My typical answer to such a question would be to start with the Golden Signals. Copyright 2018 IDG Communications, Inc. If the network operations team can monitor latency, they can see the issue while the user is first experiencing it. But quality isnt just an RTP (Real Time Transport Protocol) issue, even if that is where it is most obvious. Finally, its hard not to love how the Golden Signals avoid terminology like logs and metrics. Instead, they refer to signals. Thats nice because, although SREs are primed to think about logs and metrics (and traces, for that matter) as being separate sorts of things, the fact is that they are often overlapping categories of data, and the difference usually doesnt really matter. The PodMonitoring resource can only scrape pods in the same namespace. Thats not a bad thing. , More concretely, they map as follows: Below you can see how these metrics can be displayed in a Google Cloud Monitoring dashboard. Perhaps the greatest shortcoming of the Golden Signals is that they dont do anything to align technical outcomes with business outcomes, or help ensure that all stakeholders -- technical and non-technical -- can support reliability. In other words, in addition to using the Four Golden Signals for technical monitoring and observability, you should consider incorporating some business-centric signals into your data collection routines. We need to be able to condense insight from the vapor of data (to paraphrase Neil Stephenson). As it depends on your application how to configure this, follow the nginx-ingress documentation to create this. Prepare for the unexpected complexity of applying the Golden Signals to an actual microservices app. Which kinds of traffic. Popularized by Googles SRE book, they boil down to the idea that SREs should collect four basic types of information from the systems they support: Latency, or the time it takes for each transaction to complete. (Other well-known approaches include Brendan Greggs USE Method, or Tom Wilkies RED Method.). The controller exposes a set of metrics that we'll use to get insights into the golden signals. Perhaps the greatest shortcoming of the Golden Signals is that they dont do anything to align technical outcomes with business outcomes, or help ensure that, Conclusion: Getting more from the Golden Signals, SREs can drive the adoption of these four golden signals, all stakeholders -- technical and non-technical -- can support reliability. Here is a guide on how, But what average latency monitoring wont do is help you identify a minority of users or request types that are subject to delays. They allow us to get in front of the cycle of waiting for trouble tickets and start managing the network proactively. Historically, SREs tended to treat each of these layers of the stack as a separate entity when it came to monitoring. In that case, you need to know about the 1 percent of requests that are not going well. By Larry Zulch, Popularized by Googles SRE book, they boil down to the idea that SREs should collect four basic types of information from the systems they support: The Golden Signals have several important strengths. gke However, Cloud Monitoring is certainly less powerful compared to other solutions such as Grafana, Datadog or NewRelic. Volume of network traffic (in Gbps) would go up and the issue would occur more often, but not always. Do we care why? Theyre a great method for shaping the contours of a modern observability strategy. If youre an SRE, theres a decent chance that you live and die by the Four Golden Signals. Alongside similar concepts like the RED Method, the Four Golden Signals form the foundation for many a monitoring and observability strategy today. Errors are more than just failed requests. Alongside similar concepts like the RED Method, the Four Golden Signals form the foundation for many a monitoring and observability strategy today. Traffic, which represents the overall load placed on the system. Ensure your application is reachable through this Ingress. You learn the most after a production incident: were you able to quickly identify the cause through your dashboards? Errors, or the number of requests that result in a failure. In that case, you need to know about the 1 percent of requests that are not going well. Its not time to do away with the Golden Signals, but its worth rethinking and extending them to meet modern SRE challenges. Why do these Golden signals matter for network performance? Then you'll dive deeper into other metrics to learn what is going on.
