#Hashicorp Consul

[some-programming-pearls]

Can HashiCorp Consul be used to monitor messages and fine-grained control over network traffic management in message brokers' producer-consumer-based process in a microservice architecture?

Yes, Consul can be used to monitor message failures or non-deliveries in message broker producer-consumer processes within microservices architectures, but with some limitations and considerations. Consul primarily functions as a service discovery and configuration management tool, providing features such as service registration, health checks, and key-value store. While Consul itself doesn’t…

[roamnook]

"HashiCorp teams up with IBM to boost multi-cloud automation. Get the lowdown on this groundbreaking collaboration: [link]. #cloud #automation #collaboration"

RoamNook Blog: Unlocking the Power of Hard Facts

RoamNook Blog: Unlocking the Power of Hard Facts

Welcome to the RoamNook blog where we bring you informative content packed with new and polarizing hard facts. Our goal is to provide you with concrete data that is not only objective but also highly practical, ensuring that you can apply this information to your real-world scenarios. In this blog, we will delve into a wide range of technical, professional, and scientific terms to present you with groundbreaking insights.

Introducing HashiCorp's Collaboration with IBM for Multi-Cloud Automation

If you are looking to accelerate your multi-cloud automation processes, you must have heard the exciting news about HashiCorp joining forces with IBM. This partnership is set to revolutionize the way businesses leverage the power of the cloud. By combining the expertise of HashiCorp in cloud infrastructure automation with IBM's cutting-edge technology, organizations around the world can unlock new levels of efficiency and scalability.

Understanding the Key Products

HashiCorp Cloud Platform (HCP)

The HashiCorp Cloud Platform (HCP) is an all-in-one solution designed to streamline the management of multi-cloud infrastructure. With HCP, businesses can easily deploy and scale their applications across multiple cloud providers while maintaining consistency and security. This platform offers a unified control plane and comprehensive management capabilities that simplify the complexities of a multi-cloud environment.

Terraform

Terraform is a powerful infrastructure as code software developed by HashiCorp. It enables users to automate the deployment and management of their cloud infrastructure across various providers. With Terraform, you can define your infrastructure in a declarative language, allowing for seamless provisioning of resources across different cloud platforms. Its extensive provider ecosystem ensures compatibility with all major cloud providers, making it a versatile tool for infrastructure automation.

Packer

Packer is an open-source tool that automates the creation of machine images for multiple platforms. It allows you to define your images in a configuration file, eliminating the need for manual installation and configuration. Packer supports a range of builders, including virtual machines, containers, and more, enabling you to build consistent and reliable machine images for your infrastructure.

Consul

Consul is a highly available and distributed service mesh designed to simplify the management of services across any runtime platform. It provides features such as service discovery, health checking, and key-value storage, ensuring seamless communication and coordination between microservices in a dynamic environment. With Consul, you can achieve better resilience and scalability for your applications.

Vault

Vault is a comprehensive secrets management solution that helps organizations secure, store, and control access to sensitive data such as passwords, API keys, and certificates. It offers a robust set of encryption and authentication mechanisms, ensuring that your secrets are protected both at rest and in transit. Vault also provides fine-grained access controls and auditing capabilities, enabling you to enforce strong security policies across your infrastructure.

Boundary

Boundary is a cloud-native security solution that focuses on securing remote access to critical systems and resources. With Boundary, you can establish secure connections to your infrastructure without the need for complex VPN configurations. It offers granular access controls, session recording, and real-time visibility, enabling you to ensure compliance and detect any unauthorized activities.

Nomad

Nomad is a distributed job scheduler and workload orchestrator that simplifies the deployment and management of containerized applications and batch workloads. It allows you to seamlessly scale your applications across multiple nodes, ensuring high availability and resource optimization. Nomad's flexible scheduling capabilities and integrated health checks make it an ideal solution for maximizing the efficiency of your infrastructure.

Waypoint

Waypoint is a cloud-native build and deployment tool that enables developers to streamline their application delivery pipelines. With Waypoint, you can define your deployment workflows in a single configuration file, ensuring consistency and reliability across different environments. It offers integrations with popular CI/CD systems, making it easy to automate your build, test, and deploy processes.

Vagrant

Vagrant is a tool for creating and managing development environments. It allows you to set up reproducible development environments using virtual machines or containers. Vagrant simplifies the process of provisioning, configuring, and managing these environments, saving you time and effort in setting up your development stack.

Real-World Applications and the Importance of Hard Facts

The information we have shared with you about HashiCorp's products and collaboration with IBM is more than just technical jargon. It has real-world implications that can transform the way businesses operate and compete in today's digital landscape. By leveraging the power of multi-cloud automation, organizations can achieve:

Increased scalability and flexibility in deploying applications across different cloud providers

Improved resource utilization and cost optimization

Enhanced security and compliance through centralized secrets management and secure remote access

Streamlined development workflows and faster time-to-market

These benefits are backed by concrete data and proven success stories. By adopting HashiCorp's solutions and embracing the power of hard facts, businesses can stay ahead of the competition and drive digital growth. Whether you are a small startup or a large enterprise, the impact of multi-cloud automation cannot be ignored.

Join the RoamNook Revolution

At RoamNook, we specialize in IT consultation, custom software development, and digital marketing. Our innovative technology solutions are aimed at fueling digital growth for our clients. By leveraging HashiCorp's products and our expertise, we can help you unlock the full potential of multi-cloud automation.

Are you ready to take your business to new heights? Contact RoamNook today to learn how our solutions can transform your digital infrastructure.

© 2021 RoamNook. All rights reserved.

Source: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/infrastructure-as-code&sa=U&ved=2ahUKEwjT5ca2mZSGAxXSE1kFHeQXBEAQFnoECAEQAw&usg=AOvVaw3iJsPt_mVKHHSYyut7IQB3

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Comprehensive Guide To Setting Up And Utilizing Consul Cluster

Comprehensive Guide To Setting Up And Utilizing Consul Cluster

  In a distributed system, managing service discovery and configuration can be a challenging task. This is where Consul, a powerful tool from HashiCorp, comes into play. Consul provides a distributed service mesh to connect services seamlessly and manage their configurations. In this article, we will explore Consul Cluster in detail and learn how to set up and utilize it effectively.

