Teams running applications in cloud native environments and DevOps practices create business value by quickly deploying new changes and improvements to customers. While microservices and Kubernetes add speed and scale, they also create an explosion of complex dependencies from APIs and third parties. Constant change across billions of components increases the risk for new errors, slowness, or outages that impact service performance, customer experience, and ultimately business outcomes.
Existing monitoring tools provide business context with the ability to add custom metrics; however, they provide limited capabilities to accurately alert and measure the performance of infrastructure, application, and end user experience against their business. Since traditional monitoring largely samples data, engineers rely on incomplete data sets to scope, prioritize, and isolate problems impacting their business. And while a lot of monitoring tools do a good job surfacing visibility into application golden signals or infrastructure metrics, it’s not easy to get to the “so what?” to understand the broader impact of a software or infrastructure performance issue on your business.
How can Splunk help?
Pushing a change to an application is often the top cause of an incident, and while avoiding incidents is ideal, it is not a realistic goal. Splunk Observability Cloud provides a number of capabilities to help you understand the impact of application changes so you can respond appropriately.
- Splunk Real User Monitoring provides a summary of your applications and metrics for the various pages your users interact with. These key metrics are compared with past metrics, so if things get worse, you can easily identify the situation and dig into it.
- To enable you to troubleshoot without reproducing issues, Splunk Observability Cloud captures every single trace, which means you can search and find any transaction you need to. Session search allows you to find the transactions. You can search for sessions by the ID or by filtering for a specific subset of transactions, like by browser, country, and more. Clicking into a session gives a full list of everything the user interacted with during their session and provides links correlated to information in Splunk APM.
- Distributed tracing helps you understand where in a microservices architecture you have latency or errors. It also helps you understand when certain workflows or data influence latency or errors.
- AlwaysOn Profiling tells you how CPU time and memory are performing. While distributed tracing focuses on transactions, AlwaysOn Profiling is able to get granular to the line of code. This profiling can be run in monoliths or microservices, and can be run all the time.
- By tracing data, you can normalize SQL and NoSQL queries to understand how long queries are taking and reveal where optimization is necessary.
Watch the following video to see a demo of how AlwaysOn Profiling and Database Query Performance in Splunk APM can be used to solve an adservice latency problem.
With Splunk Observability Cloud, organizations can accurately detect changes that negatively impact their business, and thoroughly prioritize and resolve issues. As teams deploy code, make improvements, or launch new features, they measure business output alongside the health of their infrastructure, applications, and end user experience. When problems happen, they can scope the severity of an issue and confidently troubleshoot across their cloud environment.