Knowing your network helps ensure availability, protect data, and fix technical issues. But what techniques should companies use to understand network performance? This blog will look at two popular solutions: observability and monitoring.
Observability and monitoring have similar goals. Both solutions capture network data and help diagnose problems. However, they use different techniques to achieve this goal. And while comprehensive observability platforms may suit some businesses, they will be too complex for others.
Read on to learn how observability and monitoring work, their strengths and weaknesses, and how to choose the best network analysis tools.
Key takeaways
Observability vs. monitoring: they are both network visibility solutions that capture network data and diagnose issues. Observability platforms offer comprehensive insights into the internal state of systems. Monitoring tools are less complex, using predefined metrics and thresholds to assess network health.
When to use each: Observability systems enable flexible, interactive analysis, and monitoring tools are more rigid and rely on predetermined metrics. Observability tools provide deep insights into network behavior, while monitoring offers less detailed feedback. However, monitoring delivers instant insights and alerts. Observability tools take a slower, more analytical approach.
The criteria for choosing observability and monitoring: companies must assess specific needs and budget constraints. Observability platforms offer in-depth insights into complex technical challenges. They are ideal for distributed systems. Monitoring solutions provide real-time updates and alerts to enhance security and meet compliance goals.
Telemetry and Application Monitoring (APM) are closely related visibility concepts. Telemetry uses distributed protocols to track network activity and performance. APM monitors specific applications, using dedicated dashboards, metrics, and logs to present alerts and reports.
What is monitoring?
Monitoring involves collecting and analyzing information to understand the progress of a project or performance within an IT environment. We use monitoring to assess whether projects are meeting core objectives. Monitoring tools inform the decisions of managers. They enable teams to stay on track and adapt to changing circumstances.
Monitoring uses metrics to capture information. These metrics are quantitative data measurements representing IT infrastructure or program performance. For example, monitoring metrics may include data collection about server request response rates. Metrics might also capture Central Processing Unit (CPU) and network load levels.
Components of monitoring systems usually include:
Storage: Logging metrics in inaccessible and standardized formats.
Aggregation: collecting data in relevant clusters or databases.
Visualization: presenting logging data in a usable form for analysis and decision-making.
Automation: scheduling automatic responses to monitoring outputs.
What is observability?
Observability is the ability to understand the internal state of systems to assess performance and make necessary changes. For example, cloud-native observability tools identify security vulnerabilities and track system performance in multi-cloud settings.
Observability is a design principle that informs IT deployments. An observable system enables monitoring and analysis. Engineers build networks with observation in mind, making it easier to maintain assets and make network changes.
At the same time, observability is an operational goal. Thanks to observability systems, managers can understand the context in which problems arise and take remedial action.
IT teams use observability tools to gain insights into the health of assets across an enterprise network. Algorithms derived from control theory enable tools to establish and understand relationships between data centers, on-premises assets, cloud deployments, and remote devices. Tools use "three pillars" to observe and report on system health:
Logs: text or numerical records of activity occurring within an IT system. Logs track what happened and when it happened. Logs may also cover contextual data such as user involvement.
Metrics: as discussed earlier, metrics are quantitative data points that track aspects of system performance.
Traces: records of requests made within a network environment. Traces capture network calls, microservices, and databases used by each request. This information helps diagnose choke points and other network flaws.
Key differences: observability vs. monitoring
Comparing observability vs monitoring is subtle. The two concepts are closely related but differ in critical ways.
The central difference between observability and monitoring involves how tools process information. Monitoring tools assess predetermined information. Users determine data sets in advance, narrowing their analytical frame.
By contrast, observability tools consider all information processed by IT infrastructure. They check every data flow and application to optimize security and performance. Observability tools look "inside" assets to identify the internal state of network assets.
Aside from that overarching distinction, differences between monitoring and observability include:
Flexibility: observability allows flexible and interactive interrogation of network performance. IT teams can apply multiple perspectives and tailor each analysis to find the root cause of network alerts. Monitoring is more rigid, relying on predefined metrics and visualization options to track system health.
Scope: observability platforms use high-level metrics, traces, and logs to generate system-wide insights. Monitoring uses aggregated data to deliver less detailed feedback about specific aspects of the IT environment.
Depth: an observability platform goes to the root of network problems. It works from the "inside out" to diagnose issues. Monitoring tools are more limited. They deliver alerts about IT infrastructure performance based on predetermined rules.
Speed: monitoring tools deliver insights in real time. They generate alerts regarding anomalies or security threats. Observability tools tend to take a slower, more analytical approach.
Similarities between observability and monitoring
There are many differences between monitoring and observability. However, it's important to note some core similarities.Â
In practice, the two network management concepts complement each other. IT teams require observability and monitoring capabilities to optimize performance. Similarities include:
Data analysis: both observability and monitoring solutions collect, organize, and analyze network data. They use a similar mix of logs, traces, and metrics. They also assess similar issues, including resource usage, error rates, and transaction response times.
Data visualization: monitoring and observability tools must make information accessible and intelligible to users. Software generally includes external outputs like dashboards to present data. Intuitive data visualization allows users to note trends and identify areas of concern.