What is Consul? Consul is a distributed service mesh solution designed to connect, discover, and secure services across various platforms and environments. It offers a robust set of features, including service discovery, distributed key-value store, health checks, and service segmentation. With Consul, developers can build resilient and scalable applications by seamlessly connecting services and managing their configurations.

Consul Cluster A Consul Cluster is a group of Consul agent instances running together in a coordinated manner. Each agent operates as a member of the cluster, participating in leader election to ensure high availability and fault tolerance. The Consul Cluster distributes the workload among its nodes and maintains a replicated state across all agents.

Setting up a Consul Cluster Setting up a Consul Cluster involves the following steps: 1. Installation: The first step is to install Consul on each node that will be part of the cluster. Consul provides binaries for various operating systems, and installation instructions can be found in the official documentation.

2. Configuration: Once Consul is installed, the next step is to configure the agents. Consul uses a single configuration file or command-line flags to specify its settings. The configuration includes parameters such as data directory, cluster name, network settings, and other optional parameters.

3. Bootstrap: Consul cluster requires a bootstrap process to initialize the initial state. To bootstrap a cluster, one of the agents needs to be designated as the server, while the rest are considered as clients. The server acts as the leader and is responsible for cluster management. The bootstrap process can be initiated by starting the first server agent with the `-bootstrap-expect` flag, specifying the number of expected servers in the cluster.

4. Joining the Cluster: To join a Consul Cluster, the agent needs to know the IP address or hostname of at least one existing member in the cluster. This information can be passed through the configuration file or as a command-line option while starting the agent. When an agent joins the cluster, it automatically synchronizes its state with other members and participates in leader election.

5. Leader Election and Coordination: Consul Cluster employs a consensus-based algorithm known as Raft to elect a leader among server agents. The leader is responsible for making decisions and coordinating cluster activities. In the event of a leader failure, a new leader is elected from the available server agents using the Raft algorithm.

Utilizing Consul Cluster Features Now that we have a Consul Cluster up and running, let’s explore some of its key features:

1. Service Discovery: Consul provides a decentralized service discovery mechanism, which allows services to be registered and discovered dynamically. Services can be registered with Consul using DNS, HTTP, or gRPC interfaces. Clients can query Consul to retrieve the current list of available services and their associated endpoints.

2. Health Checks: Consul offers powerful health checking capabilities, ensuring that services are operating correctly. Agents can periodically perform checks on registered services and report their status to Consul. This information is used to determine the health of services and take appropriate actions, such as failing over to a healthy instance.

3. Distributed Key-Value Store: Consul includes a distributed key-value store, which can be used as a centralized configuration store. Applications can read and write key-value pairs from Consul dynamically, enabling runtime configuration updates without the need for application restarts. This feature is especially useful in dynamic and microservice-oriented environments.

4. Service Segmentation: Consul enables service segmentation by providing fine-grained access control policies. It allows administrators to define rules based on service names, tags, or other attributes. This helps in implementing security measures and isolating services based on access requirements.

Example Code Snippet Here is an example code snippet to demonstrate how to register a service with Consul using the Consul Go API:Conclusion Consul Cluster is a powerful tool for managing service discovery and configurations in distributed systems. By setting up a Consul Cluster, developers can build resilient and scalable applications with ease. With features like service discovery, health checks, distributed key-value store, and service segmentation, Consul simplifies the management of services in a distributed environment. I hope this comprehensive guide has provided you with a solid understanding of Consul Cluster and how to utilize it effectively. When integrating Consul with Drupal, one powerful approach is to leverage Drupal Confi Split module. This module allows you to manage different configurations for various environments, such as development, staging, and production. By incorporating Configuration Split into your Consul setup, you can streamline the deployment process and ensure seamless transitions between environments.

[damekraft]

Email Answers to Recruiters

In the past year, I have had extensive experience with both self-managed Kubernetes on AWS and Amazon EKS. I was a hands-on manager for the architecture, feature development, daily operations and on-call support for EKS kubernetes clusters as well as the lifecycle maintenance, daily operations and on-call support of the Self Managed Kubernetes clusters. I lead a team of 7 software engineers and a manager performing in a principal, manager, director and individual contributor role helping design, develop, implement and operate a hybrid Kong Service Mesh (envoy as the proxy layer) into Kubernetes supporting both the legacy self managed clusters and the EKS clusters by delivering dynamic service mesh capabilities across the physical datacenter and AWS compute platforms running Nordstrom.

I started working with service mesh technologies in 2014 at HomeAway, but my experience with load balancing and application routing at the network layer goes back to 2006. I have extensive experience with layer 7 application routing going back 17 years and I have remained consistently up to date through that entire evolution. The advent of memory resident virtual networking was an incredible evolution to the network industry and I began my work in that space with CloudStack and VMware early on, and quickly moved to Hashicorp Consul in 2014 when Hashicorp began releasing world-changing technologies. I was lucky to be at the ground floor of Consul launching  to be able to provide direct feedback to the founder and help shape what the product is today. I worked with a group of early platform engineers to begin testing linkerd and and istio, and my latest work has been with Kong Service

In 2014 at HomeAway, I was part of a peer team of principal engineers who came together to design, develop and deliver a service mesh to the organization. We worked with the wider organization in an ad-hoc format sharing high level design and possibility models of what services we could unlock using our proposed service mesh design and asked for feedback from the enterprise and product principals and "bright lights" across the company regarding our proposal. At the beginning we rolled out Consul as it was the only product that met our needs at the time. Eventually as we gained more feedback and learning we moved off consul and onto linkerd using existing operational change management processes and decided at that time to evaluate istio alongside linkerd for a year before being clearly informed directly by google that istio would not be mature enough to scale to our needs in the time frame we needed for our fully scaled operations requirements. 

