Alternatives to MSSQL logo

Alternatives to MSSQL

MySQL, PostgreSQL, Oracle, IBM DB2, and MongoDB are the most popular alternatives and competitors to MSSQL.
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What is MSSQL and what are its top alternatives?

It is capable of storing any type of data that you want. It will let you quickly store and retrieve information and multiple web site visitors can use it at one time.
MSSQL is a tool in the Databases category of a tech stack.

Top Alternatives to MSSQL

  • MySQL
    MySQL

    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software. ...

  • PostgreSQL
    PostgreSQL

    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions. ...

  • Oracle
    Oracle

    Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database. ...

  • IBM DB2
    IBM DB2

    DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs. ...

  • MongoDB
    MongoDB

    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding. ...

  • Firebird
    Firebird

    Firebird is a relational database offering many ANSI SQL standard features that runs on Linux, Windows, MacOS and a variety of Unix platforms. Firebird offers excellent concurrency, high performance, and powerful language support for stored procedures and triggers. It has been used in production systems, under a variety of names, since 1981. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

MSSQL alternatives & related posts

MySQL logo

MySQL

123.7K
104.6K
3.7K
The world's most popular open source database
123.7K
104.6K
+ 1
3.7K
PROS OF MYSQL
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 489
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 78
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 16
    SSL support
  • 15
    Reliable
  • 14
    Robust
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 2
    NoSQL access to JSON data type
  • 1
    Relational database
  • 1
    Easy, light, scalable
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support
CONS OF MYSQL
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes

related MySQL posts

Nick Rockwell
SVP, Engineering at Fastly · | 46 upvotes · 3.6M views

When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

See more
Tim Abbott

We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

I can't recommend it highly enough.

See more
PostgreSQL logo

PostgreSQL

96.9K
81.1K
3.5K
A powerful, open source object-relational database system
96.9K
81.1K
+ 1
3.5K
PROS OF POSTGRESQL
  • 763
    Relational database
  • 510
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
  • 173
    Great community
  • 147
    Easy to setup
  • 131
    Heroku
  • 130
    Secure by default
  • 113
    Postgis
  • 50
    Supports Key-Value
  • 48
    Great JSON support
  • 34
    Cross platform
  • 33
    Extensible
  • 28
    Replication
  • 26
    Triggers
  • 23
    Multiversion concurrency control
  • 23
    Rollback
  • 21
    Open source
  • 18
    Heroku Add-on
  • 17
    Stable, Simple and Good Performance
  • 15
    Powerful
  • 13
    Lets be serious, what other SQL DB would you go for?
  • 11
    Good documentation
  • 9
    Scalable
  • 8
    Intelligent optimizer
  • 8
    Free
  • 8
    Reliable
  • 7
    Transactional DDL
  • 7
    Modern
  • 6
    One stop solution for all things sql no matter the os
  • 5
    Faster Development
  • 5
    Relational database with MVCC
  • 4
    Full-Text Search
  • 4
    Developer friendly
  • 3
    Great DB for Transactional system or Application
  • 3
    Free version
  • 3
    Excellent source code
  • 3
    Relational datanbase
  • 3
    search
  • 3
    Open-source
  • 2
    Full-text
  • 2
    Text
  • 1
    Multiple procedural languages supported
  • 1
    Can handle up to petabytes worth of size
  • 0
    Native
CONS OF POSTGRESQL
  • 10
    Table/index bloatings

related PostgreSQL posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
Jeyabalaji Subramanian

Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

Based on the above criteria, we selected the following tools to perform the end to end data replication:

We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

See more
Oracle logo

Oracle

2.3K
1.7K
113
An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism
2.3K
1.7K
+ 1
113
PROS OF ORACLE
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
  • 4
    Maintainable
  • 4
    Hard to use
  • 3
    High complexity
CONS OF ORACLE
  • 14
    Expensive

related Oracle posts

Saurav Pandit
Application Devloper at Bny Mellon · | 9 upvotes · 290.4K views

I have just started learning Python 3 week back. I want to create REST api using python. The api will be use to save form data in Oracle database. The front end is using AngularJS 8 with Angular Material. In python there are so many framework for developing REST ** I am looking for some suggestions which REST framework to choose? ** Here are some feature I am looking for * Easy integration and unit testing like in Angular we just run command. * Code packageing, like in Java maven project we can build and package. I am looking for something which I can push in artifactory and deploy whole code as package. *Support for swagger/ OpenAPI * Support for JSON Web Token * Support for testcase coverage report Framework can have feature included or can be available by extension.

