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Vault

Secure, store, and tightly control access to tokens, passwords, certificates, API keys, and other secrets in modern computing
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What is Vault?

Vault is a tool for securely accessing secrets. A secret is anything that you want to tightly control access to, such as API keys, passwords, certificates, and more. Vault provides a unified interface to any secret, while providing tight access control and recording a detailed audit log.
Vault is a tool in the Secrets Management category of a tech stack.
Vault is an open source tool with 14.6K GitHub stars and 2.2K GitHub forks. Here’s a link to Vault's open source repository on GitHub

Who uses Vault?

Companies
112 companies reportedly use Vault in their tech stacks, including DigitalOcean, Redox Engine, and HashiCorp.

Developers
142 developers on StackShare have stated that they use Vault.

Why developers like Vault?

Here’s a list of reasons why companies and developers use Vault
Vault Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Vault in their tech stack.

Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD · | 15 upvotes · 368.4K views
Vagrant
Vagrant
VirtualBox
VirtualBox
Ansible
Ansible
Elasticsearch
Elasticsearch
Kibana
Kibana
Logstash
Logstash
TeamCity
TeamCity
Jenkins
Jenkins
Slack
Slack
Apache Maven
Apache Maven
Vault
Vault
Git
Git
Docker
Docker
CircleCI
CircleCI
LXC
LXC
Amazon EC2
Amazon EC2

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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Joseph Irving
Joseph Irving
DevOps Engineer at uSwitch · | 8 upvotes · 8.1K views
atuSwitchuSwitch
Vault
Vault
Kubernetes
Kubernetes
MySQL
MySQL
PostgreSQL
PostgreSQL
Go
Go

At uSwitch we use Vault to generate short lived database credentials for our applications running in Kubernetes. We wanted to move from an environment where we had 100 dbs with a variety of static passwords being shared around to a place where each pod would have credentials that only last for its lifetime.

We chose vault because:

  • It had built in Kubernetes support so we could use service accounts to permission which pods could access which database.

  • A terraform provider so that we could configure both our RDS instances and their vault configuration in one place.

  • A variety of database providers including MySQL/PostgreSQL (our most common dbs).

  • A good api/Go -sdk so that we could build tooling around it to simplify development worfklow.

  • It had other features we would utilise such as PKI

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David Galoyan
David Galoyan
Docker
Docker
Concourse
Concourse
Ansible
Ansible
Vault
Vault
#DeploymentWorkflow

We use Docker for our #DeploymentWorkflow along with Concourse for build pipelines and Ansible for deployment together with Vault to manage secrets.

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Gonçalo Faustino
Gonçalo Faustino
Docker
Docker
OpenShift
OpenShift
SonarQube
SonarQube
Sonatype Nexus
Sonatype Nexus
GitLab
GitLab
Vault
Vault
Apache Maven
Apache Maven
AngularJS
AngularJS
Spring Boot
Spring Boot
#DeploymentWorkflow

We use Docker for our #DeploymentWorkflow along with OpenShift SonarQube Sonatype Nexus GitLab Vault Apache Maven AngularJS Spring-Boot

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Vault's Features

  • 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 keypair 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 it. 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.

Vault Alternatives & Comparisons

What are some alternatives to Vault?
AWS Secrets Manager
AWS Secrets Manager helps you protect secrets needed to access your applications, services, and IT resources. The service enables you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle.
Docker Secrets
A container native solution that strengthens the Trusted Delivery component of container security by integrating secret distribution directly into the container platform.
Keywhiz
Keywhiz is a secret management and distribution service that is now available for everyone. Keywhiz helps us with infrastructure secrets, including TLS certificates and keys, GPG keyrings, symmetric keys, database credentials, API tokens, and SSH keys for external services — and even some non-secrets like TLS trust stores. Automation with Keywhiz allows us to seamlessly distribute and generate the necessary secrets for our services, which provides a consistent and secure environment, and ultimately helps us ship faster.
Torus CLI
Torus simplifies the modern development workflow enabling you to store, share, and organize secrets across services and environments. With Torus, you can standardize on one tool across all environments. Map Torus to your workflows using projects, environments, services, teams, and machines.
SecretHub
All software needs secrets to access other resources: encryption keys, API tokens, database passwords. Helps teams deploy those application secrets to any cloud with a secure, automatic and reproducible deployment process.
See all alternatives

Vault's Followers
214 developers follow Vault to keep up with related blogs and decisions.
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infinity7592