When the metrics show that something is off, you can click on this link to go to a dashboard that shows more metrics that hopefully explain what is going on. The next Golden Signal is traffic, defined by the Google SRE team as monitoring how many requests are occurring. , Now that weve detailed all the things that the Golden Signals get right, lets look at their shortcomings. Slow is the new out. But how slow is slow? Collecting the Four Golden Signals just for an application as a whole isnt very useful because it wont give you the visibility you need to pinpoint problems that originate in a specific microservice. You can also add more links; other links might point you to the application logs or an APM dashboard. And contextualize the Golden Signals with business-oriented metrics so that you know how technical changes affect business outcomes. Network World Expand your dashboards as you learn more about your applications and infrastructure. Then there is the errors signal. But if youre an SRE considering using the Golden Signals, its worth educating yourself about what they dont do so well. And that's it! 2022, OReilly Media, Inc. All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. Instead, you need to collect at least four signals from every microservice in your application. Instead, they refer to signals. Thats nice because, although SREs are primed to think about logs and metrics (and traces, for that matter) as being separate sorts of things, the fact is that they are often overlapping categories of data, and the difference usually doesnt really matter. Make sure you look for outliers in addition to tracking averages. Whether youre monitoring a SaaS application, a containerized microservices app running in Kubernetes or a monolith hosted on bare metal, the Golden Signals cover pretty much everything youd need to know about the state of the app itself. They keep experiencing this latency for minutes at a time, but then it goes away and the application is responding normally. Having insights and/or being alerted on all these possibilities is impossible. And perhaps most importantly, errors are often a warning sign of an impending larger problem. Along similar lines, I like that the Golden Signals dont try to draw a distinction between application metrics and infrastructure metrics. So that's what we'll configure in the podMonitor. But what average latency monitoring wont do is help you identify a minority of users or request types that are subject to delays. Youd collect metrics like CPU and memory utilization from your infrastructure, while collecting request rates and error metrics from the app. Saturation, meaning how many resources your system is consuming relative to the total resources available. But they dont correlate application performance with business performance. And contextualize the Golden Signals with business-oriented metrics so that you know how technical changes affect business outcomes. Thats mainly because you often need to collect many more than just four total signals when supporting a system.
Opinions expressed by DZone contributors are their own. Lets dive into these individually. To create this dashboard in your GCP environment, you can import my JSON export of this dashboard. Its only by pairing business data with technical data that you gain real observability. Prometheus is still one of the most popular monitoring services out there. 
Make sure you look for outliers in addition to tracking averages. Here is a guide on how SREs can drive the adoption of these four golden signals and why. Instead, you need to collect at least four signals from every microservice in your application. There can be many reasons why your application is misbehaving. Unless were talking about IoT or specialized systems, the answer is no. And, how can you use this information to guide your network performance monitoring strategy? It states, pretty straightforwardly, that the four most important metrics to keep track of are the following: Get Hands-On Infrastructure Monitoring with Prometheus now with the OReilly learning platform. Traffic, which represents the overall load placed on the system. This will configure Prometheus to start scraping the nginx-ingress metrics. However, we will create a podMonitor resource for the Managed Prometheus service instead. How to Improve Upon Googles Four Golden Signals of Monitoring, What Is xAPI: All You Need to Know to Get Started, Spring Boot Performance Workshop With Vlad Mihalcea. In other words, in addition to using the Four Golden Signals for technical monitoring and observability, you should consider incorporating some business-centric signals into your data collection routines. A second challenge when using the Golden Signals approach is that its not very helpful for identifying and troubleshooting outliers within your data. Integrates with PagerDuty, Opsgenie, Jira, Google Docs, 30+ tools. nginx-ingress Where to begin? It's an interesting prospect not having to deploy and maintain Prometheus ourselves anymore but to leave that in the capable hands of Google. It doesnt matter from an observability standpoint. Once we know what matters, we can start looking at filtering out what doesnt. Aruba service overlays existing infrastructure with virtual networks, Arista bundles edge networking gear for small enterprises, REVIEW: 5 top hardware-based Wi-Fi test tools, Sponsored item title goes here as designed, Riverbed wins 7-vendor WAN optimization test. The serviceMonitor CRD is part of the prometheus-operator and will configure it to start scraping the nginx-ingress metrics. The Golden Signals are comprehensive from a technical standpoint. Contributor, If youve ever been on a VoIP call that was very responsive, but you still couldnt easily understand the words being spoken, youve obviously experienced low quality. In Kubernetes, for example, CPU utilization isnt necessarily a good measure of how much of the total available CPU resources the pod is using, because Kubernetes abstracts the pod from the underlying physical infrastructure and may impose arbitrary resource limits. Historically, SREs tended to treat each of these layers of the stack as a separate entity when it came to monitoring. But, how do we do that? Whether youre monitoring a SaaS application, a containerized app running in Kubernetes or a monolith hosted on bare metal, the Golden Signals cover pretty much everything youd need to know about the state of the app itself. , Tags: I always prefer to have at least 2 layers of dashboards. Look for lines such as the following to change: The metric type here is the one that maps to the Traffic golden signal. In other words, even though there are only four signals, theyre comprehensive, making this a simple yet effective way to approach monitoring and observability. The Golden Signals are also advantageous because they address any type of system. This dashboard displays the most important (at least the golden signals) metrics for all services.
