Alternatives to SST logo

Alternatives to SST

NGINX, Apache HTTP Server, Amazon EC2, Firebase, and Amazon Web Services (AWS) are the most popular alternatives and competitors to SST.
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What is SST and what are its top alternatives?

SST, short for Serverless Stack, is a comprehensive guide and tool that helps developers build full-stack serverless applications on AWS. The key features of SST include easy setup and deployment of serverless resources, integration with popular AWS services like API Gateway and DynamoDB, and a strong focus on best practices for security and scalability in serverless development. However, some limitations of SST include its AWS-specific nature, which may not be suitable for developers looking for a more platform-agnostic solution, and the learning curve for beginners in serverless development.

  1. Serverless Framework: Serverless Framework is one of the most popular open-source tools for building and deploying serverless applications across different cloud providers. It offers a broad range of plugins and integrations, making it highly flexible. However, it may have a steeper learning curve compared to SST.
  2. AWS Amplify: AWS Amplify is a set of tools and services for building full-stack serverless applications on AWS. It offers a simplified developer experience, with features like authentication, data storage, and hosting. However, it may be more limited in terms of customization compared to SST.
  3. Azure Functions: Azure Functions is a serverless computing service provided by Microsoft Azure. It allows developers to build and deploy event-driven applications using various programming languages. Compared to SST, Azure Functions offers cross-platform support but may have differences in features and integrations.
  4. Google Cloud Functions: Google Cloud Functions is a serverless execution environment for building and connecting cloud services. It supports multiple programming languages and integrates with other Google Cloud services. However, compared to SST, Google Cloud Functions may have differences in pricing and features.
  5. Netlify Functions: Netlify Functions is a serverless compute service provided by Netlify for building and deploying serverless functions as part of web applications. It offers seamless integration with Netlify hosting and Git-based workflows. Compared to SST, Netlify Functions may have limitations in terms of scalability and pricing.
  6. Vercel Serverless Functions: Vercel offers a serverless function platform for deploying serverless functions quickly and easily. It integrates seamlessly with Vercel hosting and Git repositories. However, compared to SST, Vercel Serverless Functions may be more focused on frontend applications.
  7. Firebase Cloud Functions: Firebase Cloud Functions is a serverless compute service provided by Google Firebase for building event-driven serverless functions. It integrates with other Firebase services for building mobile and web applications. Compared to SST, Firebase Cloud Functions may have limitations in terms of customization and third-party integrations.
  8. Kubeless: Kubeless is a serverless framework built on top of Kubernetes, allowing developers to deploy functions on Kubernetes clusters. It offers more control and customization compared to SST but may require more advanced knowledge of Kubernetes.
  9. OpenFaaS: OpenFaaS is an open-source serverless platform that runs on Kubernetes. It offers a flexible and extensible serverless experience, allowing developers to build and deploy functions easily. Compared to SST, OpenFaaS may require more setup and configuration but offers greater control over deployment.
  10. Nuclio: Nuclio is a real-time serverless platform that runs on Kubernetes and allows developers to build and deploy serverless functions quickly and efficiently. It offers high performance and scalability for event-driven applications. Compared to SST, Nuclio may have a more specialized use case for real-time applications.

Top Alternatives to SST

  • NGINX
    NGINX

    nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...

  • Apache HTTP Server
    Apache HTTP Server

    The Apache HTTP Server is a powerful and flexible HTTP/1.1 compliant web server. Originally designed as a replacement for the NCSA HTTP Server, it has grown to be the most popular web server on the Internet. ...

  • Amazon EC2
    Amazon EC2

    It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers. ...

  • Firebase
    Firebase

    Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds. ...

  • Amazon Web Services (AWS)
    Amazon Web Services (AWS)

    It is a comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. ...

  • Heroku
    Heroku

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling. ...

  • Google Cloud Platform
    Google Cloud Platform

    It helps you build what's next with secure infrastructure, developer tools, APIs, data analytics and machine learning. It is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. ...

  • Microsoft Azure
    Microsoft Azure

    Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment. ...

SST alternatives & related posts

NGINX logo

NGINX

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60.8K
5.5K
A high performance free open source web server powering busiest sites on the Internet.
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PROS OF NGINX
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    High-performance http server
  • 894
    Performance
  • 730
    Easy to configure
  • 607
    Open source
  • 530
    Load balancer
  • 289
    Free
  • 288
    Scalability
  • 226
    Web server
  • 175
    Simplicity
  • 136
    Easy setup
  • 30
    Content caching
  • 21
    Web Accelerator
  • 15
    Capability
  • 14
    Fast
  • 12
    High-latency
  • 12
    Predictability
  • 8
    Reverse Proxy
  • 7
    The best of them
  • 7
    Supports http/2
  • 5
    Great Community
  • 5
    Lots of Modules
  • 5
    Enterprise version
  • 4
    High perfomance proxy server
  • 3
    Embedded Lua scripting
  • 3
    Streaming media delivery
  • 3
    Streaming media
  • 3
    Reversy Proxy
  • 2
    Blash
  • 2
    GRPC-Web
  • 2
    Lightweight
  • 2
    Fast and easy to set up
  • 2
    Slim
  • 2
    saltstack
  • 1
    Virtual hosting
  • 1
    Narrow focus. Easy to configure. Fast
  • 1
    Along with Redis Cache its the Most superior
  • 1
    Ingress controller
CONS OF NGINX
  • 10
    Advanced features require subscription

