What is Jelastic and what are its top alternatives?
Jelastic is a multifunctional Platform as a Service (PaaS) that offers cloud hosting solutions for Java, PHP, Ruby, Node.js, Python, and Docker. It provides scalability, high availability, and automation in managing applications on the cloud. Key features include automatic vertical scaling, automatic clustering, multi-cloud support, and Docker containers support. However, some limitations of Jelastic may include limited support for certain programming languages and frameworks, complex pricing structure, and potential performance issues.
Heroku: Heroku is a cloud platform that lets developers build, deliver, monitor, and scale applications. Key features include support for multiple programming languages, easy integration with various tools and services, and seamless deployment process. Pros of Heroku include ease of use, scalability, and robust ecosystem of add-ons. Cons may include limited configuration options for certain applications and pricing based on resource usage.
AWS Elastic Beanstalk: AWS Elastic Beanstalk is a platform that allows for easy deployment and management of applications on AWS. Key features include support for various programming languages, automatic scaling, and monitoring tools. Pros of Elastic Beanstalk include seamless integration with other AWS services, high scalability, and reliable infrastructure. Cons may include complex pricing structure and potential resource management challenges.
Google App Engine: Google App Engine is a fully managed serverless platform that supports multiple programming languages. Key features include auto-scaling, built-in security features, and seamless integration with other Google Cloud services. Pros of Google App Engine include high availability, robust infrastructure, and strong compliance standards. Cons may include limited flexibility in configuration and potential vendor lock-in.
Microsoft Azure App Service: Azure App Service is a platform that allows for building, deploying, and scaling web applications. Key features include support for multiple programming languages, auto-scaling, and integration with other Azure services. Pros of Azure App Service include high availability, seamless deployment process, and strong security features. Cons may include potential performance issues and complex pricing.
DigitalOcean App Platform: DigitalOcean App Platform is a platform that simplifies the deployment and scaling of web applications. Key features include automatic scaling, HTTPS encryption, and continuous deployment. Pros of DigitalOcean App Platform include ease of use, affordable pricing, and integration with other DigitalOcean services. Cons may include limited support for databases and potential resource limitations.
OpenShift: OpenShift is a Kubernetes-based platform that offers containerized application development and deployment. Key features include support for various programming languages, auto-scaling, and built-in monitoring tools. Pros of OpenShift include flexibility in deployment options, strong community support, and robust security features. Cons may include potential complexity in configuration and management.
IBM Cloud Foundry: IBM Cloud Foundry is a platform that enables developers to build, deploy, and scale applications with ease. Key features include support for multiple programming languages, auto-scaling, and integration with various IBM services. Pros of IBM Cloud Foundry include high availability, seamless deployment process, and strong security features. Cons may include potential vendor lock-in and complex pricing.
Oracle Cloud Platform: Oracle Cloud Platform offers a comprehensive set of cloud services for building, deploying, and managing applications. Key features include support for various programming languages, auto-scaling, and robust security features. Pros of Oracle Cloud Platform include reliability, integration with Oracle databases, and strong compliance standards. Cons may include limited documentation and potential complexity in setting up.
Pivotal Cloud Foundry: Pivotal Cloud Foundry is a platform that simplifies the deployment and management of cloud-native applications. Key features include support for multiple programming languages, auto-scaling, and containerization. Pros of Pivotal Cloud Foundry include flexibility in deployment options, seamless integration with CI/CD tools, and strong security features. Cons may include potential learning curve and pricing based on resource usage.
Red Hat OpenShift: Red Hat OpenShift is a Kubernetes-based platform that enables automated container provisioning, scaling, and management. Key features include support for various programming languages, auto-scaling, and built-in monitoring tools. Pros of Red Hat OpenShift include strong community support, robust security features, and flexibility in deployment options. Cons may include potential complexity in configuration and potential performance issues.
Top Alternatives to Jelastic
- Google App Engine
Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow. ...
- Amazon EBS
Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage. ...
