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Distributed Tracing with MuleSoft APIs using OpenTelemetry

Distributed tracing enhances observability by providing detailed insights into the performance, behavior, and dependencies of your distributed system. It empowers you to proactively identify and resolve issues, optimize performance, and deliver a reliable and high-performing application.

What is Chronograf?

InfluxDB is an open-source time-series database, i.e. a database optimized for storing data points collected across an interval of time. Developed by InfluxData, InfluxDB is intended for fast, high-availability storage and retrieval of many different system metrics. The entire InfluxDB project, which is housed at influxdata.com, includes: Yet with all of these tools for collecting and processing time-series data, there's still one step missing—visualizing it. That's where Chronograf comes in.

MTTR vs. MTBF vs. MTTF: Understanding Failure Metrics

In the dynamic landscape of software and web applications, failures can have severe consequences, impacting user experience, business continuity, and overall performance. To proactively address these challenges, organizations rely on robust monitoring practices supported by failure metrics. Failure metrics, specifically tailored to software and web application monitoring, provide crucial insights into system health, reliability, and optimization opportunities.

10 Essential Distributed Tracing Best Practices for Microservices

If you are a SaaS provider making an application that deals with, say, a health registry or some personal information of the public, you realize how crucial it is to maintain their confidentiality. It is these situations that demand a previous encryption of data followed by a prompt tracing mechanism that finds out the faults right at the moment or prior to its occurrence. And what better way to keep track of your application than tracing?

ServiceNow is a Visionary in the Gartner Magic Quadrant for Application Performance Monitoring and Observability

I’m thrilled to announce that ServiceNow has been recognized as a Visionary in the 2023 Gartner® Magic Quadrant™ for Application Performance Monitoring (APM) and Observability. We believe this validates our strong vision and unique ability to help customers bring unified telemetry into their existing ServiceNow® Event Management and Service Operations solutions, reduce mean time to resolution (MTTR), and accelerate innovation.

Sentry vs Datadog - Detailed Comparison

Datadog and Sentry are two popular tools used for application performance monitoring and observability. Sentry is a dedicated error tracking and performance monitoring service, while Datadog is a comprehensive monitoring platform that unifies logs, metrics and traces. While there are similarities in their capabilities, there are also important differences that organizations should consider when deciding which tool to use.

Better Understanding the Top-3 Challenges Facing MSPs Today

Having spent time with hundreds of different MSPs from around the world since starting our Business Transformation Program, we see that there are really three areas where MSPs are facing challenges today: This list in itself probably isn’t going to be news to anyone, but I think the way these topics are talked about within the N-able Business Transformation Program is a little different.

Monitor the past, present, and future of your Kubernetes resource utilization

Greetings, Kubernetes Time Lords! Through a series of recent updates to our multi-purpose Kubernetes Monitoring solution in Grafana Cloud, we’ve made it easier than ever to assess your resource utilization, whether you’re looking at yesterday, today, or tomorrow. All companies that use Kubernetes, regardless of size, should monitor their available resource utilization. If a fleet is under-provisioned, the performance and availability of applications and services are at serious risk.

What are Azure Functions?

Serverless computing, also known as Functions as a Service (FaaS), has taken the world of cloud computing by storm. A game-changer in its own right, serverless computing has completely transformed the way developers approach and design their applications by abstracting the underlying infrastructure layer. But what makes it a powerful paradigm shift?