Optimising Observability and Synthetic Monitoring With Splunk

Making your IT systems observable is essential to the reduction of system outages. With optimal application observability, DevOps teams can quickly track and troubleshoot app issues and system incidents. In this article, we define observability and look into how synthetic monitoring complements it. We also show how enterprises can use Splunk and 2 Steps software platforms to enhance observability in IT.    

What is Observability in Information Technology?

Observability is the generation of actionable, granular insights into the performance or behavior of a system. Typically, system developers engineer observability into a company's IT architecture. Such a system can, in turn, generate highly accurate and contextual observations on performance. Programmers or developers may then utilise these observations for debugging purposes.  

Observability does more than point out what exactly happened in the past within an IT system. It provides end-to-end visibility into processes or events that are associated with system degradation or malfunction, establishing causal relations between incidents/events. This way, technicians can troubleshoot complex IT problems and find root causes based on precise, actionable intelligence instead of relying on conjecture. 

Why Incorporate Synthetic Monitoring into Your Observability Strategy?

Monitoring complements observability, meaning that both are essential to optimal system availability and health. Synthetic monitoring relies on automated codes or scripts, rather than real users, to track the condition of IT resources. You can use it to simulate and assess the user experience on your web pages, APIs, mobile apps, and other IT assets.

Incorporating synthetic monitoring into your observability strategy has the following benefits:

• It enhances the customer experience: By simulating the path or action that a customer may take on an app or web page, you can quickly track and resolve issues that impact the user experience. For starters, IT teams may correlate any alerts generated during automated UX tests with observability findings. They may then establish root causes and troubleshoot problems before they affect real users.  
• 24/7 monitoring: You can deploy your synthetic monitoring tools and get results at any time of the day or night.
• Synthetic monitoring lets you assess the UX even without an optimal number of actual users: By automating the UX, you can simulate navigation, signup, login, or shopping-cart transactions when your site is not yet available to the public. Experience automation is also ideal for when your website is not getting enough traffic for comprehensive testing.
• Baselining: Synthetic monitoring can help with the development of baseline tests. Such tests can help to assess an application's performance and determine if it satisfies the relevant service level agreement before going live to customers. Also, the data you continuously gather during automated monitoring can help to create a reliable app performance baseline and pinpoint areas that require improvement.

In a nutshell, synthetic monitoring can give you a full view of the problems users experience or might encounter while using your mobile apps, software, or website. But it doesn't generate in-depth cause-and-effect information. That's why it makes sense to integrate synthetic monitoring with observability to give DevOps quick insights that can help with debugging or prevention of system degradation.

How Splunk Helps with the Implementation of Observability

Splunk automates the observability of IT operations, end to end. With the tool, you can build your apps to give internal visibility into code execution and events. Such automation helps to fast track continuous integration and continuous delivery in complex multi-cloud, distributed systems. In turn, DevOps can spend more time writing functional code than monitoring the development and preproduction environment.  

Splunk's key pillars include:   

• Logs: The software facilitates the consolidation and indexing of any log and machine-generated data for analytics and debugging purposes. This data may come from disparate structured and unstructured sources. It enables organizations to spot and troubleshoot operational and security issues in IT quickly.
• Events: Splunk indexes events, which are records of activities contained in log files and machine data. Each event has information on the system that generated the machine data. It includes specifics such as timestamps.
• Metrics: Splunk lets you extract performance metrics from platforms such as IoT devices, IT infrastructure, cloud-based systems, web servers, databases, and mobile applications.

Organisations can enhance observability in IT with Splunk in ways such as:

Structured/Unstructured Data Consolidation

With Splunk, you can collect events or process data from disparate sources in structured and raw formats. You may then establish correlations in real time and determine root causes.

Clustering

This feature lets you correlate and group system events to simplify behavioral analytics. It also helps to minimize alert noise.

Contextualizing Observations

Adding context to facts or observations enables DevOps to formulate appropriate solutions to system problems. With Splunk, you can track and analyse issues that are relevant to specific business applications or contexts.

Anomaly Detection

Splunk enables you to spot system events that deviate from historical behavior. Traditional monitoring techniques may not catch all unusual activities that warrant the urgent attention of DevOps personnel.

Root-Cause Analysis

DevOps teams can use Splunk to generate in-depth root-cause analytics. The software provides an easy-to-use dashboard from which users can dig deep to identify the cause of identified system incidents.

Building Your Observability Strategy: How 2 Steps Can Help

Looking to simulate and track the customer journey across your mobile app, e-commerce site, windows software, or mainframe system? Try 2 Steps, a multi-platform synthetic monitoring tool for distributed systems! The synthetic monitoring solution is ideal for on-premise and cloud-based deployment. Its key features and benefits include:

• Rapid deployment: The app requires no coding to deploy. So, it enables IT Ops teams, DevOps staff, or product managers to get started on UX analytics right away.
• Splunk integration: After gathering data on platform performance using 2 Steps, you may present it to relevant stakeholders via the Splunk dashboard. Such data may include  video replays of identified system events or processes.
• Reduced MTTR: By correlating 2 Steps synthetic monitoring data with Splunk's observability data, IT teams can quickly establish the root cause of issues. So, seamless integration of the two platforms helps to minimize the Mean Time to Resolution.   

Conclusion: Integrating Synthetic Monitoring With Observability Optimises IT Performance

Synthetic monitoring drives experience automation to track and test the UX or customer experience before going live with business solutions (or new app features). On the other hand, observability platforms deliver in-depth end-to-end insights into the performance of modern distributed systems to enhance and fast track troubleshooting. As such, synthetic monitoring and observability tools are essential to the optimisation of IT systems' performance and availability.

At 2 Steps, we offer a Synthetic Monitoring Tool you can quickly integrate with Splunk and deliver mission-critical insights into the performance of your IT systems. Contact us to learn more or request your free trial now!