I was fortunate HomeAway as a company was so forward looking in 2014 to understand the value of the service mesh. We were able to land quickly on a product and move to delivery, so much of my broader product and program outreach work there was not confrontational, rather curious and excited. The culture there allowed me to focus a lot of time on the post decision evangelizing work using lunch and learn presentations to principals and directors across home away to go over our solution and provide ample time for Q&A and feedback, led decisively so that we could bias for as much action as possible within an hour. 

As we moved through implementation and operational maturity, we provided weekly updates via the devOps meetings and I gave executive level presentations every week at the executive technology update meetings. We also set up weekly office hours meetings for hands-on demonstrations as well as provide extensive pairing across the dev organization held in a set of private conference rooms we reserved for the service mesh project where we could "talk shop" with teams for as long as needed to work through whatever obstacles came up. I spent considerable time working extensively with an application edge gateway team that I had proposed funding and organization support for in order to help the engineers understand the service and application edge architecture helping mentor and guide them. I also provided ongoing support to these engineers as they hired out and built their team over a 12 month period.

When I was at Nordstrom we used their design review process to deploy Kong Service Mesh. The design review process at Nordstrom was a very mature, highly publicized and well-attended process of meetings and demonstrations where principals across Nordstrom were able to provide feedback and questions into a formalized process of decision making. With precision I led the team through the design review process which culminated into a well-rehearsed final presentation that worked much like delivering a master's thesis. We followed and passed the design review process and moved to weekly meetings with the principals to show our implementation work and provide usable demonstrations in accordance with program and product timelines for deliverables. We socialized our service mesh program using Product and Program meeting schedules to showcase our technologies on a biweekly basis to the larger organization. If any conflicts emerged from those conversations, we were then able to go back to the design review board and follow a well-established change management process to resolve any design conflicts that had surfaced as part of the broader awareness campaigns. Another tactic we followed was identifying early adopter candidates and working with them in a tightly integrated series of agile sprints to test and learn with those organizations and then invite them along to our product and program meetings to directly talk to the wider organization about their positive and negative experiences with our service mesh product.

[bdccglobal]

Explore Top DevOps Companies in the USA

Algoworks is a technology company that provides a range of services including end-to-end product development, DevOps consulting, and 24/7 support for high availability (HA) environments. As a recognized AWS partner, Algoworks has a strong focus on utilizing the latest cloud technologies to help organizations scale and grow their businesses. The company has a team of experienced DevOps engineers who have a deep understanding of the latest DevOps tools and best practices. They work closely with clients to understand their unique needs and provide customized solutions to improve their software development and deployment processes. 

Atlassian is an Australian multinational enterprise software company that develops products for software development, project management, and content management. Its most popular products include Jira, Confluence, and Trello. Atlassian also offers a wide range of add-ons and integrations for its products, making it a popular choice for DevOps teams. 

Red Hat is an American multinational software company that provides open-source software products to the enterprise community. Its flagship product, Red Hat Enterprise Linux, is one of the most popular Linux distributions for servers and other enterprise-class systems. Additionally, Red Hat offers a variety of other products and services, such as Ansible, OpenShift, and JBoss, that are widely used in DevOps environments. 

CircleCI is a continuous integration and delivery platform that helps software teams build, test, and deploy code quickly and consistently. It allows teams to automate their software development workflows, which helps to improve the speed and quality of their releases. 

New Relic is a software analytics company that provides real-time data and insights into the performance of web and mobile applications. Its platform can be used to monitor and troubleshoot issues in real-time, making it a popular choice for DevOps teams who need to quickly identify and resolve performance issues. 

Grafana Labs is a leading open-source software company that specializes in data visualization and monitoring. Its flagship product, Grafana, is widely used to monitor and analyze time-series data from various sources, such as databases, servers, and cloud services. It is also a very popular tool among DevOps team 

GitLab is a web-based Git repository manager that provides source code management, continuous integration, and more. It is written in Ruby and is similar to GitHub. GitLab provides a central location for teams to store and manage their code, and also offers a variety of tools to help teams collaborate and automate their workflows. 

Datadog is a monitoring and analytics platform for cloud-scale applications, providing real-time visibility into the performance of applications, networks, and servers. It allows the DevOps team to collect and analyze large amounts of data from multiple sources, and to identify and troubleshoot performance issues in real time. 

PagerDuty is a digital operations management platform that helps DevOps teams respond to critical incidents and outages in real time. It provides a centralized view of all incidents across an organization and allows teams to coordinate their response efforts and minimize the impact of outages. 

HashiCorp is an American multinational software company that provides a variety of open-source tools for infrastructure automation and management. Its most popular products include Vagrant, Terraform, and Consul. These tools are widely used in DevOps environments to automate the provisioning, configuration, and management of infrastructure. 

Splunk is a software company that provides a platform for real-time operational intelligence. It allows teams to collect, analyze, and visualize large amounts of data from various sources, such as logs, metrics, and traces. This makes it a powerful tool for troubleshooting and identifying performance issues in DevOps environments. 

[theithollow]

Using Hashicorp Consul to Store Terraform State

Using @Hashicorp Consul to Store Terraform State

Hashicorp’s Terraform product is very popular in describing your infrastructure as code. One thing that you need consider when using Terraform is where you’ll store your state files and how they’ll be locked so that two team members or build servers aren’t stepping on each other. State can be stored in Terraform Enterprise (TFE)or with some cloud services such as S3. But if you want to store your…

[gslin]

HashiCorp 推出 HashiCorp Cloud Platform

HashiCorp 推出 HashiCorp Cloud Platform

HashiCorp 宣佈了 HashiCorp Cloud Platform 這個產品：「Announcing the HashiCorp Cloud Platform」。

不是自己弄機房建 cloud，而是在既有的 cloud 上提供服務，就不需要自己架了：

HashiCorp Cloud Platform (HCP) is a fully managed platform offering HashiCorp products as a service to automate infrastructure on any cloud.

HCP Consul on AWS is now available in private beta. HCP Vault coming soon.

