1616181780
Monitor and Measure The Availability Of Applications Running on Kubernetes
Concepts and implementation to observe applications availability — A foundation to track SLA/SLO targets.
When applications go in production one of our main concerns is to ensure that they are properly monitored, notably with appropriate checks and suitable metrics to report about their availability over time. This article comes to tackle this concern. Particularly focused on applications running on Kubernetes, it sets up a standard to monitor, measure, and observe the availability of applications. The goal being to help organizations to define Service Level Objectives (SLO) and/or Service Level Agreements (SLA) while be able to track them through factual KPIs over time.
This article is compose of two main sections. The first one is conceptual, introducing our fundamentals and assumptions to define, monitor, and measure application availability on Kubernetes. The second one is practical, demonstrating an implementation powered by RealOpInsight — an open source application operations monitoring framework designed to work atop of Kubernetes while leveraging the basic probe capabilities of the later.
Statement of work
Given one or more instances of Kubernetes, the goal is to be able to monitor, measure, and track the availability of applications as established by the following tenets:
- **Defining a Kubernetes application: **As previously discussed here, we define an application in one of these two ways. On the one hand, a simple application can be modeled as a set of Kubernetes services along with their pods within a single namespace. As already discussed in a previous story, the application in this case can be viewed as a dependency tree-like on the Diagram 1.a (below). Concretely, the dependency tree is a hierarchical composition of services along with the pods and containers that underlie them. Each container is associated to its pod, which in turn associated to its service, which finally is associated to the application at the top level. On the other hand, a complex application can be modeled as a composition of two or more namespace-scoped applications.
#kubernetes #prometheus #microservices #monitoring
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1602964260
50+ Useful Kubernetes Tools for 2020 - Part 2
Introduction
Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.
According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.
And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.
#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml
1624006278
The Rising Value of Big Data in Application Monitoring
In an ecosystem that has become increasingly integrated with huge chunks of data and information traveling through the airwaves, Big Data has become irreplaceable for establishments.
From day-to-day business operations to detailed customer interactions, many ventures heavily invest in data sciences and data analysis to find breakthroughs and marketable insights.
Plus, surviving in the current era, mandates taking informed decisions and surgical precision based on the projected forecast of current trends to retain profitability. Hence these days, data is revered as the most valuable resource.
According to a recent study by Sigma Computing , the world of Big Data is only projected to grow bigger, and by 2025 it is estimated that the global data-sphere will grow to reach 17.5 Zettabytes. FYI one Zettabyte is equal to 1 million Petabytes.
Moreover, the Big Data industry will be worth an estimate of $77 billion by 2023. Furthermore, the Banking sector generates unparalleled quantities of data, with the amount of data generated by the financial industry each second growing by 700% in 2021.
In light of this information, let’s take a quick look at some of the ways application monitoring can use Big Data, along with its growing importance and impact.
#ai in business #ai application #application monitoring #big data #the rising value of big data in application monitoring #application monitoring
1620025440
Top Kubernetes Health Metrics You Must Monitor
Kubernetes is one of the most popular choices for container management and automation today. A highly efficient Kubernetes setup generates innumerable new metrics every day, making monitoring cluster health quite challenging. You might find yourself sifting through several different metrics without being entirely sure which ones are the most insightful and warrant utmost attention.
As daunting a task as this may seem, you can hit the ground running by knowing which of these metrics provide the right kind of insights into the health of your Kubernetes clusters. Although there are observability platforms to help you monitor your Kubernetes clusters’ right metrics, knowing exactly which ones to watch will help you stay on top of your monitoring needs. In this article, we take you through a few Kubernetes health metrics that top our list.
Crash Loops
A crash loop is the last thing you’d want to go undetected. During a crash loop, your application breaks down as a pod starts and keeps crashing and restarting in a circle. Multiple reasons can lead to a crash loop, making it tricky to identify the root cause. Being alerted when a crash loop occurs can help you quickly narrow down the list of causes and take emergency measures to keep your application active.
#devops #kubernetes #monitoring #observability #kubernetes health monitoring #monitoring for kubernetes
1614761164
Kubernetes: Monitoring, Reducing, and Optimizing Your Costs
Over the past two years at Magalix, we have focused on building our system, introducing new features, and scaling our infrastructure and microservices. During this time, we had a look at our Kubernetes clusters utilization and found it to be very low. We were paying for resources we didn’t use, so we started a cost-saving practice to increase cluster utilization, use the resources we already had and pay less to run our cluster.
In this article, I will discuss the top five techniques we used to better utilize our Kubernetes clusters on the cloud and eliminate wasted resources, thus saving money. In the end, we were able to cut our monthly bill by more than 50%!
- Applying Workload Right-Sizing
- Choosing The Right Worker Nodes
- Autoscaling Workloads
- Autoscaling Worker Nodes
- Purchasing Commitment/Saving Plans
#cloud-native #kubernetes #optimization #kubecost #kubernetes-cost-savings #kubernetes-cost-monitoring #kubernetes-reduce-cost #kubernetes-cost-analysis
1616181780
Monitor and Measure The Availability Of Applications Running on Kubernetes
Concepts and implementation to observe applications availability — A foundation to track SLA/SLO targets.
When applications go in production one of our main concerns is to ensure that they are properly monitored, notably with appropriate checks and suitable metrics to report about their availability over time. This article comes to tackle this concern. Particularly focused on applications running on Kubernetes, it sets up a standard to monitor, measure, and observe the availability of applications. The goal being to help organizations to define Service Level Objectives (SLO) and/or Service Level Agreements (SLA) while be able to track them through factual KPIs over time.
This article is compose of two main sections. The first one is conceptual, introducing our fundamentals and assumptions to define, monitor, and measure application availability on Kubernetes. The second one is practical, demonstrating an implementation powered by RealOpInsight — an open source application operations monitoring framework designed to work atop of Kubernetes while leveraging the basic probe capabilities of the later.
Statement of work
Given one or more instances of Kubernetes, the goal is to be able to monitor, measure, and track the availability of applications as established by the following tenets:
- **Defining a Kubernetes application: **As previously discussed here, we define an application in one of these two ways. On the one hand, a simple application can be modeled as a set of Kubernetes services along with their pods within a single namespace. As already discussed in a previous story, the application in this case can be viewed as a dependency tree-like on the Diagram 1.a (below). Concretely, the dependency tree is a hierarchical composition of services along with the pods and containers that underlie them. Each container is associated to its pod, which in turn associated to its service, which finally is associated to the application at the top level. On the other hand, a complex application can be modeled as a composition of two or more namespace-scoped applications.
#kubernetes #prometheus #microservices #monitoring