Operations | Monitoring | ITSM | DevOps | Cloud

Custom resources are critical components in Kubernetes production environments. They enable users to tailor Kubernetes resources to their specific applications or infrastructure needs, automate processes through operators, simplify the management of complex applications, and integrate with non-native applications such as Kafka and Elasticsearch.

Understanding Splunk pricing is crucial for organizations evaluating SIEM solutions. This guide examines licensing models, actual costs, and essential pricing factors to help you make an informed investment decision for your security and monitoring needs.

Last9’s Telemetry Warehouse now supports Logs and Traces, offering a unified view for high cardinality observability to simplify monitoring and troubleshooting.

Generative AI (GenAI) is still in its infancy, but its impact is already being felt across industries. Over the past year, production applications leveraging GenAI have gone from proof-of-concept to delivering real-world value. According to the World Economic Forum, 75% of surveyed companies plan to adopt AI technologies by 2027. Leading cloud providers like AWS are making significant investments.

I’ve heard this story many times from production engineers: ‘We use tools like Datadog and NewRelic, but to keep costs from skyrocketing, we’re only monitoring our most critical services. We’re storing just 10% of our logs and traces and only the metrics we consider essential. It’s a frustrating situation. Engineers want full visibility across their systems, but cloud storage costs make it impossible to monitor everything.

In today's rapidly evolving technology landscape, Application Performance Monitoring (APM) has become a critical component for DevOps teams striving to maintain high-performing, reliable applications. This comprehensive guide explores everything modern DevOps teams need to know about implementing and optimizing their APM strategy.

If you are moving in the observability circles, chances are that you have heard the phrase “Observability 2.0,” which refers to how we need a new approach to observability. I am incredibly excited about the energy and discussion around a shift to “Observability 2.0,” as we now have a second chance to develop observability the way it was originally envisioned.