For example, tracking average latency for application requests is great if you want to know how long it takes your app to handle most transactions. Likewise, you may also need to collect signals from your orchestrator, your cloud environment, your network, and any other layers in your software stack. However, this is only the beginning. Collecting the Four Golden Signals just for an application as a whole isnt very useful because it wont give you the visibility you need to pinpoint problems that originate in a specific microservice. Automate tedious processes. They cover all of the information youd want to know about an application.
Would I have more services, I would add relevant metrics for that service to this dashboard. Theyre a great method for shaping the contours of a modern observability strategy. These are the metrics that can tell you if something is going on. Someone who is always late reduces it. In many ways, the Golden Signals excel at distilling complex monitoring processes down into a core set of easy-to-digest concepts. Was the change from no problem to rude a straight line, or were there steps of increasing rudeness? This is what the Dive Deeper link points to in the below Application Landscape. Whether youre monitoring a SaaS application, a containerized. If you generate logs in AWS CloudWatch based on metrics that you collect from an AWS service, for instance, are those metrics or logs? Terms of service Privacy policy Editorial independence. Popularized by Googles SRE book, they boil down to the idea that SREs should collect four basic types of information from the systems they support: The Golden Signals have several important strengths. Prepare for the unexpected complexity of applying the Golden Signals to an actual microservices app. Saturation, meaning how many resources your system is consuming relative to the total resources available. The Golden Signals helps teams avoid getting stuck in the mud of trying to force data into different buckets, and helps them focus on the data itself, no matter what its form. This blog post will dive into the golden signals and share how you can get started with these signals in Google Cloud using Managed Prometheus and the nginx-ingress controller. Change my-service to the name of the Ingress that you want to monitor. Join the DZone community and get the full member experience. Right now I'll focus on the metrics that the nginx-ingress controller exposes. Doing so is the only way to know whether a performance or availability issue lies in your application itself, or one of the external resources on which it depends. Youd collect metrics like CPU and memory utilization from your infrastructure while collecting request rates and error metrics from the app. Or are both happening at the same time? The user makes a request of a remote application. Once that is determined, where exactly is the problem located? , The golden signals are: I recommend reading the previous link to learn more about the golden signals and monitoring in general. Again, no one is saying the Golden Signals should go away. The most active servers. Finally, its hard not to love how the Golden Signals avoid terminology like logs and metrics. Instead, they refer to signals. Thats nice because, although SREs are primed to think about logs and metrics (and traces, for that matter) as being separate sorts of things, the fact is that they are often overlapping categories of data, and the difference usually doesnt really matter. (A not infrequent occurrence.) They wont tell you how changes in application behavior correlate with increases in customer support requests, for example, or with fluctuations in the length of user sessions (which are a metric that serves as a proxy for user engagement and satisfaction). And, of course, its usually the outliers that are the first signs of trouble. Let's ensure we have everything we need to get some visibility into the nginx-ingress metrics in Google Cloud Monitoring. Clearly, we want to take advantage of our network capacity, but we also need to allow for spikes in utilization. Latency, delays in meeting requests, may be the most useful signal, if for no other reason than that end users so often experience it. Google's rationale regarding monitoring is quite simple. Copyright 2022 IDG Communications, Inc. New Oak Ridge supercomputer outperforms the old in a fraction of the space, Nvidia CEO says he is open to using Intel for chip fabrication, Global enterprise IoT market strong but faces challenges. These are great ways to test if your dashboards display usable information. View all OReilly videos, Superstream events, and Meet the Expert sessions on your home TV. Finally, let's create the podMonitor. This built-in service in Google Cloud allows you to gain visibility into your applications and infrastructure. We need an Ingress resource that exposes an application in your Kubernetes cluster through a GCP load balancer. Latency, or the time it takes for each transaction to complete. It will also alert you to sudden spikes in latency that could reflect a significant issue that impacts many users. Finally, they started measuring the number of network conversations, and found that as soon as it