Real-time visibility into the customer journey and business-critical applications deliver significant strategic value. You need insight into your internal and external customers and their behaviors, as well as the health of your business-critical applications. That’s why application performance management (APM) is a critical element of any digital business strategy.
Although APM is naturally centered on technology and data, the most effective APM practices are adding concepts from design thinking and agile development to keep the focus on your customers’ and end users’ experiences. When you apply these five best practices for your digital enterprise’s APM strategy, you can keep pace with the digital revolution and ensure that you have flexible, scalable systems that drive meaningful change and deliver new insights to the business.
Trianz and AppDynamics are combining their industry-leading consulting services and application performance solutions. Their unique expertise and technology will help you prepare your organization for emerging technologies and better support the apps, systems and platforms already in place.
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Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
The Rise in Big Data Analytics According to Internet World Stats, global internet usage increased by 1,339.6% between 2000-2021. With nearly thirteen times as many people using the internet, this has resulted in a massive increase in the amount of data being processed daily. Our increased sharing and consumption of digital media also compounds this increased usage to create an enormous pool of data for big data analytics firms to process.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore