Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
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Rackspace Managed Hosting
Score 8.8 out of 10
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Rackspace Managed Hosting is cloud computing company Rackspace's managed IT services and IaaS offering. Its infrastructure options include bare metal servers, virtual single-shared servers, and cloud multi-tenant environments.
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
Rackspace is very well suited as a IaaS (Infrastructure as a Service) provider, particularly when you're planning on leaving the infrastructure up for a period of time. They seem to focus a bit more on that aspect of infrastructure. That is to say, they seem to promote running servers for longer periods of time and not spinning up/shutting down servers frequently based on usage spikes. While, they do support that sort of availability -- they don't have features built into their offering, necessarily, that make it a lot easier to implement. Our experiences with Rackspace have been 100% around their cloud platform, but they have another entire part of their business that is centered around hosting/maintaining/supporting physical hardware (bare metal). They have had a great reputation over the last several years (10+) for being top-notch providers in this space, which is one reason we even considered them for our Cloud-based hosting needs. We don't have any direct experience with their "bare metal" offerings, but their reputation is certainly great, and worth noting.
Fanatical Support - I can't stress how great their team is. Not only are they knowledgeable, whenever I call in (during the day or in the middle of the night), I never have to wait more than a minute to speak to someone.
Webmail, Hosted Exchange, and Office365 Support - As an IT team of one, Rackspace's cloud solution and migration team has really helped me over the years to minimize issues for users, but also provide a reliable and flexible email platform.
Latest outage 12/2/22 and counting over 75 hours - in my opinion, support has been miserable. In my experience, there's little/no communication regarding the problem or cause. No support. In my opinion, erroneous advice. Virtually NOTHING for users. I feel we've been abandoned.
Outage appears to have been caused by unpatched servers & no backup servers
In my opinion, NO COMPANY should trust their data or services to a nonresponsive company like Rackspace.
In my experience, there are NO published policies/practices re: server maintenance (patching) to mitigate hacking, NO published policies/practices re: backup servers in the event of problems. I feel it's stupid of me as a user to have chosen to trust them with critical services
If I wake tomorrow completely incapable of managing a client cloud operation, our dedicated Rackspace Cloud Engineering Team is deployable as literal extension of our business, immediately addressing all needs and requirements without cause of business disruption for our consultancy, and more importantly for the mission-critical ones of our clients. For this reason alone, Rackspace is our choice of choices!
If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used
The company does not put as much focus on usability as other cloud competitors and it is kind of clear. It would be good to take a quarter and gather intense feedback, and then another quarter and focus purely on UI enhancements and backend interoperability
1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
LiquidWeb or Amazon both offer some products that could be considered similar. I will say though, after years of dealing with Rackspace, their service is what always has me coming back. Their support is typically so much better than other vendors that I hesitate to use other vendors. Pricing might be cheaper, but when you have an issue and need it resolved ASAP, then Rackspace has come through in the majority of cases for me.