hit about 750,000 on a 10G link, a piece of their infrastructure hit the wall, no matter the type or amount of traffic. Think of it as standing in for the quality of the user experience. The Four Golden Signals are a set of recommendations about which types of data to collect when monitoring and observing systems. Likewise, you may also need to collect signals from your orchestrator, your cloud environment, your network and any other layers in your software stack. They must determine whether the latency is occurring because the network is introducing delays or because the application server is responding slowly. One arguable problem with the Golden Signals is that, although they seem very simple on the surface, they are difficult to apply to a real-world monitoring or observability strategy. The easiest way to do this is with Helm: Important: do not enable the serviceMonitor (controller.metrics.serviceMonitor.enabled). Even though we seldom see persistent data corruption, where some bit gets flipped in the payload, for example, poor TCP (Transmission Control Protocol) quality can cause a host of problems. This group has written a (free) book called Site Reliability Engineering, edited by Betsy Beyer, et. But increasingly, the Golden Signals are no longer enough to achieve optimal monitoring and observability outcomes. Just when theyre about to try their request again, they get a response. Now that weve detailed all the things that the Golden Signals get right, lets look at their shortcomings. Finally, Google Cloud Monitoring is a simple and relatively cheap way togain more insights into your applications and infrastructure - when you're using GCP of course. Especially interesting is that metrics scraped by Managed Prometheus are made available automatically within Google Cloud Monitoring. So, a third of the time (and much higher in some organizations) we dont know about an issue until a user complains? But increasingly, the Golden Signals are no longer enough to achieve optimal monitoring and observability outcomes. One arguable problem with the Golden Signals is that, although they seem very simple on the surface, they are difficult to apply to a real-world monitoring or observability strategy. But if youre an SRE considering using the Golden Signals, its worth educating yourself about what they dont do so well. Thats not a bad thing. kubernetes Thats bad if youre trying to achieve SLOs of 99 percent or greater. The Golden Signals helps teams avoid getting stuck in the mud of trying to force data into different buckets, and helps them focus on the data itself, no matter what its form. If you generate logs in AWS CloudWatch based on metrics that you collect from an AWS service, for instance, are those metrics or logs? And goes away. The Golden Signals are comprehensive from a technical standpoint. Over 2 million developers have joined DZone. I can also recommend organizing game days or performing other chaos engineering practices to test the value of your dashboards. By default, the nginx-ingress controller exposes these metrics through port 10254. It doesnt matter from an observability standpoint. It doesnt matter from an observability standpoint. Get full access to Hands-On Infrastructure Monitoring with Prometheus and 60K+ other titles, with free 10-day trial of O'Reilly. are a set of recommendations about which types of data to collect when monitoring and observing systems. I know of a large enterprise that had a periodic problem on a network segment. The place to start is by defining network performance in terms that matter to the end user. What other metrics should have been there to identify the cause more quickly? But what average latency monitoring wont do is help you identify a minority of users or request types that are subject to delays. A good way to monitor traffic is to view the number of network conversations. Get in touch! OReilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers. The Golden Signals are also advantageous because they address any type of system. Incident management on Slack. A saturated network can cascade into very bizarre failure modes, where the error and retry messages add to the traffic, making the situation worse. We used to talk about outages, but they have become less frequent. Therefore, the golden signals focus on factors that would be noticeable to your end-users when your application is having issues. |. Network operations teams are flooded with information, but too much information is little better than noise. If youre an SRE, theres a decent chance that you live and die by the "Four Golden Signals." The downside is that the other tools require more effort (when self-hosting Grafana) or are more expensive. Take OReilly with you and learn anywhere, anytime on your phone and tablet. ), the Application dashboard shows potential causes (what is going on?). Earlier this year, Google made Managed Prometheus generally available. Knowing the answer to that is often enough to solve the problem. The book questions some of our traditional thinking about IT. One of the questions asked, what percentage of network performance issues were first reported by end users, rather than discovered by the network operations