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Amazon EC2 vs HP Cloud Compute: What are the differences?
## Introduction
This comparison highlights the key differences between Amazon EC2 and HP Cloud Compute, making it easier for users to choose the right cloud computing platform.
1. **Pricing Model**: Amazon EC2 offers a pay-as-you-go pricing model, where users only pay for the compute resources they consume. On the other hand, HP Cloud Compute provides a fixed pricing model, with predefined configurations and prices for different instance types.
2. **Instance Types**: Amazon EC2 offers a wide range of instance types optimized for various workloads, including general-purpose, compute-optimized, memory-optimized, and storage-optimized instances. HP Cloud Compute, on the other hand, has a more limited selection of instance types, primarily focused on general-purpose computing.
3. **Global Footprint**: Amazon EC2 has a larger global footprint with data centers located in multiple regions around the world, making it easier for users to deploy their applications closer to their target audience for improved performance. HP Cloud Compute has a more limited geographic coverage in terms of data center locations.
4. **Service Level Agreement (SLA)**: Amazon EC2 offers a strong SLA guaranteeing a certain level of uptime and reliability for its services. In comparison, HP Cloud Compute may have a different SLA structure with varying levels of service guarantees.
5. **Ecosystem and Integration**: Amazon EC2 is well-integrated with the broader AWS ecosystem, allowing seamless connectivity with other AWS services such as S3, RDS, and Lambda. HP Cloud Compute may have fewer integration options with other cloud services and platforms.
In Summary, Amazon EC2 and HP Cloud Compute differ in pricing model, instance types, global footprint, SLA, and ecosystem integration options, providing users with distinct choices based on their specific requirements.
Albeit restricted to only a few places worlwide compared to its peers in the cloud segment, I am yet to find another provider capable of delivering a score over 5000 (Geekbench) in a benchmark on a single CPU machine, and each machine costs $6 a month. For homelab and experienced users who don't need DBaaS or IaaC's, it's a pretty straightforward choice. A more comprehensive review of Vultr's HF machines can be found here.
Our company builds micro saas applications. Based on the application we decide whether to deploy it over one of our shared servers or on a dedicated server.
We decided to Lightsail over EC2.
Lightsail is a lightweight, simplified product offering that has a dramatically simplified console. The instances run in a special VPC, but this aspect is also provisioned automatically, and invisible in the console.
Lightsail supports optionally peering this hidden VPC with your default VPC in the same AWS region, allowing Lightsail instances to access services like EC2 and RDS in the default VPC within the same AWS account.
Bandwidth is unlimited, but of course free bandwidth is not -- however, Lightsail instances do include a significant monthly bandwidth allowance before any bandwidth-related charges apply.
It has predictable pricing with no surprises at the end.
The flexibility of EC2 leads inevitably to complexity. Whereas for Lighsail there is virtually no learning curve, here. You don't even technically need to know how to use SSH with a private key -- the Lightsail console even has a built-in SSH client -- but there is no requirement that you use it. You can access these instances normally, with a standard SSH client.
DigitalOcean was where I began; its USD5/month is extremely competitive and the overall experience as highly user-friendly.
However, their offerings were lacking and integrating with other resources I had on AWS was getting more costly (due to transfer costs on AWS). Eventually I moved the entire project off DO's Droplets and onto AWS's EC2.
One may initially find the cost (w/o free tier) and interface of AWS daunting however with good planning you can achieve highly cost-efficient systems with savings plans, spot instances, etcetera.
Do not dive into AWS head-first! Seriously, don't. Stand back and read pricing documentation thoroughly. You can, not to the fault of AWS, easily go way overbudget. Your first action upon getting your AWS account should be to set up billing alarms for estimated and current bill totals.
We first selected Google Cloud Platform about five years ago, because HIPAA compliance was significantly cheaper and easier on Google compared to AWS. We have stayed with Google Cloud because it provides an excellent command line tool for managing resources, and every resource has a well-designed, well-documented API. SDKs for most of these APIs are available for many popular languages. I have never worked with a cloud platform that's so amenable to automation. Google is also ahead of its competitors in Kubernetes support.
GCE is much more user friendly than EC2, though Amazon has come a very long way since the early days (pre-2010's). This can be seen in how easy it is to edit the storage attached to an instance in GCE: it's under the instance details and is edited inline. In AWS you have to click the instance > click the storage block device (new screen) > click the edit option (new modal) > resize the volume > confirm (new model) then wait a very long time. Google's is nearly instant.
- In both cases, the instance much be shut down.
There also the preference between "user burden-of-security" and automatic security: AWS goes for the former, GCE the latter.
Most bioinformatics shops nowadays are hosting on AWS or Azure, since they have HIPAA tiers and offer enterprise SLA contracts. Meanwhile Heroku hasn't historically supported HIPAA. Rackspace and Google Cloud would be other hosting providers we would consider, but we just don't get requests for them. So, we mostly focus on AWS and Azure support.
Pros of Amazon EC2
- Quick and reliable cloud servers647
- Scalability515
- Easy management393
- Low cost277
- Auto-scaling271
- Market leader89
- Backed by amazon80
- Reliable79
- Free tier67
- Easy management, scalability58
- Flexible13
- Easy to Start10
- Widely used9
- Web-scale9
- Elastic9
- Node.js API7
- Industry Standard5
- Lots of configuration options4
- GPU instances2
- Simpler to understand and learn1
- Extremely simple to use1
- Amazing for individuals1
- All the Open Source CLI tools you could want.1
Pros of HP Cloud Compute
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Cons of Amazon EC2
- Ui could use a lot of work13
- High learning curve when compared to PaaS6
- Extremely poor CPU performance3