See more
Dishi Jain
Shared insights
on
OracleOracleKubernetesKubernetes

So we are re-engineering our application database to make it cloud-native and deploy on the Kubernetes platform. Currently, our data lies on the Oracle 19c database and it is normalized extensively. We store pdfs, txt files and allow a user to edit, delete, view, create new transactions. Now I want to pick a DB, which makes the re-engineering, not a big deal but allows us to store data in a distributed manner on Kubernetes. Please assist me.

See more
IBM DB2 logo

IBM DB2

243
248
19
A family of database server products developed by IBM
243
248
+ 1
19
PROS OF IBM DB2
  • 7
    Rock solid and very scalable
  • 5
    BLU Analytics is amazingly fast
  • 2
    Native XML support
  • 2
    Secure by default
  • 2
    Easy
  • 1
    Best performance
CONS OF IBM DB2
    Be the first to leave a con

    related IBM DB2 posts

    MongoDB logo

    MongoDB

    92.4K
    79.8K
    4.1K
    The database for giant ideas
    92.4K
    79.8K
    + 1
    4.1K
    PROS OF MONGODB
    • 827
      Document-oriented storage
    • 593
      No sql
    • 553
      Ease of use
    • 464
      Fast
    • 410
      High performance
    • 257
      Free
    • 218
      Open source
    • 180
      Flexible
    • 145
      Replication & high availability
    • 112
      Easy to maintain
    • 42
      Querying
    • 39
      Easy scalability
    • 38
      Auto-sharding
    • 37
      High availability
    • 31
      Map/reduce
    • 27
      Document database
    • 25
      Easy setup
    • 25
      Full index support
    • 16
      Reliable
    • 15
      Fast in-place updates
    • 14
      Agile programming, flexible, fast
    • 12
      No database migrations
    • 8
      Easy integration with Node.Js
    • 8
      Enterprise
    • 6
      Enterprise Support
    • 5
      Great NoSQL DB
    • 4
      Support for many languages through different drivers
    • 3
      Schemaless
    • 3
      Aggregation Framework
    • 3
      Drivers support is good
    • 2
      Fast
    • 2
      Managed service
    • 2
      Easy to Scale
    • 2
      Awesome
    • 2
      Consistent
    • 1
      Good GUI
    • 1
      Acid Compliant
    CONS OF MONGODB
    • 6
      Very slowly for connected models that require joins
    • 3
      Not acid compliant
    • 2
      Proprietary query language

    related MongoDB posts

    Shared insights
    on
    Node.jsNode.jsGraphQLGraphQLMongoDBMongoDB

    I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery

    For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:

    1. Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have

    2. GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.

    3. MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website

    See more
    Vaibhav Taunk
    Team Lead at Technovert · | 31 upvotes · 4M views

    I am starting to become a full-stack developer, by choosing and learning .NET Core for API Development, Angular CLI / React for UI Development, MongoDB for database, as it a NoSQL DB and Flutter / React Native for Mobile App Development. Using Postman, Markdown and Visual Studio Code for development.

    See more
    Firebird logo

    Firebird

    82
    120
    9
    Relational database offering many ANSI SQL standard features that runs on Linux, Windows, and a variety of Unix...
    82
    120
    + 1
    9
    PROS OF FIREBIRD
    • 3
      Free
    • 3
      Open-Source
    • 1
      Upgrade from MySQL, MariaDB, PostgreSQL
    • 1
      Easy Setup
    • 1
      Great Performance
    CONS OF FIREBIRD
    • 2
      Speed