professionals. The average answer was 39 percent, and the median answer was 35 percent. Perhaps the greatest shortcoming of the Golden Signals is that they dont do anything to align technical outcomes with business outcomes. It will also alert you to sudden spikes in latency that could reflect a significant issue that impacts many users. Thats mainly because you often need to collect many more than just four total signals when supporting a system. For example, tracking average latency for application requests is great if you want to know how long it takes your app to handle most transactions. The Four Golden Signals are a set of recommendations about which types of data to collect when monitoring and observing systems. Nothing happens. As mentioned, the nginx-ingress metrics give us insights into three of the golden signals. Were you alerted of the issues in time? As we'll see, the nginx-ingress metrics will give us insights into the other three signals. The nginx-ingress controller is one of the most popular Ingress controllers for Kubernetes. gcp There was some alignment, but, frustratingly, not enough to establish the root cause. There was a recent study by Enterprise Management Associates that queried 250 network professionals. A second challenge when using the Golden Signals approach is that its not very helpful for identifying and troubleshooting outliers within your data. Its not time to do away with the Golden Signals, but its worth rethinking and extending them to meet modern SRE challenges. What's primarily important is that these signals (counter-intuitively) provide insights into symptoms of issues instead of causes. Retransmits, dropped frames, even latency. Knowing that, the problem was solved quickly. A good reason certainly increases our tolerance. One is that they do a nice job of covering all of the data points an SRE would typically want to collect from an application or system. The problem isnt that we dont get enough reports. When it comes to monitoring, one of the key concepts it describes is what the team calls The Four Golden Signals or latency, traffic, errors, and saturation. Within a few minutes, the metrics should appear in Google Cloud Monitoring. Time of day. Strangely, though, it didnt correlate with any of the metrics they monitored. Doing so is the only way to know whether a performance or availability issue lies in your application itself, or one of the external resources on which it depends. observability In Kubernetes, for example, CPU utilization isnt necessarily a good measure of how much of the total available CPU resources the pod is using, because Kubernetes abstracts the pod from the underlying physical infrastructure and may impose arbitrary resource limits. All of these only loosely corresponded to the issue. Do we try to understand the user experience and adjust our performance monitoring to reflect it? Do you rely on other signals? If so, share them in the comments section so we can have an open dialog. The four golden signals - coined by the Google SRE book - can be considered a guide as to what at least to monitor for your applications. Network performance follows many of the same dynamics. Get Mark Richardss Software Architecture Patterns ebook to better understand how to design componentsand how they should interact. How much of this mildly painful experience do they tolerate before they decide to create a trouble ticket? In that case, you need to know about the 1 percent of requests that are not going well. Thats bad if youre trying to achieve. The Golden Signals are also advantageous because they address any type of system. You now have a dashboard that displays the golden metrics for your application. As you can see, when evaluating how to manage network performance both to support ongoing operations and to prepare for future digital transformation the four Golden Signals can play a significant role.
But they dont correlate application performance with business performance.
Or is the only practical answer to just wait until someone complains? If Google Cloud Monitoring is too limiting for you, know that more powerful tools exist that you might want to give a try. One is that they do a nice job of covering all of the data points an SRE would typically want to collect from an application or system. The second layer is the Application dashboard. Larry Zulch is Executive Vice President and GM of Savvius, Inc., a LiveAction company, where he directs company strategy and execution into the network and application performance, management and diagnostics marketspace. You can now seamlessly include whatever metrics you scrape with Prometheus in any Google Cloud Monitoring dashboard, giving you easy insights into GCP infrastructure and your applications. Follow me on Twitter: @SanderKnape. Finally, its hard not to love how the Golden Signals avoid terminology like "logs" and "metrics." of 99 percent or greater. Deploy the following to your cluster: Notice that this resource is installed in the same namespace as the nginx-ingress controller. If theyre three minutes late, no problem, but if theyre thirty minutes late, its rude. What challenges do you and your organization face when setting performance standards?