessly, but how can you guarantee that your network is performing optimally and without disruptions? Network monitoring can help. Network monitoring means overseeing a network's performance, availability, and overall functionality — allowing you to identify and resolve issues before they impact end-users. Read on for a full understanding.

One of the primary goals of any IT team is to ensure seamless operation and consistent uptime. This is typically achieved via monitoring — whether on-premises, in an application or across a network, monitoring allows teams to respond quickly to a given issue or even understand potential problems before they arise. For today’s complex distributed systems, one of the more common monitoring methods comes in the form of cloud monitoring.

Modern retail businesses need to deliver exceptional customer experiences that are not only fast and secure but also completely frictionless. Amazon Web Services (AWS) and Splunk have come together to provide a value proposition that goes beyond what either platform can offer independently.

Observability has been tied up with causality from its origins in the mathematical realm of control theory in the early 1960s. A system (of any kind, hardware or software, natural or engineered) was deemed to be ‘observable’ if it generated self-descriptive data from which it was possible to infer how states of the system were causally related to one another.

Observability continues to prove its worth. In The State of Observability 2023, the annual research report Splunk created in partnership with the Enterprise Strategy Group, we share the characteristics that set the observability leaders (those with a mature observability practice) apart from the rest.

The game in enterprise IT is this: delivering amazing services to your customers while also reducing costs. That means the time it takes to respond to an incident is critical. Incidents can ruin service delivery and destroy your budget. Certain incidents almost surely deliver a poor customer experience. Response times, you hear? Yep, we’re talking about MTTR, but that’s not all.