- DigitalOcean
We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel. ...
- 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. ...
- 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. ...
- Cloud Foundry
Cloud Foundry is an open platform as a service (PaaS) that provides a choice of clouds, developer frameworks, and application services. Cloud Foundry makes it faster and easier to build, test, deploy, and scale applications. ...
- 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
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. ...
Jelastic alternatives & related posts
Google App Engine
- Easy to deploy145
- Auto scaling106
- Good free plan80
- Easy management62
- Scalability56
- Low cost35
- Comprehensive set of features32
- All services in one place28
- Simple scaling22
- Quick and reliable cloud servers19
- Granular Billing6
- Easy to develop and unit test5
- Monitoring gives comprehensive set of key indicators5
- Really easy to quickly bring up a full stack3
- Create APIs quickly with cloud endpoints3
- No Ops2
- Mostly up2
related Google App Engine posts
So, the shift from Amazon EC2 to Google App Engine and generally #AWS to #GCP was a long decision and in the end, it's one that we've taken with eyes open and that we reserve the right to modify at any time. And to be clear, we continue to do a lot of stuff with AWS. But, by default, the content of the decision was, for our consumer-facing products, we're going to use GCP first. And if there's some reason why we don't think that's going to work out great, then we'll happily use AWS. In practice, that hasn't really happened. We've been able to meet almost 100% of our needs in GCP.
So it's basically mostly Google Kubernetes Engine , we're mostly running stuff on Kubernetes right now.
#AWStoGCPmigration #cloudmigration #migration
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In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.
For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.
For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.
We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.
Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.
- Point-in-time snapshots36
- Data reliability27
- Configurable i/o performance19
related Amazon EBS posts
I could spin up an Amazon EC2 instance and install PostgreSQL myself, review latest configuration best practices, sort Amazon EBS storage for data, set up a snapshot process etc.
Alternatively I could use Amazon RDS, Amazon RDS for PostgreSQL or Heroku Postgres and have most of that work handled for me, by a team of world experts...
We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.
We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.
We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.
You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?
DigitalOcean
- Great value for money560
- Simple dashboard364
- Good pricing362
- Ssds300
- Nice ui250
- Easy configuration191
- Great documentation156
- Ssh access138
- Great community135
- Ubuntu24
- Docker13
- IPv6 support12
- Private networking10
- 99.99% uptime SLA8
- Simple API7
- Great tutorials7
- 55 Second Provisioning6
- One Click Applications5
- Dokku4
- LAMP4
- Debian4
- CoreOS4
- Node.js4
- 1Gb/sec Servers3
- Word Press3
- Mean3
- LEMP3
- Simple Control Panel3
- Ghost3
- Runs CoreOS2
- Quick and no nonsense service2
- Django2
- Good Tutorials2
- Speed2
- Ruby on Rails2
- GitLab2
- Hex Core machines with dedicated ECC Ram and RAID SSD s2
- CentOS1
- Spaces1
- KVM Virtualization1
- Amazing Hardware1
- Transfer Globally1
- Fedora1
- FreeBSD1
- Drupal1
- FreeBSD Amp1
- Magento1
- ownCloud1
- RedMine1
- My go to server provider1
- Ease and simplicity1
- Nice1
- Find it superfitting with my requirements (SSD, ssh.1
- Easy Setup1
- Cheap1
- Static IP1
- It's the easiest to get started for small projects1
- Automatic Backup1
- Great support1
- Quick and easy to set up1
- Servers on demand - literally1
- Reliability1
- Variety of services0
- Managed Kubernetes0
- No live support chat3
- Pricing3
related DigitalOcean posts
This week, we finally released NurseryPeople.com. In the end, I chose to provision our server on DigitalOcean. So far, I am SO happy with that decision. Although setting everything up was a challenge, and I learned a lot, DigitalOceans blogs helped in so many ways. I was able to set up nginx and the Laravel web app pretty smoothly. I am also using Buddy for deploying changes made in git, which is super awesome. All I have to do in order to deploy is push my code to my private repo, and buddy transfers everything over to DigitalOcean. So far, we haven't had any downtime and DigitalOceans prices are quite fair for the power under the hood.
