Over the last few years, one of the more common conversations I’ve had with customers hasn’t been about load balancing, security policies, or even application delivery.
It has been about telemetry.
Not because customers suddenly woke up one morning and decided they wanted BIG-IP metrics. Rather, because observability teams are asking the same question they’ve asked application, infrastructure, and cloud teams:
“Can you get your telemetry into our platform?”
For some organizations that platform is Splunk. For others it’s Datadog, Elastic, Dynatrace, Sumo Logic, Azure Sentinel, or one of the many OpenTelemetry-based solutions that seem to appear every month.
The challenge isn’t usually convincing someone that BIG-IP telemetry is valuable.
The challenge is getting that telemetry where it needs to go.
Before I talk about the tools, though, it is worth mentioning the solution I recommend first when customers ask how to monitor, troubleshoot, and analyze BIG-IP environments.
Start with F5 Insight for ADSP
If you want operational visibility into a BIG-IP deployment, F5 Insight for ADSP should be your first stop.
F5 Insight is much more than a telemetry dashboard. It provides fleet-wide visibility, health monitoring, operational analytics, configuration insights, and troubleshooting capabilities designed specifically for BIG-IP environments. Instead of jumping between individual devices, teams can view performance, resource utilization, application behavior, and telemetry trends across their entire BIG-IP estate from a single platform.
What I’ve found particularly interesting is how Insight is evolving beyond traditional monitoring. AI-assisted analysis can help identify anomalies, surface relevant telemetry, and provide guidance based on decades of F5 operational expertise. Combined with integration into the F5 AI Data Fabric (AIDF), Insight is becoming as much about operational intelligence as it is about collecting data.
It also helps address the operational side of running BIG-IP at scale. Beyond observability, Insight provides visibility into software versions, fleet health, lifecycle management, and centralized operational workflows that simplify activities such as upgrades, maintenance planning, and ongoing management across large BIG-IP deployments.
For organizations looking for a comprehensive F5-centric operations and observability platform, that’s a powerful story.
But it’s not every story.
Many organizations have already standardized on platforms such as Splunk, Datadog, Sumo Logic, or OpenTelemetry-based observability stacks. They aren’t looking to replace those investments—they simply want BIG-IP telemetry integrated into them.
That’s where the projects in this article come in. These community-supported tools are not intended to replace F5 Insight. Instead, they focus on helping customers answer two questions:
- How do I configure BIG-IP Telemetry Streaming correctly?
- How do I get BIG-IP telemetry into the tools my organization already uses?
The first problem: Getting F5 BIG-IP Telemetry Streaming working
I can’t count the number of times I’ve worked with a customer who wanted to use BIG-IP Telemetry Streaming and found themselves stuck somewhere between “I installed the RPM” and “why isn’t anything showing up in Splunk?”
In fairness, Telemetry Streaming does a lot.
It can export BIG-IP metrics and logs to a wide variety of external systems. It supports multiple consumer types, handles normalization, and provides a declarative framework for exporting operational data from BIG-IP.
What it doesn’t do is tell you whether your BIG-IP is actually configured correctly before you start troubleshooting.
After helping enough customers work through those deployments, I decided I wanted something that could answer a very simple question:
Is this BIG-IP ready to use Telemetry Streaming?
BIG-IP Telemetry Streaming Validator and Configurator
GitHub Repository: BIG-IP Telemetry Streaming Validator and Configurator
The BIG-IP Telemetry Streaming Validator and Configurator started as a readiness checker and evolved into a configuration assistant for Telemetry Streaming deployments.
The idea is simple:
Point the tool at a BIG-IP. Select your intended telemetry destination. The tool validates that the required Telemetry Streaming components, extensions, resources, and configuration are present.
If they aren’t, it can help configure the system so that BIG-IP can begin exporting metrics and logs through Telemetry Streaming.
I intentionally focused on the things that usually slow deployments down:
- Missing extensions
- Missing shared objects
- Incorrect prerequisites
- Incomplete configurations
- TS deployment readiness
Instead of spending time piecing together prerequisites from documentation, administrators can focus on the end goal: getting telemetry exported to the destination platform.
In other words, the project is less about troubleshooting Telemetry Streaming and more about getting Telemetry Streaming configured correctly in the first place.
The second problem: Getting BIG-IP telemetry into existing pipelines
The second lesson I’ve learned is that many customers already have mature observability practices.
They’re already using dashboards.
They’re already collecting logs.
They’re already managing metrics.
They simply want BIG-IP data alongside everything else.
That observation led to the second project.
BIG-IP Telemetry Exporter
GitHub Repository: BIG-IP Telemetry Exporter
The BIG-IP Telemetry Exporter focuses on integration. Rather than treating BIG-IP as a standalone monitoring island, the exporter helps organizations incorporate BIG-IP telemetry into broader observability ecosystems and workflows.
The basic idea is pretty simple: connect to one or more BIG-IP systems, select the telemetry you care about, and export that data into the tools your organization is already using. In the current implementation, the project uses a frontend/backend design with an OpenTelemetry Collector in the middle.
The backend connects to BIG-IP through iControl REST, polls selected API endpoints for metrics, and pushes those metrics to the collector using OTLP. For logs, the tool can help configure BIG-IP remote logging through AS3 and system syslog so traffic, security, analytics, and system events can be sent off-box as well.
From the UI, the workflow is designed to be practical. You connect one or more BIG-IP devices, enable the log types that make sense for that system based on provisioned modules, choose which API endpoints should be polled for metrics, and configure where metrics and/or logs should go from the OpenTelemetry Collector.
In practice, the exporter helps with a few common use cases:
- Multi-BIG-IP metric collection — connect to one or more BIG-IP systems and poll selected iControl REST stats endpoints for telemetry that can be exported through an OpenTelemetry pipeline.
- Log export configuration — configure BIG-IP logging paths for system syslog and module-specific logging profiles where appropriate, using AS3 and BIG-IP settings to send logs off-box.
- Separate handling for metrics and logs — send metrics and logs through collector paths that can be configured independently, which is useful because customers often store, index, and alert on those signals differently.
- Collector-based forwarding — use the OpenTelemetry Collector as the point of integration so telemetry can be forwarded to the platforms already in use by the customer’s observability or SIEM teams.
- Scalability across observability ecosystems — give teams a way to experiment with different telemetry destinations without redesigning the BIG-IP side of the integration every time the backend changes.
Why I built these
Like many of the projects shared on DevCentral, these tools weren’t created because I was looking for a side project.
They were created because I kept seeing the same customer challenges.
One project helps answer:
“Is my BIG-IP configured correctly for Telemetry Streaming?”
The other helps answer:
“How do I get BIG-IP telemetry into the observability platform my organization already uses?”
Neither project replaces F5 Insight.
In fact, I expect there will be increasing overlap in the future as F5 Insight continues to evolve and add capabilities around telemetry integration and analysis.
But for customers looking to integrate BIG-IP telemetry into existing observability and SIEM platforms today, these projects have proven to be practical tools that came directly from real-world customer conversations.
And that’s usually how the best DevCentral projects start.
Additional links
BIG-IP Telemetry Streaming Validator and Configurator GitHub Repo