Automated alerts: both concepts include an alert function. Automated analysis delivers alerts regarding security or performance issues. Alerts inform corrective actions and sharpen an organization's security posture, highlighting issues before they lead to vulnerabilities.
Troubleshooting: observability and monitoring apply root cause analysis to fix network problems. Complex distributed systems rely on observation and real-time monitoring to identify flaws. Both tools feed into investigation processes. They also help meet regulatory standards for secure DevOps and network management.
Choosing between observability and monitoring
Companies often face a dilemma when designing network solutions. Both observability and monitoring tools have their place in network management. However, given the cost of sourcing specialist tools, choosing between the two technologies is usually necessary.
An observability platform suits organizations that need in-depth insights into the internal state of networks. They are ideal for dealing with complex technical challenges and ensuring optimal performance across distributed systems. Organizations can customize the use of metrics, traces, and logs - focusing their analysis where it matters most.
Click to tweetCase study
A major global company deploys an observability platform across multiple countries and hybrid cloud and on-premises environments. Distributed agents collect performance data about client databases, data security, and data flow efficiency. Data collection helps the company manage loads and ensure the visibility of every device. Technicians can diagnose bottlenecks and triage security weaknesses before data breaches occur.
Monitoring solutions suit organizations that need real-time updates and instant alerts. Monitoring systems deliver a more superficial analysis. However, they make up for this by leveraging predefined metrics to flag potential security or performance problems before they become critical.
Click to tweetCase study
A small healthcare provider must understand and protect its network assets to comply with HIPAA regulations. The company uses a network monitoring system to track device availability and the status of protected health data. The company creates simple metrics such as tracking baselines and automating monitoring to reduce its IT workload.
Observability and monitoring compared to APM and telemetry
Let's add another dimension to the discussion by bringing in Application Performance Monitoring (APM) and telemetry. Both APM and telemetry are alternatives to standard observability tools. While they can appear similar at first glance, there are some differences to consider before choosing the right option for your network.
Observability vs. APM
APM is a specific subset of observability tools that focuses on application performance. APM tools apply metrics to network applications. Examples could include response and error rates. They also assess transaction traces to track user activity, boosting overall network security.
Observability tools take a holistic perspective across all network asset classes. APM may be part of an observability solution, but these systems typically have deeper functionality than APM alone.
Another way of looking at this is scope. Observability seeks to analyze and understand connections at a network or enterprise level. APM adopts a more modest approach, focused on how single apps interact with users and other network assets.
APM has some advantages over comprehensive observability solutions. For instance, tailored APM solutions serve CRM or accounting apps. They may also feature simplified dashboards, making life easier for inexperienced IT teams.
APM is app-specific, making it a cost-effective alternative to in-depth observability platforms. Organizations need to assess whether that is a worthwhile trade-off.
Monitoring vs. APM
APM is also a subset of network monitoring. In this case, APM tools monitor end-to-end data flows within specific applications, generally to enhance DevOps performance.
APM is used to detect flaws within applications and deliver proactive alerts when things go wrong. This could be very useful in financial environments or cloud-native customer relationship management tools. However, companies often need broader monitoring systems that track network-wide performance.
Observability vs. telemetry
Telemetry deploys automated protocols like NetFlow or sFlow to collect network and device performance data. IT teams can use telemetry protocols to execute distributed tracing and monitor dynamic cloud settings. Data collection occurs across the network, delivering real-time data flows to central dashboards.
Put like this, telemetry probably sounds similar to observability, and it is. Both telemetry and observability tools enhance the visibility of data flows and network behavior. However, they offer differing analytical depths.
Observability tools allow IT professionals to carry out deep dives into network performance. DevOps teams can use observability tools to diagnose bugs rapidly and fix flaws. Telemetry on its own is less powerful. Telemetry tools deliver granular information about network activity. However, they do not have the same level of detail and flexibility.
Monitoring vs. telemetry
Telemetry monitors network systems, including local and cloud-based assets. It generates real-time information flows that can feed into alerts and automated fixes if desired.
These functions are very similar to the network monitoring tools we've already discussed. However, standard monitoring systems are usually less powerful than advanced telemetry.
Standard monitoring systems rely on predefined rules and data metrics, allowing relatively little user flexibility. Some monitoring solutions operate pre-set thresholds or device polling. This degrades their accuracy. By contrast, telemetry operates constantly, measuring data flows without interruption.
Observe and monitor your network with NordLayer's help
Monitoring and observability tools empower organizations by collecting, aggregating, and analyzing information.
Network diagnostics rely on this knowledge to isolate flaws and identify the correct solution. And when knowledge is lacking, bad things happen. Without data collection systems, technicians handle every alert or outage on a case-by-case basis. That's hardly a recipe for efficiency or security.
Companies should take action to ensure network visibility and implement data collection solutions. NordLayer is ideally placed to help you achieve these goals.
NordLayer's solutions monitor network activity so you can take dynamic action before threats materialize or systems go down. Our visibility solutions enhance operational efficiency and help you protect data—two of the most pressing challenges for today's digital businesses.
Contact our team today and explore your network monitoring options. Understand every aspect of network activity, from suspect user connections to device posture management. And give your team the knowledge needed to respond when emergencies arise.