照目前公開的資料，第一個支援的是 AWS 上的 Consul，下一個是 Vault，然後目前推出的是…

[systemtek]

HashiCorp Consul Token Privilege Escalation Vulnerability [CVE-2019-8336]

HashiCorp Consul Token Privilege Escalation Vulnerability [CVE-2019-8336]

CVE Number – CVE-2019-8336

A vulnerability in HashiCorp Consul could allow an unauthenticated, remote attacker to bypass access restrictions on a targeted system.The vulnerability is due to improper access controls that are performed by the affected software when validating Access Control List (ACL) tokens. An attacker could exploit this vulnerability by injecting a token with <hidden> as its…

[computingpostcom]

Motivation The management of secrets in an organisation holds a special place in the running of day to day activities of the business. All the way from access to the building down to securing personal and confidential documents in laptops or computers, secrets continually show up which speaks about the importance secrets wield not only in our personal lives but in the highways of businesses. A secret is anything that you want to tightly control access to, such as API encryption keys, passwords, or certificates. Taking it away from there, most applications in the current era are going towards the micro-services way and Kubernetes has come strong as the best platform to host the applications designed in this new paradigm. Kubernetes brought about new opportunities and a suite of challenges at the same time. It brought about agility, self healing, ease of scalability, ease of deployment and a good way of running decoupled systems. Now comes the issue of secrets and Kubernetes provides a way of managing them natively. The only problem with it is that it works if the workloads being run are few or the team managing the cluster is relatively small. When the applications being spawned are in the range of hundreds, it becomes difficult to manage secrets in that manner. Moreover, the native Kubernetes secrets engine lacks the capability of encryption which brings an issue of security to the fore. HashiCorp Vault is a secrets management solution that is strongly designed to provide the management of secrets at scale, with ease and it integrates well with a myriad of other tools Kubernetes included. It is an identity-based secrets and encryption management system. Let us see the features Vault comes with: Features of Vault The key features of Vault are: Source Vault Documentation Secure Secret Storage: Arbitrary key/value secrets can be stored in Vault. Vault encrypts these secrets prior to writing them to persistent storage, so gaining access to the raw storage isn’t enough to access your secrets. Vault can write to disk, Consul, and more. Dynamic Secrets: Vault can generate secrets on-demand for some systems, such as AWS or SQL databases. For example, when an application needs to access an S3 bucket, it asks Vault for credentials, and Vault will generate an AWS key-pair with valid permissions on demand. After creating these dynamic secrets, Vault will also automatically revoke them after the lease is up. Data Encryption: Vault can encrypt and decrypt data without storing it. This allows security teams to define encryption parameters and developers to store encrypted data in a location such as SQL without having to design their own encryption methods. Leasing and Renewal: All secrets in Vault have a lease associated with them. At the end of the lease, Vault will automatically revoke that secret. Clients are able to renew leases via built-in renew APIs. Revocation: Vault has built-in support for secret revocation. Vault can revoke not only single secrets, but a tree of secrets, for example all secrets read by a specific user, or all secrets of a particular type. Revocation assists in key rolling as well as locking down systems in the case of an intrusion. Project Pre-requisites BitBucket account BitBucket Pipelines already setup Docker or any tool to create images like Podman, Buildah etc Existing Google Cloud Credentials (json) in BitBucket Environment variable An existing Google Cloud Bucket for Terraform Backend (where it will keep state) We will create terraform scripts, push it to BitBucket whence BitBucket pipelines will take over and deploy vault in Google Kubernetes Engine (GKE) using the image we will build. Installation of Vault Cluster in Google Kubernetes Engine We can now embark on setting up Vault on an existing Google Kubernetes Engine via Helm, BitBucket pipelines and Terraform. The following are the steps that will get you up and running. Some parts are optional in case you do not use BitBucket pipelines in your setup.

Step 1: Prepare Terraform and Google SDK Image In this step we are going to create a Docker image that has Terraform and Google Cloud SKD and then host it in DockerHub so that BitBucket can pull and use it while deploying the infrastructure. First let us create Dockerfile file and populate it with the following. We will use Google’s cloudsdk image as the base then add Terraform. $ vim Dockerfile FROM gcr.io/google.com/cloudsdktool/cloud-sdk:alpine ENV TERRAFORM_VERSION=1.0.10 # Installing terraform RUN apk --no-cache add curl unzip && \ cd /tmp && \ curl -o /tmp/terraform.zip https://releases.hashicorp.com/terraform/$TERRAFORM_VERSION/terraform_$TERRAFORM_VERSION_linux_amd64.zip && \ unzip /tmp/terraform.zip && \ cp /tmp/terraform /usr/local/bin && \ chmod a+x /usr/local/bin/terraform && \ rm /tmp/terraform /tmp/terraform.zip After that, let us build and tag the image. Make sure the Dockerfile file is in the same place you are running this command. docker build -label imagename . Tag the image docker tag imagename penchant/cloudsdk-terraform:latest Then push it to public DockerHub or any registry you prefer docker push penchant/cloudsdk-terraform:latest And we are done with the first part Step 2: Prepare Terraform and Helm scripts In order to avoid re-inventing the wheel, this project heavily borrows from a project already in GitHub by mohsinrz. We are grateful and celebrate them for the fine work they have done. We will clone the project and then customise it to befit our environment. cd ~ git clone https://github.com/mohsinrz/vault-gke-raft.git Since we already have a GKE Cluster, we will not use the module geared towards creating one. We will further disable the use of certificates because BitBucket uses an ephemeral container and will not be able to store certificates in it and we will have trouble joining vault workers to the leader later. We will add GCP bucket to store Terraform state so that we can track changes in the what we will be deploying. Add the following in the “main.yaml” file. Ensure that the bucket name already exists in GCP. $ cd ~/vault-gke-raft $ vim main.tf ## Disable the gke cluster module if you have on already #module "gke-cluster" # source = "./modules/google-gke-cluster/" # credentials_file = var.credentials_file # region = var.region # project_id = "project-id" # cluster_name = "dev-cluster-1" # cluster_location = "us-central1-a" # network = "projects/$var.project_id/global/networks/default" # subnetwork = "projects/$var.project_id/regions/$var.region/subnetworks/default" # initial_node_count = var.cluster_node_count # module "tls" source = "./modules/gke-tls" hostname = "*.vault-internal" module "vault" source = "./modules/gke-vault" num_vault_pods = var.num_vault_pods #cluster_endpoint = module.gke-cluster.endpoint #cluster_cert = module.gke-cluster.ca_certificate vault_tls_ca = module.tls.ca_cert vault_tls_cert = module.tls.cert vault_tls_key = module.tls.key terraform backend "gcs" bucket = "terraform-state-bucket" credentials = "gcloud-api-key.json" Another modification we shall make is disable TLS because in our setup, an ephemeral container in BitBucket will provision our infrastructure and some of the certificates are meant to be stored where terraform is running. So we get to lose the certificates after the deployment is done. To disable, navigate to the modules folder and into the vault directory module. Then edit the “vault.tf” file and make it like below. Changes made are: we changed tlsDisable field to true from false we changed VAULT_ADDR environment variable from https to http

