Platform engineers and SREs in organizations that are moving homegrown workloads to the cloud often have fragmented visibility of their hybrid IT landscape, caused by the scale and ephemeral nature of cloud environments. This lack of end-to-end visibility can result in service degradations and prolonged downtimes.
Platform engineers and SREs commonly use either homegrown monitoring systems that are incomplete and require heavy maintenance, or commercial tools that were designed for a subset of environments and monitoring needs, resulting in a fragmented view of their hybrid cloud.
Software engineers who build new apps in the cloud are used to instrumenting their code with time series data (metrics) using open source frameworks such as Prometheus, Telegraf, StatsD, or CollectD. Collecting and visualizing these metrics directly into the Splunk platform is often not easy or intuitive. In addition, when viewing logs for troubleshooting, software engineers often use purpose-built visual tools that require separate data ingestion. If the organization already uses the Splunk platform, they end up paying twice for the same log data.
How can Splunk help?
Splunk Observability Cloud provides a number of capabilities that help customers observe their cloud or on-premises environments.
First, Splunk Log Observer provides a powerful way to leverage the Splunk platform. It provides a low-code way of working with logs that does not require knowledge of SPL and fits naturally with troubleshooting workflows. You can easily add groupings and filters, and save queries for future use. When you're done, take the view you created and use it along with trace and infrastructure data to get all your telemetry information on the same dashboard.
Second, Splunk Observability Cloud provides hundreds of dashboards out-of-the-box, for example, for all the major clouds such as AWS, Azure, and GCP, as well as for many technologies, databases, and middleware. Dashboards are also customizable to meet your needs.
AutoDetect is another capability from Splunk Observability Cloud that helps you get value quickly. AutoDetect detectors provide context within the UI and users can subscribe, customize, or disable these detectors.
Finally, you can observe both microservices and monoliths with Splunk Observability Cloud. With microservices, distributed tracing follows the paths of code but only takes a picture at the time of a transaction, or request to a service. This is helpful because your biggest challenge is determining which microservice is contributing to the issue. With monoliths, AlwaysOn Profiling helps you get more granular. With monoliths, you want to understand what parts of the code are problematic. AlwaysOn Profiling continuously takes pictures at a set interval so you can see what was running at a specific point in time.
With Splunk Observability Cloud, DevOps teams are able to view all the data they need for faster troubleshooting in a single, simple unified experience, without needing heavy maintenance or paying twice for sending the same data.