Zachariah  Wiza

Zachariah Wiza

1625370840

How To Setup Highly Available Kubernetes Clusters And Applications?

What is high availability? How does high availability architecture look like? How to set up highly available Kubernetes clusters and applications?

#highavailability #ha #kubernetes #k8s

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▬▬▬▬▬▬ Timecodes ⏱ ▬▬▬▬▬▬
00:00 What is high availability?
01:36 Main Kubernetes components
02:11 Single-node control plane
03:29 Two nodes control plane
05:21 Three or more nodes control plane
08:23 External load balancer
10:02 Data centers or zones
13:24 Combining control plane and worker nodes
14:23 Separate control plane and worker nodes
15:00 Highly-available applications

#kubernetes #k8s

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How To Setup Highly Available Kubernetes Clusters And Applications?
Christa  Stehr

Christa Stehr

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.

(State of Kubernetes and Container Security, 2020)

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.

(State of Kubernetes and Container Security, 2020)

#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

Maud  Rosenbaum

Maud Rosenbaum

1601051854

Kubernetes in the Cloud: Strategies for Effective Multi Cloud Implementations

Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.

This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.

Kubernetes: Your Multi Cloud Strategy

Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.

In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.

Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.

In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.

The Compelling Attributes of Multi Cloud Kubernetes

Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.

Stability

In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.

#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud

What is High Availability? A Tutorial | Liquid Web

High Availability

High availability is the description of a system designed to be fault-tolerant, highly dependable, operates continuously without intervention, or having a single point of failure. These systems are highly sought after to increase the availability and uptime required to keep an infrastructure running without issue. The following characteristics define a High Availability system.

High Availability Clustering

High-availability server clusters (aka HA Clusters) is defined as a group of servers which support applications or services that can be utilized reliably with a minimal amount of downtime. These server clusters function using a type of specialized software that utilizes redundancy to achieve mission-critical levels of five9’s uptime. Currently, approximately 60% of businesses require five9’s or greater to provide vital services for their businesses.

High availability software capitalizes on the redundant software installed on multiple systems by grouping or clustering together a group of servers focusing on a common goal in case components fail. Without this form of clustering, if the application or website crashes, the service will not be available until the servers are repaired. HA clustering addresses these situations by detecting the faults and quickly restarting or replacing the server or service or server with a new process that does not require human intervention. This is defined as a “failover” model.

The illustration below demonstrates a simple two node high availability cluster.

2nodeHAcluster

High Availability clusters are often used for mission-critical databases, data sharing, applications, and e-commerce websites spread over a network. High Availability implementations build redundancy within a cluster to remove any one single point of failure, including across multiple network connections and data storage, which can be connected redundantly via geographically diverse storage area networks.

High Availability clustered servers usually use a replication methodology called Heartbeat that is used to monitor each node’s status and health within the cluster over a private network connection. One critical circumstance all clustering software must be able to address is called split-brain, which occurs when all private internal links go down simultaneously, but the nodes in the cluster continue to run. If this occurs, every node within the cluster may incorrectly determine that all the other nodes have gone down and attempt to start services that other nodes may still be running. This condition of duplicate instances running similar services, which could cause data corruption on the system.

ha.cluster

A typical version of high availability software provides attributes that include both hardware and software redundancy. These features include:

  • The automatic detection and discovery of hardware and software components.
  • Autonomous assignment of both active and contingent roles to new elements.
  • Detection of failed software services, hardware components, and other system constructs.
  • Monitoring and notification of redundant components and when they need to be activated.
  • Ability to scale the cluster to accommodate the required changes without external intervention.

Fault tolerance

fault.tolerance

Fault tolerance is defined as the ability for a system’s infrastructure to foresee and withstand errors and provide an automatic response to those issues if encountered. The primary quality of these systems is advanced design factors, which can be called upon should a problem occur. Being able to configure an infrastructure that envisions every possible solution is a considerable task that involves the knowledge and experience to counter the multiple concerns before they occur. System architects who design such frameworks will have the methodologies which envision the means to alleviate these problems in advance, and the ability to implement these frameworks.

The following redundancy methodologies are available and should be reviewed during the initial stages of design and implementation.

  • N + 1 Model – This concept infers the sum of equipment needed (which we will refer to as ‘N’) to keep the entire framework up and running, with an additional independent component backup for each of the ‘N’ components in case of failure.
  • N + 2 Model – Similar to the N + 1 model but with an additional layer of protection if two components should fail.
  • 2N Model – This modality has a dual redundant backup for each element to ensure the system’s framework is fully functional.
  • 2N + 1 Model – Again, this model is similar to the 2N model but with a supplemental component to add a tertiary layer of protection to the system’s framework.

As models progress from Nx to 2Nx, the cost factor also increases exponentially as for truly redundant systems that require uptime. These modalities are critical for stability and availability.

Dependability and Reliability

One of the central tenants of a high availability system is uptime. Uptime is of premier importance, especially if the purpose of a system is to provide an essential service like the 911 systems that respond to emergent situations. In business, having a high availability system is required to ensure a vital service remains online. One example would be an ISP or other service that cannot tolerate a loss of function. These systems must be designed with high availability and fault tolerance to ensure reliability and availability while minimizing downtime.