we commented/removed VAULT_CACERT environment variable we changed tls_disable field from 0 to 1 we changed VAULT_ADDR from 127.0.0.1 to 0.0.0.0 And removed the certificate paths under listener block The same has been updated in the file below. $ cd ~/vault-gke-raft/modules/vault $ vim vault.tf resource "helm_release" "vault" ui = true listener "tcp" #changed tls_disable field from 0 to 1 #tls_disable = 0 tls_disable = 1 address = "[::]:8200" cluster_address = "[::]:8201" #removed the certificate paths here #tls_cert_file = "/vault/userconfig/vault-tls/vault.crt" #tls_key_file = "/vault/userconfig/vault-tls/vault.key" #tls_client_ca_file = "/vault/userconfig/vault-tls/vault.ca" storage "raft" path = "/vault/data" ui: enabled: true serviceType: "LoadBalancer" serviceNodePort: null externalPort: 8200 EOF ] We will make one more modification that will enable Kubernetes provider to communicate with GKE API. Navigate to the modules folder and into the vault module directory. Then edit the “provider.tf” file. We have added details of the GKE cluster that already exists and used the values in the Kubernetes provider. We commented the one that we fetched from the repo and added the new one as shown below. The helm provider has been edited as well by updating the host, token and cluster ca certificate with what already exists. $ cd ~/vault-gke-raft/modules/vault $ vim provider.tf data "google_client_config" "provider" data "google_container_cluster" "cluster-name" name = "cluster-name" location = "us-central1-a" project = "project-name" # This file contains all the interactions with Kubernetes provider "kubernetes" #host = google_container_cluster.vault.endpoint host = "https://$data.google_container_cluster.dev_cluster_1.endpoint" token = data.google_client_config.provider.access_token cluster_ca_certificate = base64decode( data.google_container_cluster.dev_cluster_1.master_auth[0].cluster_ca_certificate, ) #provider "kubernetes" # host = var.cluster_endpoint # token = data.google_client_config.current.access_token # # cluster_ca_certificate = base64decode( # var.cluster_cert, # ) # provider "helm" kubernetes #host = var.cluster_endpoint host = "https://$data.google_container_cluster.dev_cluster_1.endpoint" #token = data.google_client_config.current.access_token token = data.google_client_config.provider.access_token cluster_ca_certificate = base64decode(data.google_container_cluster.dev_cluster_1.master_auth[0].cluster_ca_certificate, ) After we are done editing the files, let us clone vault-helm in the root directory that will deploy the entire infrastructure for us at a go via terraform helm provider cd ~/vault-gke-raft git clone https://github.com/hashicorp/vault-helm Step 3: Create BitBucket pipelines file In this step, we are going to create and populate the BitBucket pipelines file that will steer our deployment. As you can see, we are using the image we pushed to DockerHub in Step 1. $ cd ~ $ vim bitbucket-pipelines.yaml image: penchant/cloudsdk-terraform:latest ## The image pipelines: branches: vault: - step: name: Deploy to Vault Namespace deployment: production script: - cd install-vault # I placed my files in this directory in the root of the files - export TAG=$(git log -1 --pretty=%h) - echo $GCLOUD_API_KEYFILE | base64 -d > ./gcloud-api-key.json - gcloud auth activate-service-account --key-file gcloud-api-key.json - export GOOGLE_APPLICATION_CREDENTIALS=gcloud-api-key.json - gcloud config set project - gcloud container clusters get-credentials --zone= --project - terraform init

