What Do You Monitor In A Distributed System?
7 minutes
Distributed systems are responsible for many different tasks and processes that need to be monitored and managed. In this article, we will explore what you should monitor in a distributed system, including network communication, resources, and performance.
What is a distributed system?
Distributed systems, according to Tim Berglund, are a collection of independent computers. This collection is a single computer to the user, such as a monolithic application communicating with a database.
A distributed system typically consists of multiple nodes, which are connected by a network. The nodes may be located in the same physical location, or they may be spread out across different geographical areas.
Distributed systems are often complex systems with many moving pieces. Engineers ensure that these many pieces communicate and appear to the end-user as a single service.
Popular services like Netflix, Amazon, WhatsApp, Google, and Salesforce need a lot of features. These features include login functionality, user profiles, relational and object databases, content delivery networks, and many other components served up to the user as one service.
Why should you monitor your distributed systems?
You should monitor distributed systems because of their considerable complexity. Monitoring helps you to:
- Analyze long-term trends
- Send alerts quickly
- Determine what metrics to display on dashboards
- Conduct ad hoc retrospective analysis
In software development and operations, engineers use distributed tracing to track user transactions within an application. A tracing system analyzes this process, enabling developers to identify bottlenecks, application errors, latency, and other issues.
Distributed tracing operates on a distributed services infrastructure. It would be impossible to effectively monitor an application built on a microservices architecture and running on a globally distributed system without distributed tracing.
What do you monitor in a distributed system?
Latency, traffic, errors, and saturation are the most important variables to track. They are related to the metrics you monitor in your microservice such as duration, rate, and errors.
Latency
Latency is the duration between sending a request and receiving a response. To account for differences in network speed, you measure latency from the client-side.
Traffic
Traffic measures the number of requests traversing a network, and it allows you to distinguish between capacity issues and poor system settings.
Errors
Errors provide information regarding infrastructure misconfigurations, flaws, and broken dependencies. For instance, an increase in the error rate could indicate the failure of a database.
Saturation
Saturation defines the load on your server resources, and every resource has a limit after which performance will degrade. It takes understanding your distributed system to know which parts of your service could become saturated first.
White-box monitoring
White box monitoring relies on metrics such as logs, database queries, or an HTTP handler emitting internal information disclosed by the system.
Whitebox monitoring evokes a sense of transparency. It acts like a window that you can use to watch what happens inside a building. It reveals the inner workings of your services to your engineers.
Whitebox monitoring provides you with significant advantages in operations and product insights.
Operations Insights
Operational monitoring helps to keep your system alive and healthy.
Product Insights
Operational monitoring helps build services the right way, and its insight monitors help you build the right thing.
Black-box monitoring
Blackbox testing includes testing behavior that is visible to the user. The term BlackBox evokes a sense of intrigue. When you undertake Blackbox monitoring, you cannot see into the system.
You may monitor the software’s traffic and its CPU and memory consumption. But with Blackbox monitoring, you have no clue what is occurring within the system or what queries you execute.
You can also perform black-box monitoring by:
- Tracking networking devices
- Analyzing resource use at the hypervisor level for all virtual machines running on the hypervisor
- Alerts created on hard-disks are liable to cause challenges
Black-Box Versus White-Box monitoring
System administrators and DevOps engineers are accountable for black box monitoring of services, including servers. DevOps engineers can perform white-box monitoring depending on the organization they work in.
An advantage of black-box testing is separating users’ and developers’ perspectives. In contrast, black-box testing becomes inefficient due to the tester’s lack of knowledge about the software system.
White box testing supplies us with an understanding of the system’s internal workings. At the same time, it requires high-level knowledge of the internals of the software under test.
How do you implement monitoring and logging?
Logging aims to maintain an archive of application events. Log messages provide information that assists in identifying the source of performance issues.
Using the following best practices, you can maximize your logging and monitoring solutions:
Run logging and monitoring services concurrently
To optimize the benefits of logs and metrics, send log data to your monitoring tool. Storing log data on disks is a significant resource drain and a potential barrier in the workflow.
Use organized log data
Structure your data, so it is simpler to find, index, and store. Structured data supplies your monitoring tool with unique identifiers, and these help your monitoring tool determine issues customers face using your service.
Use structured log data
Structured data provides a comprehensive view of what transpired and can supply your monitoring tool with unique identifiers, such as the customer ID that encountered the mistake.
Make optimal use of log data
Log data contains information about your apps, underlying infrastructure, and databases. Use your system trends to conduct precise comparisons.
You can also use log data to collect and visualize data based on the requirements of your business. Having statistical data sets improves the accuracy of your analysis.
It also helps you make intelligent business decisions.
The challenges of distributed systems
Distributed systems are a key part of modern technology, and they are growing in popularity. However, they present a number of challenges that need to be overcome.
Security
Securing a distributed system is more complex than securing a centralized system due to the number of systems involved.
Startup Cost
Suppose your initial system design is that of a distributed system. It will be more expensive to set up since you will need to configure nodes, which is not the best option financially.
Complexity
Compared to a centralized system, server-side management is complex, and this is because you will be managing more computers. Scaling a distributed system is a complex process, challenging to manage and maintain.
Troubleshooting Difficulty
Troubleshooting is difficult and time-consuming as the number of computers tracked increases.
Benefits of distributed systems
The distributed nature of delivering distributed systems has a number of benefits, including:
Efficiency
Distributed systems involve a network of computers, so one of the main benefits is that they can be more efficient.
Increase Fault Tolerance
Distributed systems are more fault-tolerant than centralized systems. When an error occurs, you can switch out faulty computers reducing system downtime.
Low Latency
Distributed systems make things faster. By making sure the workload shared is equal among the computers, you reduce the system’s latency.
Reduce Cost of Scale
Scaling a distributed system is less expensive compared to a centralized system. You only need to work with the computing power you need for distributed systems.
What is monitoring and observability?
Monitoring allows SREs to watch and understand their systems using predefined metrics or logs. While observability is how well you can deduce a system’s internal state from its output.
To effectively practice monitoring and observability, your team should be able to give regular reports on the health of your systems.
What are monitoring best practices?
- Identify what to monitor: By identifying the import metrics, you channel your effort into mitigating challenges found in these areas.
- Embed security in your systems: When you secure your monitoring systems, you prevent hackers from tampering with it.
- Create alerts: Your monitoring systems should alert you when it discovers anomalies.
Monitoring and Reliability
Reliability tells you a system’s state judging by logs from monitoring services. Highly reliable systems experience fewer downtime and failures.
When designing systems, embed reliability into your design as poorly designed systems are less reliable. Monitoring methods assess an application’s accessibility, availability, performance, and reliability. These metrics give information about customers’ experience with a service.
Investing in proactive and adaptive incident response systems and management helps develop reliable services.
Some benefits of reliability and monitoring include:
- A reduced cost of system maintenance
- Fulfilment of customer expectations
- Reduces the time spent in resolving system failures
- Improves servers’ performance by identifying bottlenecks
SRE monitoring tools
As an SRE, you can use monitoring tools to assist you in developing better monitoring systems. It is best to use tools compatible with your systems.
Some of these tools have secure logging and alerting systems inbuilt. Some of these tools are listed below: