The Best Strategies When It Comes to Observability
Observability is a game-changer for software developers and managers as it allows them to have real-time information and updates about how their site or app is functioning. It also offers invaluable insights into issues occurring within the site.
This piece will explore observability best practices to employ to get the most out of observability for your website and apps.
The term and idea of observability were first coined in the 60s. However, observability tools only hit the market in the early 2000s. On top of this, observability platforms have only become effective and useful within the last few years with improvements in technology and an increase in demand. This demand is expected to continue increasing over the next few years.
Observability differs from monitoring as it focuses on providing insight into what’s happening in the system rather than just looking at performance metrics.
For example, if you are running an e-commerce site, you can use observability to see which products are selling well, which ones aren’t, and why. You can also use this data to optimize your marketing campaigns by targeting specific products that are performing poorly.
The reason observability is so effective is that it reveals the running condition of the program. You can’t make good choices if you don’t know the current situation. Consequently, observability is essential for comprehending the behavior of your applications.
To get the most out of your observability investments, you need to clearly understand what observability is and the best practices to use when implementing your observability strategy.
What Is Observability?
Observability is the ability to monitor and analyze the behavior of an application. Because of this, you have complete insight into the functioning of your app. In addition, it helps you gain valuable insights into how users interact with your application, whether they are experiencing any errors, and so forth.
Observability is more than just monitoring your website. Monitoring a website or application involves collecting performance metrics and analyzing those metrics to determine how well the application performs. However, observing an application means more than that. It means looking inside the application and seeing exactly what’s happening.
The key benefit of observability is that it enables you to gain deep insights into how your application is behaving. With these insights, you can identify problems before they occur, fix them, and find the source of issues in your system more efficiently, which can have massive advantages for your business.
Nearly half of those polled (53%) by Forbes, in fact, blame app problems for lost business or customers, which means that issues in your apps create issues for your customers and hurt user satisfaction.
The early 2000s saw its introduction, but the past several years have seen its widespread adoption. With the rise of microservices architecture, observability has become even more important.
Microservice architectures allow you to break down large monolithic applications into smaller services. As a result, they are easier to manage and deploy. However, they require a different approach to debugging and monitoring.
There are many different approaches to putting observability into practice. While others favor using open-source software, others prefer the ability to design their own unique solutions from scratch.
Some observability practices are more effective than others. See the best practices to use for your business next.
Best Practices for Observability
There are many different practices employed by developers involving observability. However, learning about the best practices to maximize efficacy and efficiency is worthwhile if you want to get your money’s worth from your observability investment.
Failing to implement proper observability practices is a disaster for your business. Observability is a sizable investment for a company, and using it inefficiently can be wasteful. That is why you need to know the best observability practices and how to implement them effectively.
The best practices for observability are:
- Focusing on instrumentation
- Keeping production top of mind
- Streamlining understanding between developers and operations
See below for more on these.
Focus on instrumentation
Instrumentation refers to the process of adding additional information to your code. Profiling, tracing, and logging are all part of this. With these instruments, you may collect and analyze data related to your application. The goal is to provide insight into how your application behaves.
While the instrumentation is useful, you should use it sparingly. The reason is that it adds overhead to your application. You don’t want to add too much instrumentation because it will slow down your application.
If you do decide to add instrumentation, focus on the following areas:
All of these are valuable tools for understanding how your application works.
When you think about instrumentation, you should consider two main types: code instrumentation and non-code instrumentation.
Code instrumentation involves modifying the code itself. Non-code instrumentation involves using external tools to gather data.
Code instrumentation is often used for logging events, tracing calls, and profiling your application. For instance, you could write a new library that logs every time a user clicks on a button. Then, you would be able to view all the actions performed by users.
Non-code instrumentation is typically used to gather data about your environment. Examples include using a tool like New Relic or Splunk to monitor your server infrastructure.
Keep production top of mind.
Production observability should be kept as a priority. It’s easy to forget production observability after deploying an application. However, if your application lacks the necessary observability, you will be unable to determine what is wrong and how to fix it.
To keep production observability top of mind, you should make sure that you understand the following:
- What type of observability does your application require?
- How frequently does your application need to be observed?
- Where is your application hosted?
- Is there any special configuration required in order to observe your application?
You have to ensure that production is at the forefront of your thoughts at all times so that you don’t overlook any mistakes. To accomplish this, you need to ensure that you have a solid understanding of the functionality of your application.
After deployment, you should ensure you have enough visibility into your application to identify problems before they occur.
The observability of production can be broken down into two primary categories: alerting and passive monitoring.
Alerting in the context of production observability is the practice of sending notifications to someone whenever there is something unusual happening.
An example might be sending an email to notify someone when a particular error occurs. Alerting is useful because it allows you to respond to issues quickly.
Did you know that studies indicate approximately 38% of U.S. organizations lost $1 million or more due to network downtime in 2020, with many losing $1 million or more from a single outage?
This case highlights the need for urgent responses to outages offered by alerting.
Passive monitoring is the practice of collecting data about your application automatically. Passive monitoring is useful because it helps you understand how your application performs under normal conditions.
For example, you may notice that certain requests take longer than others. If you were to perform active monitoring, you would have to manually trigger each request to see which one takes longer. With passive monitoring, you can simply wait until the next scheduled interval and then capture the data.
The key difference between passive and active monitoring is that passive monitoring collects data passively. In other words, passive monitoring doesn’t require manual intervention. But on the other hand, active monitoring requires manual intervention.
Streamline understanding between developers and operations
DevOps is a term that has been around for a while now. However, many organizations still struggle to implement DevOps successfully.
The reason is that DevOps teams tend to focus on development and operations separately. Unfortunately, this means that developers and operations staff rarely communicate effectively. As a result, both groups end up working independently.
This situation leads to a lack of understanding between developers and operations. For example, if a developer makes changes to code without consulting operations, the results could lead to unexpected errors.
To avoid these situations, you must streamline communication between developers and operations. You can do this by creating a shared repository where both groups can store their work. The shared repository will allow everyone to access the same information.
Doing this allows you to get better insight into what’s going on. Failing to do so can also interfere with your observability strategy and efficacy. To achieve this, you need to create a culture where everyone understands their role. In addition, it would help if you also encouraged cross-functional collaboration.
Finally, you need to provide training and support to DevOps teams to help people work together more efficiently.
Get Ahead of the Game with Observability
Observability is important for all applications. Therefore, it’s especially crucial for mission-critical systems like financial services or healthcare.
However, most organizations still fail to plan properly for observability. Consequently, they tend to overlook the importance of observability and end up spending too much time and money on it.
Remembering the three best practices outlined before is integral to your observability implementation for raising your observability level.
Start planning for observability in your business today to get ahead of the game. You can use TelemetryHub to monitor your application performance and gain insights into its behavior.
Once you’ve done that, you’ll be able to make better business decisions and continuously improve your software systems.
If you are interested in discovering more about how integrating open telemetry and observability into your application’s infrastructure could significantly boost its performance, explore TelemetryHub.
People Also Ask Questions
We answer your observability questions.
How can observability be improved?
You can improve observability by increasing the number of metrics available. You can also increase the frequency at which those metrics are collected. You should always be gathering as much data as you can in order to improve your system.
You should also try to collect that information as frequently as possible. If you’re collecting metrics from multiple sources, you should combine them into one report. That way, you can see how each metric affects other metrics.
What are the three pillars of observability?
Metrics, logs, and tracing are the backbone of an observability system. Metrics measure how well an application performs. Logs record events that occur during runtime. Tracing allows you to follow execution flow through code. Let’s take a deep dive into these three pillars.
Metrics measure application performance.
When you think about observability, you probably think about metrics. These are the measurements that tell you whether your application is performing well.
For example, you might measure response times, throughput, and error rates. You might even measure the amount of memory used by your app.
You can potentially gain insight into the functioning of your app by using these metrics. Furthermore, when employed correctly, metrics can indicate problems and bottlenecks before they become critical.
Logs record runtime events
Logs record everything that happens during runtime. This record includes errors, exceptions, and user interactions.
These records contain valuable information about your application. For example, they can show you when users have trouble logging in or if there are any security vulnerabilities.
Tracing follows execution flow through code.
Tracing is a technique that lets you follow execution flow through your code. For example, with tracing, you can find out where your application crashes, what causes it to slow down, and how long it takes to complete certain tasks.
It’s important to note that not every log entry will necessarily lead to a trace point. Some logs may just indicate that something happened. But some logs may actually cause your program to execute different code paths.
In these cases, tracing can determine which path was taken.
What is service observability?
Service observability is about observing the state of individual services within an application instead of a general overview of how the system operates. Service observability is useful when trying to troubleshoot issues affecting specific services.
For example, if one of your services is slow, you might want to observe that service specifically. By doing so, you’ll know exactly why that service is slow.
What are the best practices for monitoring?
Data gathering alone is insufficient for effective monitoring. It is necessary to examine monitoring data to ensure optimal application health. To implement monitoring effectively, your operations team needs to remember the following monitoring practices.
- You need to understand which metrics matter most to your business. In addition, you need to know how each metric affects your business.
- The entire application stack must be in your line of sight. If you don’t, you won’t be able to detect any sluggishness or other problems.
- There needs to be a method of swiftly scanning the data. And if you do that, you’ll waste too much time staring at useless numbers.
- It’s crucial that you learn how to decipher the information at hand. If you don’t, you’ll waste time analyzing data that doesn’t provide actionable insight.
How do you achieve observability?
Choosing the right observability platform is the best way to achieve observability in your business. Implementing the following best practices for efficient observability will also be beneficial:
- Focusing on instrumentation
- Keeping production top of mind
- Streamlining understanding between developers and operations
However, there is more to achieving observability than employing the correct practices.
You also need to understand what observability means for your organization. This practice includes understanding the benefits of observability, determining who will be responsible for it, and deciding whether to outsource it.
What is the observability framework?
An observability framework is a set of tools that helps you collect, store, and analyze data from different sources. This includes things such as metrics, logs, and tracing.
Why should I choose an observability framework?
Choosing an observability framework allows you to focus on collecting and analyzing data instead of managing infrastructure. It also has other uses, such as:
- It makes finding problems easier because you can see where they occur.
- It allows users to monitor the efficiency of their applications.
- It provides insights into the behavior of your users.
- It enables you to identify bottlenecks.
What are observability tools?
An observability tool is a set of monitors and logs used to keep tabs on your systems and applications. Unlike standalone monitoring solutions, observability technologies give businesses continual visibility into and feedback on their systems. In addition, they help you gain deep insights into your software and hardware environments.
Other examples of observability methods include machine learning and artificial intelligence (AI).
There are many different ways to approach observability; machine learning and AI are only two examples. In fact, 90% of respondents say they use machine-learning tools in their observability. Using these tools allows automation to resolve issues without human intervention.
What is observability tracing?
Tracing is a technique that records information about the program’s execution path. It’s often used to debug complex software bugs.
Tracing finds and pinpoints the source of any bugs or problems in your system.
This method allows your software teams to resolve any issues quickly. As a consequence, resolving them enhances user experience.