The days of relying solely on on-premises hardware and software are fading fast as enterprises increasingly adopt public cloud services. With its undeniable benefits, organizations have embraced the cloud: Gartner estimates that the cloud will account for over 45% of all enterprise IT spending by 2026.
But while organizations welcome the cloud for its advantages, many IT professionals still struggle to monitor it. In fact, only 31% of IT leaders say their public cloud monitoring is effective. However, it’s more important than ever that companies successfully monitor and maintain their digital services as customer expectations are at an all-time high: 76% of consumers in our survey said their expectations are higher now than during the pandemic.
The issue many enterprises face is that they are limited by tools that promise a full-stack view but fail to deliver. Faced with scalability and performance issues as they juggle multiple applications, they’re simply not getting the complete picture. This results in disconnected data silos that force IT operations to jump from tab to tab, hinder visibility, and provide a biased point of view.
Navigating the journey to cloud native can be daunting, but it doesn’t have to be. In this article, we’ll share expert tips and best practices for monitoring and troubleshooting your organization’s public cloud applications.
Five tips for monitoring and troubleshooting public cloud applications
As your organization starts to run and manage applications in a public cloud environment, it’s critical to ensure you have the right tools and strategies to achieve the necessary visibility and performance.
Here are six tips to help you monitor your public cloud applications more effectively:
Tip One: Troubleshoot with cross-MELT data
Most companies use at least one of the four telemetry data types — Metrics, Events, Logs and Traces (MELT) — to pinpoint and troubleshoot application performance issues. However, each data type plays a critical role in discovering problems within applications — and each answers a different question when there is an issue:
- Monitor Metrics lets IT know what is going wrong
- Traces and Events reveal where the issues are originating
- Logs uncover the root cause of why the problem is happening
Sometimes, logs are unnecessary when you can use historical learning to isolate a common issue IT experienced in the past. However, most of the time, logs are critical in uncovering the why when troubleshooting.
While each of these data types gives critical insights, they work most effectively when used together. Correlating them will accelerate root cause identification. From there, you can quickly dive in to see where the problem is happening. This enables IT teams to reduce the time it takes to detect and resolve application issues in the cloud.
Tip Two: Speed issue resolution with AIOps
Monitoring complex IT operations is a time-consuming job that is at risk for error, especially as an organization’s cloud presence grows. Artificial intelligence for IT operations (or AIOps) helps improve operations and gives an added layer of vigilance in the public cloud.
AIOps platforms utilize big data, machine learning, and other advanced analytics technologies to detect issues automatically in real time. With proactive alerts, IT teams can respond quickly — sometimes even preventing performance problems before they happen. Leveraging AIOps technology to monitor public cloud applications is an essential business strategy that can enhance security and reduce performance issues that impact the business.
Tip Three: Don’t neglect containers
Kubernetes® is growing in popularity across businesses — and it’s not going anywhere anytime soon. A recent Cloud Native Computing Foundation survey found that 96% of organizations either use or are considering Kubernetes.
With many applications running on top of open-source containers, the desired state can make visibility murky. While it sounds great in theory that Kubernetes can correct configurations when needed, it does have significant holes. For example, it can’t correct when the configurations are fundamentally misconfigured, when there is a mistake in the infrastructure layer, or if the code has an error.
To effectively monitor the performance of applications deployed in Kubernetes, organizations need to rethink their monitoring approach. An end-to-end, unified container monitoring tool will give you insights into containerized applications, Kubernetes clusters, Docker containers and underlying infrastructure metrics. With full-stack Kubernetes observability, you can visualize Kubernetes availability, performance, and dependencies — and correlate them with the supporting cloud infrastructure health.
Tip Four: Ensure cross-domain visibility
With the overwhelming amount of data, assets, networks and applications, monitoring everything separately is inefficient, if not impossible. Add to that any on-prem infrastructure, and creating a single performance baseline becomes more than challenging.
Use a monitoring platform to help you create a unified baseline by pulling in third-party data from the cloud — such as Amazon Web Services, Microsoft Azure or Google Cloud Platform — and marrying it to your current infrastructure metrics. With a correlated, full-stack view of all telemetry data across the entire cloud native landscape, you can quickly address issues before they impact the availability and performance of cloud native apps.
Tip Five: Enable observability with open standards
‘Open standards such as OpenTelemetry™ are changing how IT teams approach monitoring of public cloud applications. A new framework for greater observability, OpenTelemetry standardizes how telemetry data — MELT — is collected and sent to your backend platform. This allows developers and site reliability engineers to practice observability with a more complete view of app performance.
Use an application monitoring platform that relies on OpenTelemetry as a data-ingestion standard. Be sure it can integrate seamlessly into the rest of your ecosystem with rich APIs to automate your CI/CD deliveries or share availability and performance telemetry data.
Modern applications need modern observability
Effective cloud monitoring is critical for both performance and security. Cloud monitoring tools collect data across multiple deployments so that IT teams get a clear perspective across their infrastructure. It helps save time, increases performance and improves efficiency — both now and in the future.
AppDynamics Cloud — our all-new observability platform — helps organizations do just that. It supports modern distributed applications with better visibility, trace analysis, and AI/ML-assisted baselines. AppDynamics Cloud is purpose-built to observe both dynamic and distributed cloud native applications at scale. Providing a unique combination of observability and advanced AIOps functionality, it empowers organizations with intelligent insights to address issues before they impact the availability and performance of cloud native apps.
Public cloud monitoring is simpler than you think
With AppDynamics Cloud, you can cut through the complexity of modern applications to get a seamless, unified view of your cloud native technology landscape. Take the guided tour of AppDynamics Cloud to see how it works.
Ready to talk to a cloud native specialist about how AppDynamics Cloud can help you boost visibility and performance? Let’s chat.