As OpenTelemetry rises in popularity, more organizations are implementing, or planning to implement, the open source project to monitor their applications — and, meanwhile, more vendors are offering OpenTelemetry support. In fact, a quick Google search for “OpenTelemetry support” shows results ranging from legacy APM vendors to newer, cloud native solutions like Grafana Cloud.

Every business is a software business. And by software, we don’t mean code—we mean running software serving customers in production. Those customers may be internal to the company, they may pay you money, or they may represent attention that increases ad revenue—either way, making them happy is your business. And your fast, reliable software makes them happy. Application performance monitoring, also known as APM, represents the difference between code and running software.

The rapid growth of 5G technology and expanse of the Telecoms industry has created the need for these organizations to implement effective data-driven decisions, to enable the future profitability of their companies. This raises the challenge of analyzing data from various sources across complex networks to derive insights and ultimately decision making.

Choosing an OpenTelemetry backend depends on several factors, such as your monitoring and observability requirements, current infrastructure, scalability needs, and budget constraints.

We're delighted to introduce our new Ingest API Keys, a significant step toward enabling all Honeycomb customers to manage their observability complexity simply, efficiently, and securely. Ingest Keys are currently available for Environment & Services customers, with Classic support and programmatic key management capabilities under development and coming soon!

In my role here at Splunk, I get the opportunity to speak to a number of our customers about the challenges they are facing in building and running these complex platforms that power today’s environments. And what’s more, is that the challenges are more or less the same.

Deploying Kubernetes in production environments at scale is a common enterprise challenge. Learn how Cisco and Spectro Cloud ease deployment and management of Kubernetes clusters in the cloud, bare metal and virtualized data center, and at the edge.

Data-centric AI is the new frontier in AI, where the models themselves now remain stationary while tools, techniques and engineering practices improve data quality. As Andrew Ng puts it, “Data-centric AI is the discipline of systematically engineering data to build an AI system.”

One of the major trends in software development in the last decade has been “shifting left” responsibilities that have traditionally been under operation’s domain to earlier in the software development life cycle (SDLC). It first came in the form of DevOps where a lot of the software engineering best practices were introduced to the deploy, operate, monitor phases. Such examples include continuous integration and continuous deployment (CI/CD) and Infrastructure as Code (IaC).

Many companies are using cloud technologies to become more agile, scalable, and cost-effective during their digital transformation. However, this change brings new challenges in maintaining the security and performance of applications and infrastructure in the cloud. Security and observability go hand-in-hand.