- terraform plan -out create_vault - terraform apply -auto-approve create_vault services: - docker Step 4: Initialise cluster by creating the leader node/pod After installing vault cluster via terraform and helm, it is time to bootstrap the cluster and unseal it. Initialise the cluster by making vault-0 node as the leader then we can unseal it and then later join the rest of the nodes to the cluster and unseal them as well. Initialize the cluster by making node vault-0 as the leader as shown follows: $ kubectl exec -ti vault-0 -n vault -- vault operator init Unseal Key 1: 9LphBlg31dBKuVCoOYRW+zXrS5zpuGeaFDdCWV3x6C9Y Unseal Key 2: zfWTzDo9nDUIDLuqRAc4cVih1XzuZW8iEolc914lrMyS Unseal Key 3: 2O3QUiio8x5W+IJq+4ze45Q3INL1Ek/2cHDiNHb3vXIz Unseal Key 4: DoPBFgPte+Xh6L/EljPc79ZT2mYwQL6IAeDTLiBefwPV Unseal Key 5: OW1VTaXIMDt0Q57STeI4mTh1uBFPJ2JvmS2vgYAFuCPJ Initial Root Token: s.rLs6ycvvg97pQNnvnvzNZgAJ Vault initialized with 5 key shares and a key threshold of 3. Please securely distribute the key shares printed above. When the Vault is re-sealed, restarted, or stopped, you must supply at least 3 of these keys to unseal it before it can start servicing requests. Vault does not store the generated master key. Without at least 3 keys to reconstruct the master key, Vault will remain permanently sealed! It is possible to generate new unseal keys, provided you have a quorum of existing unseal keys shares. See "vault operator rekey" for more information. Now we have the keys and the root token. We will use the keys to unseal the nodes and join every node to the cluster. Step 5: Unsealing the leader node/pod We will use the unseal keys from the output of above command in Step 4 to unseal Vault as shown below. Run the command three times and supply the keys in the order they have been generated above. After running the command, you will be presented with a prompt where you are required to enter one of the seals generated above. Simply copy and paste one of them and hit enter. $ kubectl exec -ti vault-0 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 1/3 Unseal Nonce f4c34433-6ef1-59ca-c1c9-1a6cc0dfabff Version 1.8.4 Storage Type raft HA Enabled true Run it the second time $ kubectl exec -ti vault-0 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 2/3 Unseal Nonce f4c34433-6ef1-59ca-c1c9-1a6cc0dfabff Version 1.8.4 Storage Type raft HA Enabled true Run it again the third time $ kubectl exec -ti vault-0 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed false Total Shares 5 Threshold 3 Version 1.8.4 Storage Type raft Cluster Name vault-cluster-3d108027 Cluster ID a75de185-7b51-6045-20ca-5a25ca9d9e70 HA Enabled true HA Cluster n/a HA Mode standby Active Node Address Raft Committed Index 24 Raft Applied Index 24 For now, we have not added the remaining four nodes/pods of vault statefulsets into the cluster. If you check the status of the pods, you will see the they are not ready. Let us confirm that. $ kubectl get pods -n vault NAME READY STATUS RESTARTS AGE vault-0 1/1 Running 0 14m

vault-1 0/1 Running 0 14m vault-2 0/1 Running 0 14m vault-3 0/1 Running 0 14m vault-4 0/1 Running 0 14m vault-agent-injector-5c8f78854d-twllz 1/1 Running 0 14m As you can see, vault-1 through to vault-4 are not ready (0/1) Step 6: Add the rest of the nodes to the cluster and Unsealing them This is the step where we are going to add each one of them to the cluster step by step. The procedure is as follows: Add a node to the cluster Then unseal it using the number of threshold shown in the status command above (kubectl exec -ti vault-0 -n vault — vault status). It is 3 in this example. This means we will run the unseal command three times for each node. When you are unsealing, use the same keys that we used for the node 1 above. Let us get rolling. Join the other nodes to the cluster starting with vault-1 node. $ kubectl exec -ti vault-1 -n vault -- vault operator raft join --address "http://vault-1.vault-internal:8200" "http://vault-0.vault-internal:8200" Key Value --- ----- Joined true After it has successfully joined, unseal the node three times. ## First Time $ kubectl exec -ti vault-1 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 1/3 Unseal Nonce 188f79d8-a87f-efdf-4186-73327ade371a Version 1.8.4 Storage Type raft HA Enabled true ## Second Time $ kubectl exec -ti vault-1 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 2/3 Unseal Nonce 188f79d8-a87f-efdf-4186-73327ade371a Version 1.8.4 Storage Type raft HA Enabled true ## Third Time $ kubectl exec -ti vault-1 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 0/3 Unseal Nonce n/a Version 1.8.4 Storage Type raft HA Enabled true Then join node vault-2 to the cluster and then unseal it just like it was done in node vault-1 $ kubectl exec -ti vault-2 -n vault -- vault operator raft join --address "http://vault-2.vault-internal:8200" "http://vault-0.vault-internal:8200" Key Value --- ----- Joined true Unseal node vault-2 three times entering one of the 3 keys on each run ##First Time $ kubectl exec -ti vault-2 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 1/3 Unseal Nonce 60ab7a6a-e7dc-07c8-e73c-11c55bafc199 Version 1.8.4 Storage Type raft HA Enabled true ##Second time $ kubectl exec -ti vault-2 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 2/3 Unseal Nonce 60ab7a6a-e7dc-07c8-e73c-11c55bafc199 Version 1.8.4 Storage Type raft HA Enabled true ##Third Time $ kubectl exec -ti vault-2 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- -----

Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 0/3 Unseal Nonce n/a Version 1.8.4 Storage Type raft HA Enabled true Do the same for the remaining pods/nodes in your cluster that are still not ready. Simply check your pods as follows $ kubectl get pods -n vault NAME READY STATUS RESTARTS AGE vault-0 1/1 Running 0 14m vault-1 1/1 Running 0 14m vault-2 1/1 Running 0 14m vault-3 0/1 Running 0 14m vault-4 0/1 Running 0 14m vault-agent-injector-5c8f78854d-twllz 1/1 Running 0 14m The ones with 0/1 are not yet ready so join them to the cluster and unseal them. Add Node vault-3 $ kubectl exec -ti vault-3 -n vault -- vault operator raft join --address "http://vault-3.vault-internal:8200" "http://vault-0.vault-internal:8200" Key Value --- ----- Joined true Unseal Node vault-3 three times again. ##First Time $ kubectl exec -ti vault-3 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 1/3 Unseal Nonce 733264c0-bfc6-6869-a3dc-167e642ad624 Version 1.8.4 Storage Type raft HA Enabled true ##Second Time $ kubectl exec -ti vault-3 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 2/3 Unseal Nonce 733264c0-bfc6-6869-a3dc-167e642ad624 Version 1.8.4 Storage Type raft HA Enabled true ##Third Time $ kubectl exec -ti vault-3 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 0/3 Unseal Nonce n/a Version 1.8.4 Storage Type raft HA Enabled true Add Node vault-4 $ kubectl exec -ti vault-4 -n vault -- vault operator raft join --address "http://vault-4.vault-internal:8200" "http://vault-0.vault-internal:8200" Key Value --- ----- Joined true Unseal Node vault-4 three times once more. ##First Time $ kubectl exec -ti vault-4 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 1/3 Unseal Nonce 543e3a67-28f9-9730-86ae-4560d48c2f2e Version 1.8.4 Storage Type raft HA Enabled true ##Second Time $ kubectl exec -ti vault-4 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 2/3 Unseal Nonce 543e3a67-28f9-9730-86ae-4560d48c2f2e Version 1.8.4 Storage Type raft HA Enabled true ##Third Time $ kubectl exec -ti vault-4 -n vault -- vault operator unseal Unseal Key (will be hidden): Key Value --- ----- Seal Type shamir Initialized true Sealed true Total Shares 5 Threshold 3 Unseal Progress 0/3 Unseal Nonce n/a

