Adding additional attributes to your telemetry not only provides valuable context to your observability pipeline but also enhances the flexibility and precision of your data operations. Consider, for example, the need to route data from specific geographical locations, like the EU, to a designated destination. With a ‘Location’ attribute added to your logs, you can seamlessly achieve this.

When engaging with potential customers, we are often asked “how can we reduce spend on our observability platform like Splunk or Data Dog and simultaneously justify the cost of BindPlane OP?” Let’s dive in and see how the powerful capabilities of BindPlane OP can reduce your total ingest, and get a positive ROI on your BindPlane OP investment.

In the rapidly evolving landscape of modern tech, system reliability has become a critical factor for businesses to succeed. To ensure the stability and performance of complex distributed systems, companies are relying on observability—a concept that isn’t synonymous, but instead goes beyond traditional monitoring approaches.

If you’ve worked with NGINX web servers, you know they’re efficient but can generate a lot of log data. While this data is valuable, sorting through it can be a challenge, and the storage and processing costs can quickly add up. This is where BindPlane OP comes in. It helps reduce log volume while still preserving the crucial information. It streamlines your data, filters out the irrelevant bits, and zeroes in on key data points, helping manage storage and keep costs under control.

Parsing logs with regex is a valuable technique for extracting essential information from large volumes of log data. By employing this method, one can effectively identify patterns, errors, and other key insights, ultimately streamlining log analysis and enhancing system performance.

As the amount of telemetry being collected continues to grow exponentially, businesses are continuously seeking cost-effective ways to monitor and analyze their systems. Data collection and monitoring can be expensive, especially when dealing with large volumes of logs. One approach to maintaining visibility while reducing the amount of data collected is through creating log-based metrics.

Logs often contain sensitive data, including personally identifiable information (PII) such as names, email addresses, and phone numbers. To maintain security and comply with data protection regulations, it’s crucial to mask this data before storing it in your log analytics tool. BindPlane OP streamlines this process with the Mask Sensitive Data processor, ensuring your logs are safe and compliant.

At observIQ, we use the OTel collector to collect host/container-level metrics and logs from our systems. But to get more detailed monitoring of our applications (APM), we use the OTel SDK and instrumentation libraries. This post aims to provide a quick start to setting up tracing exporting to a local Jaeger instance.

With observIQ’s latest contributions to OpenTelemetry, you can now use free open source tools to easily monitor Cloudflare. The easiest way to use the latest OpenTelemetry tools is with observIQ’s distribution of the OpenTelemetry collector. You can find it here. In this blog, the Cloudflare receiver is configured to monitor logs locally with OTLP– you can use the receiver to ship logs to many popular analysis tools, including Google Cloud, New Relic, OTLP, Grafana, and more.

Fluentbit is a popular logs and metrics collector used for monitoring anything from virtual machines to containerized applications. With the rise of BindPlane OP and OpenTelemetry, it is not uncommon for organizations to begin replacing Fluentbit, or integrating OpenTelemetry with Fluentbit. An organization may have hundreds or thousands of Fluentbit agents deployed to their endpoints but they want to manage the pipeline using BindPlane OP.