Organizations of all sizes rely on their observability data to drive critical business decisions. Production Engineers across Development, ITOps, and Security use it to understand their systems better, respond to issues faster, and ultimately provide more performant and secure user experiences. But while the value of observability data is well understood, teams struggle to derive value from it.

HAProxy is generally the frontend layer of your application, which means it plays a critical role since all traffic first lands on this layer. Because of this, you need to make sure everything is working at this layer all the time, as any issue can directly impact your business. Therefore, having visibility on this layer is crucial. Visibility can come from two aspects: the metrics HAProxy emits and the logs it generates while handling requests.

Understanding if your applications are not just available but also functioning as expected is critical for any organization. Third-party dependencies and different end-user device types means that infrastructure monitoring and application observability alone are not enough to spot and minimize the impact of application anomalies.

Microservices architecture is the new norm for building products these days. An application made up of hundreds of independent services enables teams to work independently and accelerate development. However, such highly distributed applications are also harder to monitor. When hundreds of services are traversed to satisfy a single request, it becomes difficult to investigate system issues.

Ask any cloud software team using Kubernetes (and most do); this powerful container orchestration technology is transformative, yet often truly challenging. There’s no question that Kubernetes has become the de-facto infrastructure for nearly any organization these days seeking to achieve business agility, developer autonomy and an internal structure that supports both the scale and simplicity required to maintain a full CI/CD and DevOps approach.

The ongoing partnership between Papertrail and DigitalOcean led to the development of the Papertrail software as a service (SaaS) add-on in the DigitalOcean Marketplace. With the add-on, developers can add powerful, simple, and scalable Papertrail log management to their DigitalOcean infrastructure in seconds. In two earlier posts, we reviewed how the add-on helps teams simplify and centralize log management.

In part 1 of this series, we talked about zombie data and what it means for your observability architecture. In this post, we’ll talk more about how to handle all of it. How well can your organization handle the firehose of data it’s collecting? Yes, you have the ability to collect it, but chances are you don’t have the financial or human resources available to analyze all of it effectively.

Dashboards are not just tools for businesses and other organizations to monitor and respond to their data, but can be a method of storytelling. All of our data has the potential to be crafted into compelling narratives, which can easily be accomplished with the help of Dashboard Studio’s customizable formats and advanced visualization tools. We can take a series of disparate datasets and bring them together in one place if they share a common theme — in this case, Halloween.

We’ve reached the point where our ability to collect data has actually exceeded our ability to process it. Nowadays, it’s commonplace for organizations to have terabytes or even petabytes worth of data sitting in storage, waiting patiently for well-intentioned systems admins to eventually analyze it.