Version 1.8.4 Storage Type raft HA Enabled true Now lets check our pods $ kubectl get pods -n vault NAME READY STATUS RESTARTS AGE vault-0 1/1 Running 0 32m vault-1 1/1 Running 0 32m vault-2 1/1 Running 0 32m vault-3 1/1 Running 0 32m vault-4 1/1 Running 0 32m vault-agent-injector-5c8f78854d-twllz 1/1 Running 0 32m Beautiful. You can see that all of them are successfully ready. And we are finally done with our vault ha cluster setup in GKE platform. Next, we shall cover how to authenticate to Kubernetes/GKE, create secrets then launch a sample app and inject secrets to the pod via sidecar model. Use Vault-Agent sidecar to inject Secrets in Vault to Kubernetes Pod We hope the document provides insight and has been helpful for your use case. In case you have an idea of how to auto-unseal, kindly point us in the right direction as well. Lastly, the tremendous support and messages we continue to receive is a blessing and we pray that you continue to prosper in your various endeavours as you change the world. Have an amazing end year season and keep at it, keep the safety and may your hard work yield the fruits you desire .

[powerelec]

클라우드 접속 보안 강화 방안.. 하시코프, 제로 트러스트 보안 솔루션 확장

클라우드 접속 보안 강화 방안.. 하시코프, 제로 트러스트 보안 솔루션 확장

멀티 클라우드를 위한 인프라 자동화 소프트웨어 선도기업인 하시코프(HashiCorp®)는 안전한 원격 액세스 제품인 하시코프 클라우드 플랫폼(HCP: HashiCorp Cloud Platform) 바운더리(Boundary)를 공식 출시한다고 밝혔다. 이번 릴리스를 통해 하시코프는 HCP 볼트(Vault)와 HCP 컨설(Consul)에 이어 클라우드용으로 구현된 애플리케이션과 네트워크 및 사용자를 보호하는 바운더리를 추가해 업계 최초의 제로 트러스트(Zero Trust) 보안 솔루션에 제공할 수 있게 되었다. 기업들이 클라우드로 이전하고, 클라우드 운영 모델을 채택함에 따라 보안에 대한 새로운 접근방식이 요구되고 있다. 기본적으로 아무것도 신뢰하지 않고, 모든 것을 인증 및 승인하는 보안 정책이 필요하며,…

[swarnalata31techiio]

What is Kubernetes?

Kubernetes (aka "Kube" or k8s) is an open-source container orchestration platform written in Go. It was initially developed by Google in 2014 but is currently maintained by the Cloud Native Computing Foundation (CNCF). According to surveys, Kubernetes usage share has grown from 58% in 2014 to 83% in 2021, being by far the most popular of the orchestration technologies. Leading public cloud providers like Amazon Web Services (AWS), Google Cloud Platform, IBM Cloud, and Microsoft Azure include managed Kubernetes services in their packages.

What is Nomad?

Nomad is HashiCorps' answer to developers looking for a powerful yet flexible platform for application deployment or container orchestration. Heralded as simple to run and maintain, Nomad is cloud-agnostic and designed to natively handle multi-datacenter and multi-region deployments with a high scalability potential. It is referred to as "Kubernetes without the complexity," but it's making a name for itself on its own merit.

Nomad vs Kubernetes: how to choose?

Kubernetes is an amazing assortment of parts that cooperate, incorporated into one center unit. It is intended to send, oversee and scale application holders across bunches of hosts, very much like a working framework for cloud-local applications.

Wanderer begins as a group chief and undertaking scheduler, yet it very well may be associated with different devices like Consul to grow its capacities. Its adaptability to adjust to various jobs makes Nomad extremely interesting to medium-sized organizations with less equipment and staff assets. It's more straightforward to begin with, simpler to keep up with, however needs local area support.

However, you don't need to pick either Kubernetes and Nomad.

Nomad AND Kubernetes

Both platforms can work together, complementing each other: Kubernetes is used by global companies and is offered as a service by Google Cloud Platform, Azure, and AWS, the three most prominent cloud providers, because it is recognized as a powerful container orchestration tool with cutting edge features. But Nomad's agility makes it perfect for maintenance and core scheduling purposes.

Here's a head to head comparison:

Kubernetes:

Complexity:More complex but provides a higher level of control

Community:Superior community, providing tools, resources and support

Costs :Potencial higher costs due to larger teams and more demanding architecture

Workload support:Focused on Linux containers

Openness:Community supported

Nomad:

Complexity:Easier to start with, but more immature

Community:Lacks a significative community, with the consequential lack of resources

Costs:Requires smaller teams, less servers, and it’s less time consuming

Workload support:Nomad supports virtualized, containerized and standalone applications (Java, Windows apps and even binary.)

Openness:It is closely tied to HashiCorp’s products and development.

[damekraft]

Email answers to recruiters

In the past year, I have had extensive experience with both self-managed Kubernetes on AWS and Amazon EKS. I was a hands-on manager for the architecture, feature development, daily operations and on-call support for EKS kubernetes clusters as well as the lifecycle maintenance, daily operations and on-call support of the Self Managed Kubernetes clusters. I lead a team of 7 software engineers and a manager performing in a principal, manager, director and individual contributor role helping design, develop, implement and operate a hybrid Kong Service Mesh (envoy as the proxy layer) into Kubernetes supporting both the legacy self managed clusters and the EKS clusters by delivering dynamic service mesh capabilities across the physical datacenter and AWS compute platforms running Nordstrom.

