Bazel vs Kubernetes

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Bazel vs Kubernetes: What are the differences?

Bazel: Correct, reproducible, fast builds for everyone. Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment; Kubernetes: Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops. Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Bazel belongs to "Java Build Tools" category of the tech stack, while Kubernetes can be primarily classified under "Container Tools".

Some of the features offered by Bazel are:

  • Multi-language support: Bazel supports Java, Objective-C and C++ out of the box, and can be extended to support arbitrary programming languages.
  • High-level build language: Projects are described in the BUILD language, a concise text format that describes a project as sets of small interconnected libraries, binaries and tests. By contrast, with tools like Make you have to describe individual files and compiler invocations.
  • Multi-platform support: The same tool and the same BUILD files can be used to build software for different architectures, and even different platforms. At Google, we use Bazel to build both server applications running on systems in our data centers and client apps running on mobile phones.

On the other hand, Kubernetes provides the following key features:

  • Lightweight, simple and accessible
  • Built for a multi-cloud world, public, private or hybrid
  • Highly modular, designed so that all of its components are easily swappable

"Fast" is the primary reason why developers consider Bazel over the competitors, whereas "Leading docker container management solution" was stated as the key factor in picking Kubernetes.

Bazel and Kubernetes are both open source tools. Kubernetes with 55K GitHub stars and 19.1K forks on GitHub appears to be more popular than Bazel with 12.4K GitHub stars and 2.02K GitHub forks.

Google, Slack, and Shopify are some of the popular companies that use Kubernetes, whereas Bazel is used by Google, Asana, and Square. Kubernetes has a broader approval, being mentioned in 1046 company stacks & 1096 developers stacks; compared to Bazel, which is listed in 11 company stacks and 7 developer stacks.

What is Bazel?

Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment.

What is Kubernetes?

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
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What are some alternatives to Bazel and Kubernetes?
Pants
Pants is a build system for Java, Scala and Python. It works particularly well for a source code repository that contains many distinct projects.
Webpack
A bundler for javascript and friends. Packs many modules into a few bundled assets. Code Splitting allows to load parts for the application on demand. Through "loaders" modules can be CommonJs, AMD, ES6 modules, CSS, Images, JSON, Coffeescript, LESS, ... and your custom stuff.
Buck
Buck encourages the creation of small, reusable modules consisting of code and resources, and supports a variety of languages on many platforms.
Ansible
Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.
CMake
It is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of the user's choice.
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Decisions about Bazel and Kubernetes
Yshay Yaacobi
Yshay Yaacobi
Software Engineer · | 27 upvotes · 294K views
atSolutoSoluto
Docker Swarm
Docker Swarm
Kubernetes
Kubernetes
Visual Studio Code
Visual Studio Code
Go
Go
TypeScript
TypeScript
JavaScript
JavaScript
C#
C#
F#
F#
.NET
.NET

Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

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Sebastian Gębski
Sebastian Gębski
CTO at Shedul/Fresha · | 6 upvotes · 51K views
atFresha EngineeringFresha Engineering
Amazon RDS
Amazon RDS
Amazon S3
Amazon S3
Amazon EKS
Amazon EKS
Amazon EC2
Amazon EC2
Ansible
Ansible
Terraform
Terraform
Kubernetes
Kubernetes
Docker Compose
Docker Compose
Docker
Docker

Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

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Emanuel Evans
Emanuel Evans
Senior Architect at Rainforest QA · | 12 upvotes · 131.7K views
atRainforest QARainforest QA
Terraform
Terraform
Helm
Helm
Google Cloud Build
Google Cloud Build
CircleCI
CircleCI
Redis
Redis
Google Cloud Memorystore
Google Cloud Memorystore
PostgreSQL
PostgreSQL
Google Cloud SQL for PostgreSQL
Google Cloud SQL for PostgreSQL
Google Kubernetes Engine
Google Kubernetes Engine
Kubernetes
Kubernetes
Heroku
Heroku

We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

Read the blog post to go more in depth.