    related Firebird posts

    JavaScript logo

    JavaScript

    354.2K
    269.4K
    8.1K
    Lightweight, interpreted, object-oriented language with first-class functions
    354.2K
    269.4K
    + 1
    8.1K
    PROS OF JAVASCRIPT
    • 1.7K
      Can be used on frontend/backend
    • 1.5K
      It's everywhere
    • 1.2K
      Lots of great frameworks
    • 897
      Fast
    • 745
      Light weight
    • 425
      Flexible
    • 392
      You can't get a device today that doesn't run js
    • 286
      Non-blocking i/o
    • 237
      Ubiquitousness
    • 191
      Expressive
    • 55
      Extended functionality to web pages
    • 49
      Relatively easy language
    • 46
      Executed on the client side
    • 30
      Relatively fast to the end user
    • 25
      Pure Javascript
    • 21
      Functional programming
    • 15
      Async
    • 13
      Full-stack
    • 12
      Setup is easy
    • 12
      Future Language of The Web
    • 12
      Its everywhere
    • 11
      Because I love functions
    • 11
      JavaScript is the New PHP
    • 10
      Like it or not, JS is part of the web standard
    • 9
      Expansive community
    • 9
      Everyone use it
    • 9
      Can be used in backend, frontend and DB
    • 9
      Easy
    • 8
      Most Popular Language in the World
    • 8
      Powerful
    • 8
      Can be used both as frontend and backend as well
    • 8
      For the good parts
    • 8
      No need to use PHP
    • 8
      Easy to hire developers
    • 7
      Agile, packages simple to use
    • 7
      Love-hate relationship
    • 7
      Photoshop has 3 JS runtimes built in
    • 7
      Evolution of C
    • 7
      It's fun
    • 7
      Hard not to use
    • 7
      Versitile
    • 7
      Its fun and fast
    • 7
      Nice
    • 7
      Popularized Class-Less Architecture & Lambdas
    • 7
      Supports lambdas and closures
    • 6
      It let's me use Babel & Typescript
    • 6
      Can be used on frontend/backend/Mobile/create PRO Ui
    • 6
      1.6K Can be used on frontend/backend
    • 6
      Client side JS uses the visitors CPU to save Server Res
    • 6
      Easy to make something
    • 5
      Clojurescript
    • 5
      Promise relationship
    • 5
      Stockholm Syndrome
    • 5
      Function expressions are useful for callbacks
    • 5
      Scope manipulation
    • 5
      Everywhere
    • 5
      Client processing
    • 5
      What to add
    • 4
      Because it is so simple and lightweight
    • 4
      Only Programming language on browser
    • 1
      Test
    • 1
      Hard to learn
    • 1
      Test2
    • 1
      Not the best
    • 1
      Easy to understand
    • 1
      Subskill #4
    • 1
      Easy to learn
    • 0
      Hard 彤
    CONS OF JAVASCRIPT
    • 22
      A constant moving target, too much churn
    • 20
      Horribly inconsistent
    • 15
      Javascript is the New PHP
    • 9
      No ability to monitor memory utilitization
    • 8
      Shows Zero output in case of ANY error
    • 7
      Thinks strange results are better than errors
    • 6
      Can be ugly
    • 3
      No GitHub
    • 2
      Slow
    • 0
      HORRIBLE DOCUMENTS, faulty code, repo has bugs

    related JavaScript posts

    Zach Holman

    Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

    But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

    But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

    Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

    See more
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 11.2M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Git logo

    Git

    293.4K
    175.6K
    6.6K
    Fast, scalable, distributed revision control system
    293.4K
    175.6K
    + 1
    6.6K
    PROS OF GIT
    • 1.4K
      Distributed version control system
    • 1.1K
      Efficient branching and merging
    • 959
      Fast
    • 845
      Open source
    • 726
      Better than svn
    • 368
      Great command-line application
    • 306
      Simple
    • 291
      Free
    • 232
      Easy to use
    • 222
      Does not require server
    • 27
      Distributed
    • 22
      Small & Fast
    • 18
      Feature based workflow
    • 15
      Staging Area
    • 13
      Most wide-spread VSC
    • 11
      Role-based codelines
    • 11
      Disposable Experimentation
    • 7
      Frictionless Context Switching
    • 6
      Data Assurance
    • 5
      Efficient
    • 4
      Just awesome
    • 3
      Github integration
    • 3
      Easy branching and merging
    • 2
      Compatible
    • 2
      Flexible
    • 2
      Possible to lose history and commits
    • 1
      Rebase supported natively; reflog; access to plumbing
    • 1
      Light
    • 1
      Team Integration
    • 1
      Fast, scalable, distributed revision control system
    • 1
      Easy
    • 1
      Flexible, easy, Safe, and fast
    • 1
      CLI is great, but the GUI tools are awesome
    • 1
      It's what you do
    • 0
      Phinx
    CONS OF GIT
    • 16
      Hard to learn
    • 11
      Inconsistent command line interface
    • 9
      Easy to lose uncommitted work
    • 7
      Worst documentation ever possibly made
    • 5
      Awful merge handling
    • 3
      Unexistent preventive security flows
    • 3
      Rebase hell
    • 2
      When --force is disabled, cannot rebase
    • 2
      Ironically even die-hard supporters screw up badly
    • 1
      Doesn't scale for big data

    related Git posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more
    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 8.9M views

    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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