Alternatives to Vultr

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!

Hi, I'm a beginner at using MySQL, I currently deployed my crud app on Heroku using the ClearDB add-on. I didn't see that coming, but the increased value of the primary key instead of being 1 is set to 10, and I cannot find a way to change it. Now I`m considering switching and deploying the full app and MySql to DigitalOcean any advice on that? Will I get the same issue? Thanks in advance!

What is the data transfer out cost (Bandwidth cost) on Linode compared to Microsoft Azure?

We use Hetzner Online AG since the inception of our business, because of the great prices, marvelous support and great interface (especially the new cloud interface). Other options that we tested are DigitalOcean (was more expensive than the new hetzner cloud and didn't offer "huge" dedicated servers), @Vultr (about the same issue as with DigitalOcean , although the prices were better), OVH (Prices, old interface, no "tiny" packages and [at least back at the day] only monthly payment) and Living Bots (Only dedicated servers, too expensive for our needs).

Hetzner offered the best spectrum of servers and has great prices and REALLY great prices in the server auctions.

We use Hetzner Online AG since the inception of our business, because of the great prices, marvelous support and great interface (especially the new cloud interface). Other options that we tested are DigitalOcean (was more expensive than the new hetzner cloud and didn't offer "huge" dedicated servers), @Vultr (about the same issue as with DigitalOcean , although the prices were better), OVH (Prices, old interface, no "tiny" packages and [at least back at the day] only monthly payment) and Living Bots (Only dedicated servers, too expensive for our needs).

Hetzner offered the best spectrum of servers and has great prices and REALLY great prices in the server auctions.

Hosting updown.io started with a single OVH server and quickly grew to more server, first it was DigitalOcean VMs and we were very satisfied about them. But we then noticed some shortcomings about #IPv6 networking, although DigitalOcean supports it they don't provide the standard IP range to each VM (by choice) and thus have to block port 25 to avoid other machines being blocked in case of spammer. This is not good for us it means we can't monitor IPv6 SMTP servers properly, that's why we switched to @Vultr (one of their main competitors) which provides similar prices, more locations, and true IPv6 support with no blocked ports. Of course they offer less tools and the support is probably better at DigitalOcean but so far we're happy with @Vultr.

We still use some @OVH servers (which offers tremendous price/performance ratio) for the main web and database server + 2 of the daemons. In addition to this, we also have 2 DigitalOcean VMs for the secondary web and database server and for the automatic TLS termination proxy used to automatically issue Let's Encrypt certs for status page custom domains (for these servers the IPv6 port block is not an issue)

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

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.