Hello, I'm currently writing an e-commerce website with Laravel and Laravel Nova (as an admin panel). I want to start deploying the app and created a DigitalOcean account. After some searches about the deployment process, I saw that the setup via DigitalOcean (using Droplets) isn't very easy for beginners. Now I'm not sure how to deploy my app. I am in between Laravel Forge and DigitalOcean (?Apps Platform or Droplets?). I've read that Heroku and Laravel Vapor are a bit expensive. That's why I didn't consider them yet. I'd be happy to read your opinions on that topic!
Kubernetes
- Leading docker container management solution166
- Simple and powerful129
- Open source107
- Backed by google76
- The right abstractions58
- Scale services25
- Replication controller20
- Permission managment11
- Supports autoscaling9
- Simple8
- Cheap8
- Self-healing6
- Open, powerful, stable5
- Reliable5
- No cloud platform lock-in5
- Promotes modern/good infrascture practice5
- Scalable4
- Quick cloud setup4
- Custom and extensibility3
- Captain of Container Ship3
- Cloud Agnostic3
- Backed by Red Hat3
- Runs on azure3
- A self healing environment with rich metadata3
- Everything of CaaS2
- Gke2
- Golang2
- Easy setup2
- Expandable2
- Sfg2
- Steep learning curve16
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1
related Kubernetes posts
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
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...
Heroku
- Easy deployment703
- Free for side projects459
- Huge time-saver374
- Simple scaling348
- Low devops skills required261
- Easy setup190
- Add-ons for almost everything174
- Beginner friendly153
- Better for startups150
- Low learning curve133
- Postgres hosting48
- Easy to add collaborators41
- Faster development30
- Awesome documentation24
- Simple rollback19
- Focus on product, not deployment19
- Natural companion for rails development15
- Easy integration15
- Great customer support12
- GitHub integration8
- Painless & well documented6
- No-ops6
- I love that they make it free to launch a side project4
- Free4
- Great UI3
- Just works3
- PostgreSQL forking and following2
- MySQL extension2
- Security1
- Able to host stuff good like Discord Bot1
- Sec0
- Super expensive27
- Not a whole lot of flexibility9
- No usable MySQL option7
- Storage7
- Low performance on free tier5
- 24/7 support is $1,000 per month2
related Heroku posts
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
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.
Cloud Foundry
- Perfectly aligned with springboot2
- Free distributed tracing (zipkin)1
- Application health management1
- Free service discovery (Eureka)1
related Cloud Foundry posts
NGINX
- High-performance http server1.4K
- Performance894
- Easy to configure730
- Open source607
- Load balancer530
- Free289
- Scalability288
- Web server226
- Simplicity175
- Easy setup136
- Content caching30
- Web Accelerator21
- Capability15
- Fast14
- High-latency12
- Predictability12
- Reverse Proxy8
- Supports http/27
- The best of them7
- Great Community5
- Lots of Modules5
- Enterprise version5
- High perfomance proxy server4
- Embedded Lua scripting3
- Streaming media delivery3
- Streaming media3
- Reversy Proxy3
- Blash2
- GRPC-Web2
- Lightweight2
- Fast and easy to set up2
- Slim2
- saltstack2
- Virtual hosting1
- Narrow focus. Easy to configure. Fast1
- Along with Redis Cache its the Most superior1
- Ingress controller1
- Advanced features require subscription10
related NGINX posts
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.
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
Apache HTTP Server
- Web server479
- Most widely-used web server305
- Virtual hosting217
- Fast148
- Ssl support138
- Since 199644
- Asynchronous28
- Robust5
- Proven over many years4
- Mature2
- Perfomance2
- Perfect Support1
- Many available modules0
- Many available modules0
- Hard to set up4
related Apache HTTP Server posts
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.
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.