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Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 10.7M 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
John-Daniel Trask
Co-founder & CEO at Raygun · | 19 upvotes · 276.5K views

We chose AWS because, at the time, it was really the only cloud provider to choose from.

We tend to use their basic building blocks (EC2, ELB, Amazon S3, Amazon RDS) rather than vendor specific components like databases and queuing. We deliberately decided to do this to ensure we could provide multi-cloud support or potentially move to another cloud provider if the offering was better for our customers.

We’ve utilized c3.large nodes for both the Node.js deployment and then for the .NET Core deployment. Both sit as backends behind an nginx instance and are managed using scaling groups in Amazon EC2 sitting behind a standard AWS Elastic Load Balancing (ELB).

While we’re satisfied with AWS, we do review our decision each year and have looked at Azure and Google Cloud offerings.

#CloudHosting #WebServers #CloudStorage #LoadBalancerReverseProxy

See more
Apache HTTP Server logo

Apache HTTP Server

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Open-source HTTP server for modern operating systems including UNIX and Windows
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    Since 1996
  • 28
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  • 5
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  • 4
    Proven over many years
  • 2
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  • 0
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Nick Rockwell
SVP, Engineering at Fastly · | 46 upvotes · 3.9M 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
Shared insights
on
NGINXNGINXApache HTTP ServerApache HTTP Server
at

We've been happy with nginx as part of our stack. As an open source web application that folks install on-premise, the configuration system for the webserver is pretty important to us. I have a few complaints (e.g. the configuration syntax for conditionals is a pain), but overall we've found it pretty easy to build a configurable set of options (see link) for how to run Zulip on nginx, both directly and with a remote reverse proxy in front of it, with a minimum of code duplication.

Certainly I've been a lot happier with it than I was working with Apache HTTP Server in past projects.

See more
Amazon EC2 logo

Amazon EC2

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    Free tier
  • 58
    Easy management, scalability
  • 13
    Flexible
  • 10
    Easy to Start
  • 9
    Widely used
  • 9
    Web-scale
  • 9
    Elastic
  • 7
    Node.js API
  • 5
    Industry Standard
  • 4
    Lots of configuration options
  • 2
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Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 38 upvotes · 3.1M views

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

See more
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 10.7M 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
Firebase logo

Firebase

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  • 83
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  • 68
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    Great customer support
  • 32
    Great documentation
  • 25
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  • 21
    Mobile friendly
  • 19
    Rapid prototyping
  • 14
    Great security
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    Automatic scaling
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    Freakingly awesome
  • 8
    Super fast development
  • 8
    Angularfire is an amazing addition!
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  • 3
    Great
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    It's made development super fast
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  • 2
    Free hosting
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    JS Offline and Sync suport
  • 2
    Low battery consumption
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    The concurrent updates create a great experience
  • 2
    Push notification
  • 2
    I can quickly create static web apps with no backend
  • 2
    Great all-round functionality
  • 2
    Free authentication solution
  • 1
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    Google's support
  • 1
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    CDN & cache out of the box
  • 1
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  • 1
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  • 31
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  • 16
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  • 15
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  • 9
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  • 7
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  • 3
    Very unstable server
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    No Relational Data
  • 2
    Too many errors
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Stephen Gheysens
Lead Solutions Engineer at Inscribe · | 14 upvotes · 1.8M views

Hi Otensia! I'd definitely recommend using the skills you've already got and building with JavaScript is a smart way to go these days. Most platform services have JavaScript/Node SDKs or NPM packages, many serverless platforms support Node in case you need to write any backend logic, and JavaScript is incredibly popular - meaning it will be easy to hire for, should you ever need to.

My advice would be "don't reinvent the wheel". If you already have a skill set that will work well to solve the problem at hand, and you don't need it for any other projects, don't spend the time jumping into a new language. If you're looking for an excuse to learn something new, it would be better to invest that time in learning a new platform/tool that compliments your knowledge of JavaScript. For this project, I might recommend using Netlify, Vercel, or Google Firebase to quickly and easily deploy your web app. If you need to add user authentication, there are great examples out there for Firebase Authentication, Auth0, or even Magic (a newcomer on the Auth scene, but very user friendly). All of these services work very well with a JavaScript-based application.

