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APM

The latest News and Information on Application Performance Monitoring and related technologies.

The Business Case for OpenTelemetry - APM for Modern Applications

DevOps professionals know that ensuring optimal application performance is paramount. More and more customers and prospects interact with companies online, and any hiccup can impact your bottom line. What’s more, companies continue to leverage cloud-native apps for improved flexibility and resource optimization. All of which means that Application Performance Monitoring (APM) tools need to evolve.

eG Enterprise Monitoring Now Available on the IGEL App Portal

For several years, eG Innovations has been providing advanced AIOps-powered monitoring and observability to customers leveraging IGEL-powered devices in VDI and DaaS environments. Our out-of-the-box metric thresholds, alerting, dashboards, and reporting ensure IT teams can proactively avoid end-user support calls and tickets and ensure organizations get optimal performance from their IGEL investment. IGEL and eG Innovations recently announced the availability of eG Enterprise on the IGEL App Portal.

How to decide between cloud and on-premise monitoring

Application performance monitoring systems tend to be available in two modes: on-premise and cloud-based SaaS. Which is the “right” choice? Well, it depends on your situation, but overall cloud-based SaaS offerings have significant benefits when compared to on-premise. However, it’s not always so simple. The right selection depends on the facts on the ground.

Analyzing OpenTelemetry apps with Elastic AI Assistant and APM

OpenTelemetry is rapidly becoming the most expansive project within the Cloud Native Computing Foundation (CNCF), boasting as many commits as Kubernetes and garnering widespread support from customers. Numerous companies are adopting OpenTelemetry and integrating it into their applications. Elastic® offers detailed guides on implementing OpenTelemetry for applications. However, like many applications, pinpointing and resolving issues can be time-consuming.

RIP Xamarin: Adding .NET MAUI to Real User Monitoring

We’re constantly seeing frameworks evolving and churning, and in May 2024 we’ll see the end of Xamarin after 12 years. The deprecation of Xamarin means we need to ensure that MAUI is equipped with the tools and functionalities that developers have come to rely on Xamarin for. At Raygun, that’s Real User Monitoring (RUM).

APM Metrics: The Ultimate Guide

How your software applications perform is an extremely important factor in determining end-user satisfaction. APM metrics are the key indicators that help business-critical applications achieve peak performance. This article explains APM metrics, their importance, and the core APM metrics used by modern software systems to measure and optimize the performance of their applications.

Datadog on Data Science

In this episode we'll visit the world of predictive analytics and machine learning and uncover how these cutting-edge technologies are transforming the way Datadog monitors and improves its services. We’ll focus our conversation on two key aspects: using advanced statistical methods for proactive monitoring and the strategic implementation of machine learning for algorithm enhancement.

The Ultimate Guide to API Monitoring in 2024 - Metrics, Tools, and Proven Practices

According to Akamai, 83% of web traffic is through APIs. Microservices, servers, and clients constantly communicate to exchange information. Even the Google search you made to reach this article involved your browser client calling Google APIs. Given APIs govern the internet, businesses rely on them heavily. API health is directly proportional to business prosperity. This article covers everything about API monitoring, so your API infrastructure’s health is always in check ✅.

Apache Spark at Scale #datadog #shorts #security #observability

Datadog is an observability and security platform that ingests and processes tens of trillions of data points per day, coming from more than 22,000 customers. Processing that amount of data in a reasonable time stretches the limits of well known data engines like Apache Spark. In addition to scale, Datadog infrastructure is multi-cloud on Kubernetes and the data engineering platform is used by different engineering teams, so having a good set of abstractions to make running Spark jobs easier is critical.