Introduction to Splunk Observability Cloud - Building a Resilient Hybrid Cloud
In today’s fast-paced digital landscape, applications are supported by a growing array of technologies, all designed to accelerate time-to-market. However, the competition is fierce, and failing to move quickly could mean being outpaced by rivals. Yet, operating at this speed is anything but straightforward. The environments businesses utilize grow increasingly complex, often spanning private data centers, public clouds, and colocation facilities. Among ongoing upgrades, migrations, and innovations, one truth remains: customers typically don’t care about where a business is in its transformation journey; they expect seamless service.
Each component of your infrastructure generates immense volumes of data. Logs from applications, servers, firewalls, network performance tools, and security monitoring have created an endless amount of information. When issues arise, determining where to look for the cause can be overwhelming. At Splunk, we understand this challenge and aim to cut through the noise, providing clarity and actionable insights. Without the ability to correlate an application’s performance with business outcomes and user experience, organizations are left in the dark.
The Evolution of Application Architecture
I’ve been building enterprise IT infrastructures for over 20 years now. Looking back in the early 2000s, classic 3-tier application architecture was much simpler. A new application typically required merely deploying a physical or virtual server, installing an OS, and layering the application on top.
Troubleshooting involved checking the OS performance and logs. However, these straightforward architectures couldn’t scale or change fast enough to adapt to the evolving digital landscape.
The advent of distributed application architectures, such as Kubernetes and microservices, revolutionized how applications are built and deployed. Modern applications are now interwoven across multiple clouds and can be developed quickly. However, as these applications grew more complex, they often emerged from shadow IT teams that rapidly turned them into mission-critical operations requiring dedicated monitoring and support.
Classic infrastructure teams that were built around monitoring 3-tier applications were now tasked with monitoring these new distributed architectures. Traditional tools and processes designed for 3-tier applications do not suffice for these new distributed architectures. When errors occur, teams often find themselves struggling across various siloed tools, resulting in costly “tiger” teams and diminished end-user satisfaction. This is where Splunk Observability Cloud comes into play.
Introducing Splunk Observability Cloud
Splunk Observability Cloud empowers organizations to manage and monitor both classic 3-tier architectures as well as modern distributed applications with speed and precision. By leveraging the power of our AI engine, Splunk helps businesses identify problems faster and significantly reduces mean time to resolution (MTTR). Thus building a more resilient architecture.
Let’s take a closer look at how Splunk enhances observability through foundational features tailored for both 3-tier and modern architectures.
Today, modern application services may be distributed across private data centers, hyperscaler clouds, or various third-party SaaS offerings. Each service operates with its own tools and access procedures, making it challenging to pinpoint errors. Splunk, however, provides visibility across all these services.
With our Observability Cloud, we can aggregate logs, performance metrics, and application traces, offering a comprehensive overview of how each service interacts. Splunk application trace analysis reminds me of classic Windows or Linux network tracing tools like trace route, Trace route would show an admin each network hop from point A to point B. Splunk Application Traces powered by OpenTelemetry work in a similar fashion, this would allow teams to visualize the communication between application services.
This interplay creates Splunk Observability Cloud application service maps. These service maps are dynamically created and illuminate error locations and their impacts on upstream and downstream services.
Moreover, our AI capabilities extend to predictive analytics, enabling early anomaly detection. By providing real-time alerts on performance issues, teams can address potential problems before they escalate. The Splunk Observability Cloud UI streamlines this process, allowing for rapid examination of logs tied to specific services through the Splunk Platform.
Bringing all these pieces together gives you a powerful view of the big infrastructure picture of your entire hybrid cloud. Helping you reduce the amount of tools necessary to diagnose issues in your environment. While also, reducing your MTTR across all your public and private cloud infrastructure.
Conclusion
In this blog, I’ve only touched lightly on what Splunk Observability Cloud is. Many fans of Splunk know us for our log analytics, but Splunk does so much more than just logs. We can use the power of our log analytics (Splunk Platform) along with Splunk Observability Cloud to monitor the performance and diagnose issues of an entire hybrid cloud all with AI.
This is my first blog as a new Splunker, I ask you to continue on this journey with me. In each blog, I’ll dive deeper into what Observability Cloud is and all the features and capabilities it has to offer. You’ll soon discover Splunk is more than logs.
Want to try it out? Take Splunk Observability Cloud for a free 14 day trial.
https://www.splunk.com/en_us/download/o11y-cloud-free-trial.html