See more
Eugene Cheah

For inboxkitten.com, an opensource disposable email service;

We migrated our serverless workload from Cloud Functions for Firebase to CloudFlare workers, taking advantage of the lower cost and faster-performing edge computing of Cloudflare network. Made possible due to our extremely low CPU and RAM overhead of our serverless functions.

If I were to summarize the limitation of Cloudflare (as oppose to firebase/gcp functions), it would be ...

  1. <5ms CPU time limit
  2. Incompatible with express.js
  3. one script limitation per domain

Limitations our workload is able to conform with (YMMV)

For hosting of static files, we migrated from Firebase to CommonsHost

More details on the trade-off in between both serverless providers is in the article

See more
Amazon Web Services (AWS) logo

Amazon Web Services (AWS)

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A comprehensive and broadly adopted cloud platform
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      waheed khan
      Associate Java Developer at txtsol · | 8 upvotes · 45K views

      I want to make application like Zomato, #Foodpanda.

      Which stack is best for this? As I have expertise in Java and Angular. What is the best stack you will recommend?

      Web Micro-service / Mono? Angular / React? Amazon Web Services (AWS) / Google Cloud Platform? DB : SQL or No SQL

      Mob Cross-platform: React Native / Flutter

      Note: We are a team of 5. what languages do you recommend if I go with microservices?

      Thanks

      See more
      Santiago Velasco
      Java Software Developer at ViewNext · | 8 upvotes · 15.6K views

      Hello everyone, I would like to start using a cloud service to host my projects, which are web applications. If anyone has enough experience with Microsoft Azure, Amazon Web Services (AWS) or Google Cloud Platform, I would like to know which of these is most recommended to use, depending on the features they have or how used they are. Thank you so much.

      See more
      Heroku logo

      Heroku

      25.5K
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      Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
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      • 24
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      • 19
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      Russel Werner
      Lead Engineer at StackShare · | 32 upvotes · 2.6M views

      StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

      Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

      #StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

      See more
      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 10.7M 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
      Google Cloud Platform logo

      Google Cloud Platform

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      A suite of cloud computing services
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      CONS OF GOOGLE CLOUD PLATFORM
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        My days of using Firebase are over! I want to move to something scalable and possibly less cheap. In the past seven days I have done my research on what type of DB best fits my needs, and have chosen to go with the nonrelational DB; MongoDB. Although I understand it, I need help understanding how to set up the architecture. I have the client app (Flutter/ Dart) that would make HTTP requests to the web server (node/express), and from there the webserver would query data from MongoDB.

        How should I go about hosting the web server and MongoDb; do they have to be hosted together (this is where a lot of my confusion is)? Based on the research I've done, it seems like the standard practice would be to host on a VM provided by services such as Amazon Web Services, Google Cloud Platform, Microsoft Azure, etc. If there are better ways, such as possibly self-hosting (more responsibility), should I? Anyways, I just want to confirm with a community (you guys) to make sure I do this right, all input is highly appreciated.

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        waheed khan
        Associate Java Developer at txtsol · | 8 upvotes · 45K views

        I want to make application like Zomato, #Foodpanda.

        Which stack is best for this? As I have expertise in Java and Angular. What is the best stack you will recommend?

        Web Micro-service / Mono? Angular / React? Amazon Web Services (AWS) / Google Cloud Platform? DB : SQL or No SQL

        Mob Cross-platform: React Native / Flutter

        Note: We are a team of 5. what languages do you recommend if I go with microservices?

        Thanks

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        Ganesa Vijayakumar
        Full Stack Coder | Technical Architect · | 19 upvotes · 5.3M views

        I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

        I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

        As per my work experience and knowledge, I have chosen the followings stacks to this mission.

        UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

        Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

        Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

        Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

        Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

        Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

        Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

        Happy Coding! Suggestions are welcome! :)

        Thanks, Ganesa

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        Omar Mehilba
        Co-Founder and COO at Magalix · | 19 upvotes · 424.9K views

        We are hardcore Kubernetes users and contributors. We loved the automation it provides. However, as our team grew and added more clusters and microservices, capacity and resources management becomes a massive pain to us. We started suffering from a lot of outages and unexpected behavior as we promote our code from dev to production environments. Luckily we were working on our AI-powered tools to understand different dependencies, predict usage, and calculate the right resources and configurations that should be applied to our infrastructure and microservices. We dogfooded our agent (http://github.com/magalixcorp/magalix-agent) and were able to stabilize as the #autopilot continuously recovered any miscalculations we made or because of unexpected changes in workloads. We are open sourcing our agent in a few days. Check it out and let us know what you think! We run workloads on Microsoft Azure Google Kubernetes Engine and Amazon EC2 and we're all about Go and Python!

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