I started working with service mesh technologies in 2014 at HomeAway, but my experience with load balancing and application routing at the network layer goes back to 2006. I have extensive experience with layer 7 application routing going back 17 years and I have remained consistently up to date through that entire evolution. The advent of memory resident virtual networking was an incredible evolution to the network industry and I began my work in that space with CloudStack and VMware early on, and quickly moved to Hashicorp Consul in 2014 when Hashicorp began releasing world-changing technologies. I was lucky to be at the ground floor of Consul launching  to be able to provide direct feedback to the founder and help shape what the product is today. I worked with a group of early platform engineers to begin testing linkerd and and istio, and my latest work has been with Kong Service

In 2014 at HomeAway, I was part of a peer team of principal engineers who came together to design, develop and deliver a service mesh to the organization. We worked with the wider organization in an ad-hoc format sharing high level design and possibility models of what services we could unlock using our proposed service mesh design and asked for feedback from the enterprise and product principals and "bright lights" across the company regarding our proposal. At the beginning we rolled out Consul as it was the only product that met our needs at the time. Eventually as we gained more feedback and learning we moved off consul and onto linkerd using existing operational change management processes and decided at that time to evaluate istio alongside linkerd for a year before being clearly informed directly by google that istio would not be mature enough to scale to our needs in the time frame we needed for our fully scaled operations requirements. 

I was fortunate HomeAway as a company was so forward looking in 2014 to understand the value of the service mesh. We were able to land quickly on a product and move to delivery, so much of my broader product and program outreach work there was not confrontational, rather curious and excited. The culture there allowed me to focus a lot of time on the post decision evangelizing work using lunch and learn presentations to principals and directors across home away to go over our solution and provide ample time for Q&A and feedback, led decisively so that we could bias for as much action as possible within an hour. 

As we moved through implementation and operational maturity, we provided weekly updates via the devOps meetings and I gave executive level presentations every week at the executive technology update meetings. We also set up weekly office hours meetings for hands-on demonstrations as well as provide extensive pairing across the dev organization held in a set of private conference rooms we reserved for the service mesh project where we could "talk shop" with teams for as long as needed to work through whatever obstacles came up. I spent considerable time working extensively with an application edge gateway team that I had proposed funding and organization support for in order to help the engineers understand the service and application edge architecture helping mentor and guide them. I also provided ongoing support to these engineers as they hired out and built their team over a 12 month period.

When I was at Nordstrom we used their design review process to deploy Kong Service Mesh. The design review process at Nordstrom was a very mature, highly publicized and well-attended process of meetings and demonstrations where principals across Nordstrom were able to provide feedback and questions into a formalized process of decision making. With precision I led the team through the design review process which culminated into a well-rehearsed final presentation that worked much like delivering a master's thesis. We followed and passed the design review process and moved to weekly meetings with the principals to show our implementation work and provide usable demonstrations in accordance with program and product timelines for deliverables. We socialized our service mesh program using Product and Program meeting schedules to showcase our technologies on a biweekly basis to the larger organization. If any conflicts emerged from those conversations, we were then able to go back to the design review board and follow a well-established change management process to resolve any design conflicts that had surfaced as part of the broader awareness campaigns. Another tactic we followed was identifying early adopter candidates and working with them in a tightly integrated series of agile sprints to test and learn with those organizations and then invite them along to our product and program meetings to directly talk to the wider organization about their positive and negative experiences with our service mesh product.

[credibleauomotive]

Service Discovery Software Market Comprehensive Research Study, Regional Growth, Business Top Key Players Analysis

Global Service Discovery Software Market report emphasizes on the detailed understanding of some decisive factors such as size, share, sales, forecast trends, supply, production, demands, industry and CAGR in order to provide a comprehensive outlook of the global market. Additionally, the report also highlights the challenges impeding market growth and expansion strategies employed by leading companies in the “Service Discovery Software Market”.

Global Service Discovery Software Market research report analyzes top players in the key regions like North America, South America, Middle East and Africa, Asia and Pacific region. It delivers insight and expert analysis into key consumer trends and behavior in market place, In addition to an overview of the market data and key brands. It also provides all data with easily digestible information to guide every businessman’s future innovation and move business ahead.

Global Service Discovery Software Market Segmentation Analysis:

Major Players in Service Discovery Software market are: Avi Networks HashiCorp Consul Netflix Most important types of Service Discovery Software products covered in this report are: Server-side Client-side Most widely used downstream fields of Service Discovery Software market covered in this report are: Large Enterprises SMEs

Click the link to get a free Sample Copy of the Report @ https://crediblemarkets.com/sample-request/service-discovery-software-market-485010?utm_source=Kaustubh&utm_medium=SatPR

Service Discovery Software Market, By Geography:

The regional analysis of Service Discovery Software market is studied for region such as Asia pacific, North America, Europe and Rest of the World. The North America is one of the leading region in the market due to numerous cross industry collaborations taking place between automotive original equipment manufacturers and mobile network operators (MNOs) are taking place for continuous internet connectivity inside a car to enhance the user experience of connected living, while driving. Asia-Pacific region is one of the prominent player in the market owing to large enterprises and SMEs in the region are increasingly adopting Service Discovery Software solutions.

Some Points from Table of Content

Global Service Discovery Software Market 2022 by Company, Regions, Type and Application, Forecast to 2030

1 Service Discovery Software Introduction and Market Overview

2 Industry Chain Analysis

3 Global Service Discovery Software Market, by Type

4 Service Discovery Software Market, by Application

5 Global Service Discovery Software Consumption, Revenue ($) by Region (2018-2022)

6 Global Service Discovery Software Production by Top Regions (2018-2022)

7 Global Service Discovery Software Consumption by Regions (2018-2022)

8 Competitive Landscape

9 Global Service Discovery Software Market Analysis and Forecast by Type and Application

10 Service Discovery Software Market Supply and Demand Forecast by Region

11 New Project Feasibility Analysis

12 Expert Interview Record

13 Research Finding and Conclusion

14 Appendix 

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Qualitative and quantitative analysis of the market based on segmentation involving both economic as well as non-economic factors

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Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region

Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled

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Market dynamics scenario, along with growth opportunities of the market in the years to come

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