Cloud native applications, built on microservices, containers, and dynamic orchestration like kubernetes, offer unparalleled scalability and agility. However, this very complexity demands a new approach to understanding and managing application health and performance – enter cloud native observability. Cloud-native observability is a powerful approach to gaining deep insights into your cloud applications and infrastructures.

In this article, we'll delve into specific use cases to demonstrate how observability solutions can help you effectively monitor and optimize the health of your cloud-native applications.

Eliminate blind spots in your Kubernetes cluster

Kubernetes is renowned for making applications highly available and minimizing downtimes, but this doesn't mean Kubernetes applications are free from issues. Blindspots can occur when application pods or clusters are restarted without understanding whether the restarts are due to traffic fluctuations, application errors, configuration mistakes, or routine operations. Additionally, despite their high availability, applications can still face performance issues during peak traffic periods due to the ephemeral nature of Kubernetes-managed environments.

Site24x7's infrastructure monitoring solution helps DevOps teams gain real-time visibility into the performance of the servers, Docker containers, and Kubernetes clusters powering your cloud-native applications.

Our Kubernetes monitoring tool provides visibility at various levels to ensure that you can view even the tiniest of details and optimize performance and resource utilization. At the cluster level, you can monitor CPU and memory usage to understand how your cluster behaves and identify any potential bottlenecks. Node monitoring allows you to track CPU and memory usage across your nodes, maintain an inventory of nodes, and monitor node conditions to ensure optimal health. Additionally, at the namespace level, you can analyze resource utilization and understand how CPU and memory are utilized within each namespace.

Our tool also provides detailed monitoring of workloads, including Pods, Deployments, DaemonSets, and StatefulSets, and offers inventory and performance data for each. Kubernetes service monitoring allows you to monitor the health and performance of the services within your Kubernetes environment, including Amazon EKS, Azure Kubernetes Service (AKS), and Google Kubernetes Engine (GKE). With event log and Pod log monitoring, you can keep track of events and application logs, facilitating troubleshooting and performance optimization.

Kubernetes Monitoring Fig 1: Kubernetes monitoring

Finally, our predictive forecasting feature helps you anticipate performance issues by providing insights into future performance metrics, allowing you to proactively address potential issues before they impact your applications. Additionally, Site24x7's Docker monitoring module identifies performance bottlenecks within containerized microservices, enabling your DevOps team to quickly identify the root causes of performance issues, such as insufficient server capacity and resource contention, within containerized workloads.

Debug latency issues in your application flow using distributed tracing

Understanding the flow of a single request across a complex, distributed system is inherently challenging due to several factors. Identifying latencies and performance bottlenecks within individual services or across the entire request flow is difficult, yet crucial for optimizing overall system performance. Additionally, visualizing the dependencies and communication patterns between different services is essential to grasp the overall system architecture, which in turn helps identify potential areas for improvement or refactoring. These complexities make it hard to ensure efficient and reliable operation of distributed systems especially when the microserves are interacting with services like DynamoDB and S3.

Let us take the example of an e-commerce website where an unexpected spike in traffic overwhelms a microservice responsible for processing user orders. This microservice might interact with DynamoDB to retrieve product data and S3 to access product images. Without observability, it becomes difficult to pinpoint whether the slowdown was cuased by the overloaded microservice, or a bottleneck within Dynamo DB, or because of an issue in S3. Site24x7 and other cloud-native observability tools like AWS X-Ray can shed light on these interactions by tracing requests across the entire application stack, including external services, allowing developers to identify the specific component causing the performance issue, leading to quick troubleshooting. Additionally, Site24x7 and services like Amazon CloudWatch collect server logs through a centralized log management system. This holistic view empowers teams to correlate events across different layers, identify potential issues before they impact users, and ensure the smooth operation of your entire cloud-native application.

Site24x7's APM Insight solution helps you gain deep visibility by correlating the three pillars of observability. Your team can easily monitor key metrics, like response times, throughput, errors, and saturation (commonly known as the golden signals), for each microservice.

With distributed tracing, Site24x7's APM Insight traces the entire user journey and various interactions among different microservices to identify performance bottlenecks across the entire application flow. You can now optimize application performance, streamline development workflows, and ensure a reliable, scalable back end for your cloud deployments with the utmost ease.

Distributed tracing Fig 2: Distributed tracing

Escape alert fatigue with AI and automation

Manual processes, a lack of automation, and limited visibility into root causes all pose challenges when it comes to maintaining the reliability and availability of applications and services. Static rules and processes can severely limit your team's ability to detect abnormal behavior before it leads to an outage. By leveraging AI to detect anomalies based on past data and by implementing automated remediation mechanisms, you can reduce your DevOps team's workload and eliminate the possibility of human error.

With Site24x7's incident management, organizations gain access to advanced automation, AIOps, event correlation, and root cause analysis (RCA) features to streamline incident detection, diagnosis, and resolution in cloud-native environments. With our automation features, your team can automate repetitive tasks, such as incident triage, ticket creation, and remediation, reducing the mean time to resolution while improving operational efficiency. Event correlation identifies related events across applications, services, and infrastructure components, enabling you to prioritize critical incidents effectively. Our RCA capabilities provide insights into the root causes of incidents, helping you address underlying issues and prevent their recurrence.

With third-party integrations, you can tailor your monitoring stack to your needs and examine the factors impacting your business. You can even build your own custom plugins using custom scripts to gather the exact data for which you're looking. In case of any issues, alerts and notifications let you know when to dynamically scale server resources and adjust container resource limits to accommodate increased traffic loads and mitigate downtime. This allows you to achieve complete infrastructure observability.

By leveraging Site24x7's incident management capabilities, you can improve your operational efficiency, minimize downtime, ensure the reliability and availability of your cloud-native applications and services, and achieve complete cloud-native observability. Accomplish all this by automating incident detection, diagnosis, and resolution; detecting anomalies and predicting performance trends; correlating related events effectively; and identifying and addressing the root causes of incidents efficiently.

AI and automation Fig 3: AI-powered Anomaly Detection

Eliminate data silos and overcome tool sprawl with multi-cloud monitoring

Organizations deploying cloud-native architectures across multiple cloud platforms face challenges in achieving comprehensive observability. For instance, if an organization uses multiple tools, like Prometheus, Grafana, and Amazon CloudWatch, to monitor various aspects of its applications to make sense of their behavior, this can lead to tool sprawl, causing a disconnect in data collection and analysis. The use of a unified platform eliminates data silos completely and improves the user experience by leaps and bounds.

Site24x7's multi-cloud monitoring solution helps you ensure high performance, reliability, and security for your applications and services by consolidating telemetry data from diverse cloud platforms into a unified view. It provides insights into cross-cloud interactions and dependencies, facilitates proactive performance monitoring and alerting, and enables consistent compliance and governance across multi-cloud deployments. By leveraging multi-cloud monitoring, your team can optimize the efficiency, resilience, and compliance of their cloud-native architectures, ensuring seamless operations, superior user experiences, and enhanced security across multiple cloud platforms.

Eliminate data silos and overcome tool sprawl with multi-cloud monitoring Fig 4: Multi-Cloud Monitoring