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GitHub
GitHub
nginx
nginx
ESLint
ESLint
AVA
AVA
Semantic UI React
Semantic UI React
Redux
Redux
React
React
PostgreSQL
PostgreSQL
ExpressJS
ExpressJS
Node.js
Node.js
FeathersJS
FeathersJS
Heroku
Heroku
Amazon EC2
Amazon EC2
Kubernetes
Kubernetes
Jenkins
Jenkins
Docker Compose
Docker Compose
Docker
Docker
#Containerized
#Containers
#Backend
#Stack
#Frontend

Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

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Ido Shamun
Ido Shamun
at The Elegant Monkeys · | 6 upvotes · 49K views
atDailyDaily
Helm
Helm
Docker
Docker
CircleCI
CircleCI
GitHub
GitHub
Kubernetes
Kubernetes

Kubernetes powers our #backend services as it is very easy in terms of #devops (the managed version). We deploy everything using @helm charts as it provides us to manage deployments the same way we manage our code on GitHub . On every commit a CircleCI job is triggered to run the tests, build Docker images and deploy them to the registry. Finally on every master commit CircleCI also deploys the relevant service using Helm chart to our Kubernetes cluster

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Russel Werner
Russel Werner
Lead Engineer at StackShare · | 0 upvotes · 5.5K views
atStackShareStackShare
Amazon EC2 Container Service
Amazon EC2 Container Service
CircleCI
CircleCI
Helm
Helm
Slack
Slack
Google Kubernetes Engine
Google Kubernetes Engine
Amazon EKS
Amazon EKS
Kubernetes
Kubernetes
Heroku
Heroku

We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.

We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.

The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.

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Robert Zuber
Robert Zuber
CTO at CircleCI · | 6 upvotes · 14.6K views
atCircleCICircleCI
Helm
Helm
Nomad
Nomad
Kubernetes
Kubernetes
Docker
Docker

Our backend consists of two major pools of machines. One pool hosts the systems that run our site, manage jobs, and send notifications. These services are deployed within Docker containers orchestrated in Kubernetes. Due to Kubernetes’ ecosystem and toolchain, it was an obvious choice for our fairly statically-defined processes: the rate of change of job types or how many we may need in our internal stack is relatively low.

The other pool of machines is for running our users’ jobs. Because we cannot dynamically predict demand, what types of jobs our users need to have run, nor the resources required for each of those jobs, we found that Nomad excelled over Kubernetes in this area.

We’re also using Helm to make it easier to deploy new services into Kubernetes. We create a chart (i.e. package) for each service. This lets us easily roll back new software and gives us an audit trail of what was installed or upgraded.

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Interest over time
Reviews of Bazel and Kubernetes
Review ofKubernetesKubernetes

It's a little bit complex to onboard, but once you grasp all the different concepts the platform is really powerful, and infrastructure stops being an issue.

Service discovery, auto-recovery, scaling and orchestration are just a few of the features you get.

How developers use Bazel and Kubernetes
Avatar of Matt Welke
Matt Welke uses KubernetesKubernetes

Just tinkering with it for personal use at this stage based on positive experience using it at work. Plan to use it for high traffic distributed systems if not using a managed hosting service like Heroku, AWS Lambda, or Google Cloud Functions. Reasons for using instead of these alternatives would be cheaper cost at higher scale.

Avatar of realcloudratics
realcloudratics uses KubernetesKubernetes

Good existential question. Kubernetes is painful in the extreme - especially when combined with Ansible. The layers of indirection are truly mind altering. But hey - containers are kewl!

Avatar of Japan Digital Design
Japan Digital Design uses KubernetesKubernetes

Our developer experience system is on Kubernetes (Google Kubernetes Engine at the moment). We would like to expand our Kubernetes clusters over other Kubernetes engine.

Avatar of ShareThis
ShareThis uses KubernetesKubernetes

Kubernetes is used for managing microclusters within our AWS infrastructure. This allows us to deploy new infrastructure in seconds.

Avatar of papaver
papaver uses KubernetesKubernetes

minor experience with kubernetes. helped a client setup a kubernetes infrastructure. love the elegance of the system.

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