Operations | Monitoring | ITSM | DevOps | Cloud

Datadog is a powerful observability platform. However, unlocking it’s full potential while managing costs necessitates more than just utilizing its platform, no matter how powerful it may be. It requires a strategic approach to data management. Enter telemetry pipelines, a key to elevating your Datadog experience. Telemetry pipelines offer a toolkit to achieve the essential steps for maximizing the value of your observability investment. The Mezmo Telemetry Pipeline is a great example of such.

Microsoft Teams call quality issues can stem from a lot of places. People often jump to blame Microsoft when they’re having a call or video breakup. But, the reality is that while this does happen, more often than not it’s an external factor to the Microsoft service itself. To give you some insight into where your Teams problems come from we put together this easy primer on the five most common sources of Teams call quality issues.

Microsoft Teams has become a popular platform for remote communication and collaboration, especially since the outbreak of the COVID-19 pandemic. As more and more businesses rely on Microsoft Teams to communicate and work together, it’s crucial to ensure that the platform is performing optimally and to measure and improve Microsoft Teams performance. Fortunately, there are free tools available to help you monitor the performance of Microsoft Teams.

Prometheus is an open source and free to use metrics collection and storage solution. It's used extensively in the industry for monitoring many different technologies. In this article I will show you how to get Prometheus up and running as a binary, a container running in Docker, and inside Kubernetes.

In today’s dynamic and rapidly changing environment, organizations deploy most, if not all of their business solutions using SaaS applications. This fast-paced digital transformation makes it critical for organizations to ensure the performance of SaaS applications, so that these applications can meet end user demands and provide the expected experiences. IT teams must ensure their SaaS applications are functioning well, facilitating productivity rather than inhibiting it.

There are many aspects of application performance, but they broadly fall into two categories: frontend performance and backend performance. As a tester, it’s important to know the differences between the two and how that impacts the way you approach your tests. In this blog, I’ll provide a high-level overview of frontend performance testing and backend performance testing, including pros and cons of each one.

With the goal of helping you get to the “why” faster, Splunk Observability recently announced several new enhancements to reduce noise and provide more visibility when isolating problems in your environments. Specific to applications and services, whether you operate monolithic or microservices architectures our releases help you easily investigate problems in complex environments. Here’s a roundup of the recent Splunk APM capability releases, and helpful links to help get started now.

Platform engineering is the practice of automating infrastructure operations and enabling self-service infrastructure capabilities within collaborative Dev, Ops and QA teams. It involves designing and building platforms, technologies and workflows that enable self-service capabilities to automatically manage, provision and operate complex modern software architecture environments.

If you’re part of the DevOps, SecDevOps, or IT team, you would agree that continuous monitoring of the entire IT systems and networks is vital. And this explains why 70% of businesses treat preventing downtime as a priority to avoid causing significant issues in the future. So monitoring your IT infrastructure constantly with a continuous monitoring plan is one way of improving efficiency and productivity.

The blog will take you through best practices to observe Kafka-based solutions implemented on Confluent Cloud with Elastic Observability. (To monitor Kafka brokers that are not in Confluent Cloud, I recommend checking out this blog.) We will instrument Kafka applications with Elastic APM, use the Confluent Cloud metrics endpoint to get data about brokers, and pull it all together with a unified Kafka and Confluent Cloud monitoring dashboard in Elastic Observability.