The year is over, and the word ‘Observability’ has been one of the buzzwords that kept everyone checking throughout the year for deserving reasons. The organizations do not want to leave any stone unturned to maintain performance and offer robust services from ‘monitoring’ practices to ‘observability’, ‘telemetry’, and visibility capacities. So let’s get into the meaning of each term and understand how they are vital for business growth.
What is Observability?
Shaun McCormick, a senior staff engineer at Big Commerce, explained the idea behind observability how it’s not about knowing if the problem is occurring, but why it is happening in the first place and how someone can solve it.
The only way to stay sustainable in a competitive market is by adopting market requirements and offering robust services. And to achieve the fit, the enterprises adopt multi-layered architecture and AI, ML integrated operations. The practice of observability helps the developers understand the multi-layered architecture better with answers to the questions like what’s slow, why it’s slow, what’s broken, and what can be done to improve the performance.
What is Network Monitoring?
Network Monitoring is the practice of collecting data systematically and analyzing the same in order to keep the infrastructure and application running seamlessly. Network Monitoring has been a common practice in large and multi-layered architectures.
Monitoring becomes crucial for long-term trends and analyzing the historical data to build a powerful dashboard. In addition, monitoring helps you understand your application and its functioning and utilization. The problem with monitoring the complex distributed applications is that the production failures are not linear and hence, difficult to predict.
Telemetry
Telemetry is made of two words, Tele and Metry. Tele means distance, and Metry means measuring. Hence, Telemetry, collecting data from remote systems. One might claim that monitoring tools also collect data from remote systems. Well, the traditional monitoring tools also collect metrics from the remote servers.
The concept of telemetry is not idealized with collecting the data from various sources, but to standardize the process of collecting the data in distributed, multi-layered hybrid-cloud environments.
Cloud-native applications depend on the environment for telemetry, where the data is collected and transmitted to centralized locations for further analysis automatically.
Where Kubernetes comes with some built-in capabilities, such as Heapster. However, telemetry capabilities are integrated with the Kubernetes control panel in most of places.
There are basically three types of telemetry data which can be monitored and analyzed. Logs, Metrics, and Traces.
- Logs: Data, timestamp, and record of the events, which helps identify the system’s behavior and provide detailed and powerful insights to make data-driven decisions. It helps understand the system better, resolve issues faster with historical data and predict potential problems by learning patterns and behavior.
- Metrics: The basic fundamental of monitoring, numbers, counts, or measurement that are produced over a period of time. The metrics would provide information like memory utilization, memory used, number of requests generated and managed for a particular event or application.
- Traces: Traces are footsteps, and therefore, it leaves historical data. A trace displays the operation’s path and how it executes in a distributed multi-layered system for every transaction or request.
Observability vs. Application Performance Monitoring
The traditional APM solutions work on sampling the data. It has less than one percent of historical data to debug. Hence, in the case of failure and root cause analysis, the chances of debugging the event and resolving it with the help of APM are rare and minimal.
Even after the root cause is detected, it takes time until a retest is executed. This will increase the MTTR efforts drastically. The tools use an agent-based approach, requiring additional integrations for containers and cloud environments.
In addition, at a certain point, the data will become summary leaving you with no choice of auditing the older data to find the inefficiencies in the system because you no longer have full-fledged historical data.
Network Observability Benefits
Network Observability is not limited to IT leaders or Network admins to be benefited. It is for everyone. Here are the observability benefits of role in IT enterprises.
- Developers: By reducing the maintenance and constant manual monitoring, the observability capabilities make the developer’s life much easier. Real-time tracking, root cause analysis, and historical data enable the developers to spend less time.
- Teams: Observability provides visibility and contexts across the organization; hence, admins, managers, developers share the same view and insights about particular applications, services, and customers.
- Business: Ultimately, employees and teams perform seamless operations, resulting in better services and boosting business growth. It gives confidence to the company to make crucial decisions with the ability to debug events in case of failure.
Network Observability Use Cases
Where Net Op’s team loves monitoring, observability is widely used by DevOps and IT Ops teams. The strategy and approach of applying the practice of observability in any enterprise varies as per requirements. A few of the use cases of observability are given below.
- Troubleshooting: Detecting problems and detailed troubleshooting prevent any potential damages. Enterprises can set up the alarms or get powerful insights from the dashboard to achieve the fit.
- Proactive Approach: Rather than reacting to things with observability on board, the systems start acting proactively to secure the system before any possible issues occur.
- Continuous Improvement: The capability of reporting and log trails makes the system more intelligent and advanced day by day with historical data and behavior.
Adopting Observability
Network Observability has become essential for IT Operations and DevOps teams. The IT teams need to integrate the code into the applications in order to enable alarms. Wherewith Observability on hand, the integrations and operations can be automated, and the teams can stay alert about the upcoming events.
AIOps by Motadata comes with an observability capacity that does comprehensive IT stack monitoring from a single platform. Provides insights that help make data-driven decisions and in-synch integrations with everything on board. The solution is built with AI and ML technologies, offering rich abilities and keeping you stand firm in the market. Adopt Observability in your enterprise right away. Feel free to reach out to us at sales@motadata.com.