Prometheus – Shawn Deggans

As a new engineer, understanding cloud-native observability is important for several reasons.

First, it is a key component of cloud-native application development. It uses monitoring and observability tools native to the cloud, designed to work seamlessly with cloud-native applications. This helps build, deploy, and manage applications more effectively.

Second, cloud-native observability provides better visibility and troubleshooting. It provides a comprehensive view of the application and its underlying infrastructure, helping to identify and troubleshoot issues quickly.

Third, it promotes better collaboration and DevOps culture. By providing insights into the performance and behavior of the application, it becomes easier for different teams and developers to work together.

Fourth, it allows for better security. By using monitoring and observability tools native to the cloud, it enables quick detection and response to security threats.

In summary, understanding cloud-native observability is important for building and deploying applications in a cloud environment. It is a key component of cloud-native application development, provides better visibility and troubleshooting, promotes better collaboration and DevOps culture, and allows for better security. It is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about cloud-native observability. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

“What is Cloud Native Observability” by new relic: https://newrelic.com/blog/best-practices/what-is-cloud-native-observability
“Cloud monitoring guide: Observability” by Microsoft: https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/manage/monitor/observability
“What is Observability? ” by splunk: https://www.splunk.com/en_us/data-insider/what-is-observability.html

Intermediate:

“Cloud-Native Observability with AWS” by AWS: https://aws.amazon.com/cloudops/monitoring-and-observability/?whats-new-cards.sort-by=item.additionalFields.postDateTime&whats-new-cards.sort-order=desc&blog-posts-cards.sort-by=item.additionalFields.createdDate&blog-posts-cards.sort-order=desc
“Cloud monitoring guide: observability” by Microsoft: https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/manage/monitor/observability
“Implementing observability for always-on Ecommerce experience” by Google: https://cloud.google.com/blog/products/management-tools/observability-on-google-cloud

Advanced:

“The Definitive Guide to Observability in Kubernetes” by observeinc: https://www.pluralsight.com/courses/advanced-cloud-native-observability
“Kubernetes Observability 101: Tools, Best Practices, and More” by Cloudzero:

Videos to Watch

LF Live Webinar: Kubernetes Observability with OpenTelemetry and Beyond

Martin Fuentes and Cedric, product managers at Instantana, discussed Kubernetes resource management and how to observe Kubernetes workloads. They explained how CPU and memory are the most important resources managed by Kubernetes, and how requests and limits can be configured for containers. They also discussed the different types of scaling, such as horizontal and vertical scaling, and how HPA (Horizontal Pod Autoscaling) can be used to automatically scale containers.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different observability tools such as Prometheus, Grafana, and Elasticsearch. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of observability, you can begin to explore the underlying concepts and technologies such as Kubernetes metrics, logging, and tracing. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Observability is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of observability, such as metrics collection, log aggregation, and tracing.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with observability for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using observability tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Ok, let’s talk about observability. It’s a pretty important concept to understand, especially if you’re working in a DevOps culture. Even if you’re not, it’s a great practice to start using when you think about building out your solutions.

So, what is observability? Essentially, it’s the ability to understand the internal state of a system by observing its external behavior. This means that you can use metrics, traces, and logs to understand what’s happening inside your system, even if you don’t have direct access to the internal state.

There are three main principles of observability:

Measurability: The ability to collect and aggregate data from your system. This includes metrics, traces, and logs.
Understandability: The ability to understand the data that you collect. This includes using visualization tools and dashboards to make sense of the data.
Explainability: The ability to explain the data that you collect. This includes using tracing and logging to understand the cause of issues.

So, how does observability fit into a DevOps culture? Well, in a DevOps culture, you’re focused on smooth, but rapid development and deployment. This means that you need to be able to quickly understand and fix issues that arise in your system. Observability gives you the tools to do that, by providing a way to understand the internal state of your system.

Now, let’s talk about some tools that can help with observability on Kubernetes. Here are a couple of popular options:

Prometheus: Prometheus is an open-source metrics collection and monitoring tool. It’s great for use cases where you need to collect and aggregate metrics from your system.
Jaeger: Jaeger is an open-source tracing tool. It’s great for use cases where you need to understand the cause of issues in your system.

Both of these options are great choices for different types of observability, and they’re both built specifically to work with Kubernetes.

So, what are the consequences of not practicing observability? Well, if you’re not practicing observability, you’ll have a hard time understanding what’s happening inside your system. This means that you won’t be able to quickly fix issues that arise, which can lead to downtime and lost revenue. Additionally, you won’t be able to understand the performance of your system, which can lead to poor performance and a bad user experience. So, observability is a crucial practice to ensure the smooth running of your system.

