OpenTelemetry has emerged as the gold standard fueling o11y and SIEM platforms, but transitioning an existing telemetry stack requires careful planning and execution. This guide outlines a practical approach to evaluating, implementing, and scaling OpenTelemetry in production environments.

Winter has fully set in at Bindplane’s Michigan-based headquarters, but we’re keeping warm with the excitement from this piping-hot announcement and accompanying release. It’s just the thing to ignite the hearts, minds, and typing fingers (?) of our team and observability professionals as we kick off 2025.

Maintaining and visualizing telemetry data efficiently is super important for DevOps and SecOps teams. OpenTelemetry, a fantastic open-source observability framework, can really help with this without being too costly. Picture having a simple process that improves your data and helps your team make smart decisions without spending too much money. Let's chat about some budget-friendly ways to set up OpenTelemetry agents.

OpenTelemetry has quickly become a must-have tool in the DevOps toolkit. It helps us understand how our applications are performing and how our systems are behaving. As more and more organizations move to cloud-native architectures and microservices, it's super important to have great monitoring and tracing in place. OpenTelemetry provides a strong and flexible framework for capturing data that helps DevOps engineers keep our systems running smoothly and efficiently.

OpenTelemetry has quickly become a must-have tool in the DevOps toolkit. It helps us understand how our applications are performing and how our systems are behaving. As more and more organizations move to cloud-native architectures and microservices, it's super important to have great monitoring and tracing in place. OpenTelemetry provides a strong and flexible framework for capturing data that helps DevOps engineers keep our systems running smoothly and efficiently.

Solving system failures and performance issues can be like solving a tough puzzle for engineers. But trace data can make it simpler. It helps engineers see how systems behave, find problems, and understand what's causing them. So let’s chat about why trace data is important, how it's used for finding the root cause of issues, and how it can help engineers troubleshoot more effectively.

Starting your journey to build your first OTel Collector can be really exciting, but it can also feel a bit overwhelming. OpenTelemetry, or OTel, is an amazing tool that can help standardize the collection of observability data, but it's normal to feel a bit lost at first. There are lots of little details and best practices that can make the whole process easier, but many of us end up learning them the hard way.

OpenTelemetry, OTel, is an incredible open-source observability framework that helps you collect, process, and export trace data. It's super valuable for engineers who want to understand their systems better. At the heart of this framework lies the OpenTelemetry Collector, a pivotal component that turns raw traces into useful metrics. Let’s explore the importance of the OpenTelemetry Collector and show you how it makes it easier for engineers to make sense of data.

Telemetry data, at its core, is all about transmitting real-time information from remote sources to centralized systems for analysis and action. This data is super important across different industries due to its ability to provide immediate, actionable insights that enhance operations and strategic decision-making.

The OpenTelemetry Collector is a powerful tool for processing different types of telemetry data, such as metrics, traces, and logs, all in one place. This is important because traditional observability tools often require separate toolchains, which can be inconvenient and inflexible when changes are needed.