Application Performance Monitoring (APM) is a technology approach that provides real-time information about how your software applications are performing. With a comprehensive view into application health and availability, APM can do things like: Both the importance and the usage of APM has grown in recent years. That’s because companies rely on increasingly complex applications to run their businesses. Here is what you need to know about Application Performance Monitoring.

Whether you're a small business or a large enterprise, working with data consumes time and effort. But what if there was a way to turn this data into opportunities for growth? That’s what DataOps offers. DataOps helps create a collaborative environment to improve data quality by automating manual processes. Research shows the market for DataOps platforms will grow from USD 3.9 billion in 2023 to USD 10.9 billion by 2028. This growth shows how steadily organizations will streamline their operations.

The famous phrase “Houston, we’ve had a problem” isn’t a one off event for space missions or Tom Hanks — its a regular occurrence for most IT teams! Today’s IT teams are peppered with alerts indicating that something has gone amiss in their production environments. Visibility of uptime and performance is an essential part of ensuring that your IT infrastructure can power applications to meet business needs and deliver value for users.

At the end of last year, I wrote about using Splunk to monitor the Know Your Customer (KYC) use case that is a regulation in most Financial Services Institutions in many countries. The last part of the regulation states that continuous monitoring of your customers in terms of their interactions and transactions needs to take place.

Splunk Cloud Platform has always been a powerful platform for aggregating, analyzing, and extracting actionable insights from your machine-generated data. As data volumes continue to grow exponentially, efficiently managing the ingestion of data into Splunk becomes crucial. To address this need, we are thrilled to announce the debut of Terraform support for the Splunk Cloud Platform.

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.

If you were one of the thousands of Splunk customers who joined us this year at.conf23, you heard our CEO Gary Steele say that Splunk's mission is to help you be digitally resilient. (And don't worry if you couldn't join us, because you can catch the keynote replays.) But what is digital resilience and how do you attain it?

In our service-driven world, businesses must provide the best user experience possible. Great service helps you retain long-term customers while also growing your customer base — to keep tabs on service performance, a few key metrics and signals come into play.

Adaptive thresholding is a key capability in Splunk IT Service Intelligence (ITSI) that enables customers to dynamically monitor the status of their key performance indicators (KPIs) and derive meaningful service insights and alerts.