So, that’s the basics of observability. It’s a powerful tool that can help you build robust and scalable solutions on Kubernetes. If you have any more questions, feel free to ask!

Connect with Shawn

Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

Shawn’s LinkedIn

As a new engineer, understanding the concept of logging and monitoring is important for several reasons.

First, logging and monitoring are key components of cloud-native application development. They involve collecting, analyzing, and visualizing data from an application and its underlying infrastructure. By understanding how logging and monitoring work, you can build, deploy, and manage cloud-native applications more effectively.

Second, logging and monitoring provide better visibility and troubleshooting. By collecting, analyzing, and visualizing data, you can understand the behavior and performance of the application, identify problems, and troubleshoot issues quickly.

Third, logging and monitoring promote better collaboration and DevOps culture. By providing insights into the performance and behavior of the application, it becomes easier for different teams and developers to work together on the same application.

Fourth, logging and monitoring allow for better security. By collecting and analyzing data from different sources, you can detect and respond to security threats quickly.

In summary, as a new engineer, understanding the concept of logging and monitoring is important because it is a key component of cloud-native application development, provides better visibility and troubleshooting, promotes better collaboration and DevOps culture, and allows for better security. It is a powerful tool for building and deploying applications in a cloud environment and is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about logging and monitoring. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

“Introduction to Cloud Monitoring” by Google: https://cloud.google.com/monitoring/docs/monitoring-overview
“AWS Monitoring and Logging” by AWS: https://docs.aws.amazon.com/whitepapers/latest/introduction-aws-security/monitoring-and-logging.html
“AWS Monitoring Strategies” by O’Reilly: https://learning.oreilly.com/videos/aws-monitoring-strategies/9780136611899/

Intermediate:

“Logging and Monitoring with Elastic Stack” by Microsoft: https://learn.microsoft.com/en-us/dotnet/architecture/cloud-native/logging-with-elastic-stack
“Using Prometheus and Grafana to Monitor K8s” by Gardener Cloud: https://gardener.cloud/docs/guides/applications/prometheus/
“Log Monitoring” by Datadog: https://www.datadoghq.com/log-monitoring/

Advanced:

“Google Cloud’s Operations Suite” by Google: https://cloud.google.com/products/operations
“Kubernetes Logging and Monitoring Explained” by kublr: https://kublr.com/blog/kubernetes-logging-and-monitoring-explained/
“Cloud-Native Logging and Monitoring Pattern” by weaveworks: https://www.weave.works/blog/cloud-native-logging-and-monitoring-pattern

Videos to Watch

Monitoring, Logging, And Alerting In Kubernetes

This video provides an overview of the different components of a self-managed monitoring and logging stack for Kubernetes clusters, such as Prometheus, Node Exporters, Push Gateway, and Alert Manager. Robusta is also mentioned as a platform for Kubernetes notifications, troubleshooting, and automation.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different logging and monitoring tools such as Prometheus, Grafana, and Elasticsearch. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of logging and monitoring, you can begin to explore the underlying concepts and technologies such as Kubernetes API objects, metrics, and alerting. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Logging and monitoring are important aspects of a microservices architecture, so it’s important to understand the key principles and best practices of logging and monitoring such as observability, log retention, and monitoring dashboards.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with logging and monitoring for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using logging and monitoring tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Believe it or not, in my early days of development a rarely created logs in production. I’m not sure if it was “bro science,” but many of us were of the opinion that writing logs would slow down our applications. It was almost as though many of us believed you could drive faster if you kept your eyes closed.

Logging and monitoring are like a detective and a spy for your application. They help you to understand what’s happening inside your application and detect any issues that might arise.

In a cloud-native environment, logging and monitoring are essential for understanding the health and performance of your application. Logging is the process of capturing information about what’s happening inside your application, such as error messages or performance metrics. Some of the common tools used for logging in cloud-native environments are Elasticsearch, Logstash, and Kibana (ELK stack), Fluentd, and Graylog. A typical log file might look like this:

[2022-11-01T09:15:00Z] [INFO] Server started on port 80
[2022-11-01T09:15:02Z] [ERROR] Failed to connect to database
[2022-11-01T09:15:03Z] [INFO] Successfully connected to database

Monitoring is the process of collecting and analyzing data about the performance and health of your application. Some common monitoring tools used in cloud-native environments are Prometheus, Grafana, and InfluxDB. These tools allow you to collect metrics about your application, such as CPU usage, memory usage, and network traffic. They also provide visualizations of the metrics, which makes it easy to understand what’s happening inside your application.

In Kubernetes, logging and monitoring are built into the platform and can be easily configured with Kubernetes resources. This allows you to collect and analyze data about your applications and systems.

Connect with Shawn

Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

Shawn’s LinkedIn