The modern software development life cycle is faster than ever, with multiple stages of development and testing happening concurrently. This is the DevOps culture, transitioning from siloed teams, performing development, testing, and operations tasks to a united team performing all functions and embracing the “you build it, you run it” philosophy. So now, with the continuous development of DevOps practices, as well as other factors like the rapid pace of modern code changes, the work of Dev and Ops teams is never done.
But how can one recognize the signs of a malfunctioning system? How does the IT department detect system compromises? How does the development team find out when a bug has surfaced and is interfering with user experience? Well, the answer is continuous monitoring.
It is expected that using DevOps will result in speedier development, more frequent releases, regular testing, and cost savings. Automation and increased measurement and visibility across the whole development lifecycle—from planning, development, integration and testing, deployment, and operations— can be achieved by DevOps monitoring tools. In this blog, we will delve into the types of monitoring and intricacies of how tools like Prometheus help in continuous DevOps monitoring. Let us dive in!
DevOps Monitoring: A Necessity
The two major obstacles software businesses frequently struggle with today are: delivering at speed and innovating at scale. And DevOps helps address these challenges by imbibing automation throughout the software development lifecycle (SDLC) to develop and deliver high-quality software. However, one must continuously monitor this CI/CD pipeline to realize the DevOps promise.
What exactly is monitoring in DevOps, and how can companies use it to maximize their DevOps potential? Let’s investigate further.
Monitoring the entire development process, including planning, development, integration and testing, deployment, and operations, comes under DevOps monitoring. It includes a comprehensive and up-to-date picture of the infrastructure, services, and applications present in the production environment.
With DevOps monitoring, teams can react swiftly and autonomously to any deterioration in the user experience. More significantly, it minimizes broken production changes by enabling teams to “shift left” to previous phases of development.
But how can one start? By Monitoring the infrastructure and Application Performance!
Monitoring Infrastructure
Infrastructure Monitoring collects the data from the IT infrastructure and analyzes it to derive insights that help in tracking the performance and availability of the computer systems, networks, and other IT systems. Infra Monitoring covers hardware, OS, network, and server monitoring. One of the popular Infrastructure monitoring tools is Prometheus. Monitoring IT Infra helps in:
Real-Time Visibility
For identifying potential bottlenecks, performance issues, or vulnerabilities, visibility is highly crucial. This includes the real-time tracking of the computer systems, servers, processes and equipment that make up the computing network in an enterprise. Each member of the DevOps team should be able to understand and access real-time data so any bottlenecks can be removed effectively.
Use Case: Consider a sudden spike in CPU usage is detected across multiple servers. With real-time visibility provided by monitoring tools, a business can quickly identify this anomaly and investigate the root cause, such as a poorly optimized application or a sudden increase in user activity.
Having a Centralized Dashboard
A single pane of glass provides a comprehensive view of various applications, services, and infrastructure dependencies, not only in production but also in staging. This gives the ability to provision, ingest, tag, view, and analyze the health of complex distributed environments. Some tools offer customizable dashboards that allow to visualize and analyze data from multiple sources, facilitating quick identification of performance anomalies.
Use Case: In a distributed microservices architecture, a centralized dashboard can display key performance metrics for each microservice, allowing us to monitor the overall system health and identify any service-specific performance issues. By visualizing metrics such as request latency, error rates, and throughput, we can quickly pinpoint underperforming services and take proactive measures.
Network Monitoring
Everything on the network is monitored, including firewalls, servers, virtual machines, routers, and more. Network monitoring is responsible for finding errors, gauging these components’ effectiveness, and optimizing its functionality. A dynamic network monitoring system can help avoid downtimes and failures before it affects performance.
Use Case: Suppose there is a sudden increase in network latency or a spike in packet loss. By monitoring these network metrics in real-time, we can promptly identify and address potential network performance issues.
Application Performance Monitoring with KPI Metrics
Application Performance Monitoring (APM) plays a crucial role in ensuring the performance and reliability of applications. APM tools collect and analyze data from various sources, such as application logs, metrics, and transaction logs, to provide insights. By leveraging KPI metrics with it, businesses can identify areas for optimization and enhance the user experience. This includes analyzing response times to ensure that applications meet performance expectations, as well as monitoring resource utilization to identify potential scalability issues. This can be done by:
Following Metrics-Driven Approach
A metrics-driven approach to APM involves tracking key performance indicators (KPIs) to quantitatively measure the effectiveness of an application in achieving business objectives. But capturing the right metrics is crucial. Monitoring tools can be used to collect custom application metrics such as request throughput, error rates, and database query latency.
Use Case: Consider an e-commerce application experiencing a sudden increase in error rates during peak traffic hours. By leveraging KPI metrics collected by Prometheus and visualized in Grafana, we can swiftly identify the root cause, such as a database overload or a misconfigured API endpoint.
Response Time Analysis
It is a critical metric that measures the time taken for the system to respond to user requests. Average response time, 95th percentile response time, etc. are important metrics for assessing application performance. These metrics enable development teams to identify and address performance issues that may impact user satisfaction and overall application performance.
Use Case: In a customer-facing application, a sudden increase in response times for checkout transactions is detected. By analyzing response time metrics collected by tools like Prometheus and visualized in Grafana, we can promptly identify the underlying cause, such as a third-party payment gateway latency or database contention etc.
Resource Utilization
It is essential for identifying potential scalability issues and ensuring consistent performance as the system grows. Prometheus can be utilized to monitor CPU, memory, and disk utilization, while Grafana provides visualizations for analyzing resource utilization trends.
Use Case: As app experiences increased user adoption, monitoring resource utilization becomes crucial. By collecting resource utilization metrics and visualizing them, we can accurately forecast requirements and proactively scale the infrastructure to accommodate growing demand.
At Nujtech Software Solutions, we understand the significance of robust monitoring solutions and offer services that leverage cutting-edge tools like Prometheus. Our tailored solutions enable businesses to achieve real-time visibility, proactive incident management and continuous improvement.
For more information on how Cloud4C’s monitoring solutions can boost your business, contact our team today.