Orchestrated Error Handling

Should an error occur, the system will adapt and compensate for the issue while remaining up and online. Building this type of system requires forethought and planning for the unexpected. Being able to foresee the problems in advance, and planning for their resolution is one of the main qualities of a high availability system.

Scalability

Should the system encounter an issue like a traffic spike or an increase in resource usage, the system’s ability to scale to meet those needs should be automatic and immediate. Building features like these into the system will provide the system’s ability to respond quickly to any change in the systemic functionality of the architectures processes.

Availability & Five 9’s Uptime

Five 9’s is the industry standard of measure of uptime. This measurement can be related to the system itself, the system processes within a framework, or the program operating inside an infrastructure. This estimation is often related to the program being delivered to clients in the form or a website or web application. A systems Availability can be measured as the percentage of time that systems are available by using this equation: x = (n – y) * 100/n. This formula denotes that where “n” is the total amount of minutes within a calendar month, and “y” is the amount of minutes that service is inaccessible within a calendar month. The table below outlines downtime related to the percentage of “9’s” represented.

**Availability %**90%

(“1 Nine“)99%

(“2 Nines“)99.9%

(“3 Nines“)99.99%

(“4 Nines“)99.999%

(“5 Nines“)Downtime/Year36.53 days3.65 days8.77 hours52.60 minutes5.26 minutes

As we can see, the higher the number of “9’s”, the more uptime is provided. A high availability system’s goal is to achieve a minimal amount of potential downtime to ensure the system is always available to provide the designated services.

Heartbeat

One of the main High Availability components is called Heartbeat. Heartbeat is a daemon which works with a cluster management software like Pacemaker that is designed specifically for high-availability clustering resource management. Its most important characteristics are:

  • No specific or fixed maximum number of nodes – Heartbeat can be used to build large clusters as well as elementary ones.
  • Resource monitoring: resources can be automatically restarted or moved to another node on failure.
  • A fencing mechanism needed to remove failed nodes from the cluster.
  • A refined policy-based resource management, resource inter-dependencies, and constraints.
  • A time-based rule set to allow for different policies depending on a defined timeframe.
  • A group of resource scripts (for software like Apache, DB2, Oracle, PostgreSQL, etc.) included more granular management.
  • A GUI for configuring, controlling and monitoring resources and nodes.

Cluster Architecture

**Engineered Availability **

The first segment of a highly available system is the clearly designed utilization of clustered application servers that are engineered in advance to distribute load amongst the whole cluster, which includes the ability to failover to a secondary and possibly a tertiary system.

The second division includes the need for database scalability. This entails the requirement of scaling, either horizontally or vertically, using multiple master replication, and a load balancer to improve the stability and uptime of the database.

ha cluster

#tutorials #2nx models #architecture #autonomous #availability #backups #best practice #clustering #deployment #design #disaster recovery #downtime #engineered #fault tolerance #ha cluster #heartbeat #high availability #infrastructure #monitoring #node #nx models #orchestrated #pacemaker #redundancy #reliability #replication #scalability #single point of failure #split brain #system #testing #uptime

Mitchel  Carter

Mitchel Carter

1601305200

Microsoft Announces General Availability Of Bridge To Kubernetes

Recently, Microsoft announced the general availability of Bridge to Kubernetes, formerly known as Local Process with Kubernetes. It is an iterative development tool offered in Visual Studio and VS Code, which allows developers to write, test as well as debug microservice code on their development workstations while consuming dependencies and inheriting the existing configuration from a Kubernetes environment.

Nick Greenfield, Program Manager, Bridge to Kubernetes stated in an official blog post, “Bridge to Kubernetes is expanding support to any Kubernetes. Whether you’re connecting to your development cluster running in the cloud, or to your local Kubernetes cluster, Bridge to Kubernetes is available for your end-to-end debugging scenarios.”

Bridge to Kubernetes provides a number of compelling features. Some of them are mentioned below-

#news #bridge to kubernetes #developer tools #kubernetes #kubernetes platform #kubernetes tools #local process with kubernetes #microsoft

Michel  Kub

Michel Kub

1596110100

Webinar: Things to consider to operate a Multi-Tenant Kubernetes Cluster

Using Kubernetes to serve multi tenants is not a trivial task. Kubernetes provides the tools that are necessary(RBAC, Rolebinding, Network Policy, ResourceQuota and etc) to provide isolation between tenants but building/implementing an architecture is solely upon users. In this webinar, we would like to introduce multiple approaches that can be taken to provide multi-tenancy in the kubernetes cluster. We will also talk about how others in the communities are doing to achieve multi-tenancy. We’ll analyze pros and cons of different approaches and share specific use-cases that fit each approach. Finally, we will look in to lessons we’ve learned and we have implemented these factors into our on-premise cloud environment.

#kubernetes #a multi-tenant kubernetes cluster #kubernetes cluster #on-premise cloud environment