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Looking at open source PaaS technologies

Posted by: , Posted on: - Categories: GaaP, Open Source

I’ve been working on a prototype of what a Platform as a Service (PaaS) for government might look like, as we wrote about in a previous post. One of the first things we did was look at the open source PaaS options that were available. This post is about how we did that and what we learned.

Comparison table of PaaS

The open source options we considered

We looked at a range of proprietary and open source options. In this post, I am focusing on open source. This is because much of the information we learned about the proprietary options was shared in commercial confidence. I’ll talk more about the proprietary options we considered and how we compared them in a later post.

Exploring the options

PaaS is a very fast-moving field at the moment and there are a lot of options. The first thing we did was take some time individually within the team to identify which options were worth investigating. We based that on previous experience, things we’d read about, and further research online. We were around eight people on the team, so we had a lot to draw on.

It’s not always the case that you are comparing like-for-like with PaaS technologies. For example, Cloud Foundry is a fully-featured PaaS, whereas Mesos is a cluster-management system. While Mesos on its own has a number of PaaS features, it didn’t meet a combination of the criteria "developer self-service" and "multi-tenancy" (e.g. no authentication, access control).

I wanted to investigate Mesos as it’s an interesting technology, so we looked at ways to combine it with other technologies who offer those features. We chose combinations of technologies based on what we found to be common combinations. In this example, you can see we looked at both Mesos + Aurora, and Mesos + Marathon + Chronos (Mesosphere).

At this stage, we ruled out things that we didn’t think were worth investigating further (for example, they were nowhere near production-ready) and worked out some combinations that made sense to look more into.

The longlist of technologies we investigated is:

Our selection criteria

In our previous post I outlined the four main criteria we’d identified from our user research: a PaaS would have to be multi-tenant, self-service, allow application developer support and be able to run on multiple public clouds. This had already allowed us to rule out some technologies (for example, a number of PaaS technologies only run on AWS). We also had some further must-have criteria. The complete list of our selection criteria is below:

Must haves

  • Multi-vendor capabilities
  • Developer self-service model
  • Support for scaling application instances with ease (elastic scaling, manual, self serve)
  • Support for Linux
  • Ability to choose application language
  • Ability to recover from failure of all hosts
  • Ability to maximise the application availability during underlying host failure
  • Zero downtime deploys
  • Some multi-tenancy capabilities
  • Access to raw stdout / stderr logs

Investigation points

  • What is involved in deploying applications to this PaaS?
  • How easy is the maintenance/operation for the team maintaining the platform?
  • Is there a hosted option available?
  • Could the unit of deployment be used without the PaaS?
  • How well documented is the PaaS? Do they keep their documentation up to date?
  • What type of multi-tenancy support is offered?
  • Is there commercial support/consulting available?
  • What different levels of access permissions does the PaaS support?
  • Is it open source?
  • Does the PaaS provide any database service?
  • What is the language/tech?
  • What APIs are available to enable application developers to manage their own applications?
  • Is this technology production-ready now?
  • Is there a cost associated with this and what is it?
  • How do we get data on which application is using which resources?
  • Is it possible to back up data from the PaaS itself?

Brett Ansley, our business analyst, wrote these up very clearly and with acceptance criteria to clarify what we were looking for. For example, for zero downtime deploys:

Given: an application that is receiving requests
When: a new version of the application is deployed
Then: there is no downtime of the application.

Comparing against our selection criteria

We then split into pairs and each pair took a technology in turn to evaluate it. Dan Carley, our tech lead, outlined some consistent steps to take in each investigation so that we could be sure each pair was investigating in the same way. For example, to investigate high availability:

  • High availability (if self-hosted)
  • Kill one of the hosts (if self-hosted)
  • Repeat HTTPS requests to application endpoints
  • Confirm that we have the same number of workers
  • Restore host

Each pair spun up the technology they were using and investigated it. As they found the answer to each of the selection criteria, they marked it on the whiteboard (main photograph) so we (and any passers-by) could clearly see how we were progressing and which technologies had what. If any technology failed a must-have, the investigation would stop; otherwise it was time-boxed to two days.


The overview of what we learned about each can be seen from the photograph of the whiteboard above, and is summarised in this spreadsheet. It’s worth noting that the spreadsheet is slightly more up-to-date than the photograph of the board; for example Rancher and Tsuru were late entries, and some answers were updated with more information that we learned later.

One thing that I found particularly interesting was that multi-tenancy is not a feature of many of these technologies. For example, Kubernetes and Mesos, two widely used and interesting technologies, do not support multi-tenancy. There’s no way to ensure that a team of developers can administer only their application and not the applications of another team. This meant that they were not suitable for our purposes.

The tech that meets our needs

After going through this process of looking at and comparing a number of open source PaaS solutions, the clear front-runners were Deis, Tsuru, and Cloud Foundry. The next stage was to investigate these three technologies more and choose one to build a prototype. This has helped us with user research, which we'll share more on later. In the meantime, we hope sharing what we’ve learnt about these technologies is useful to you, and do let us know your thoughts in the comments below.

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  1. Comment by Wojciech Sielski posted on

    I would re-consider mesos & marathon.
    In eBay eCG we actually use the similar stack, combined with consul.
    Below you have projects that have already integrated all pieces together:

    As router/LB you can choose better stuff that read from consul directly:

    Alternate PaaS project with mention:

    • Replies to Wojciech Sielski>

      Comment by Wojciech Sielski posted on

      *worth mentioning

    • Replies to Wojciech Sielski>

      Comment by Anna Shipman posted on

      Thanks! That’s good to know. We did this evaluation a while ago and many of the technologies have moved on a lot since then. This is useful information about Mesos and Marathon and thanks for sharing your code!

  2. Comment by Des posted on

    A really great post - thanks 🙂

    Was there any reason why WSO2 was not included in the target list for investigation / evaluation?

    • Replies to Des>

      Comment by Anna Shipman posted on

      Hi, thanks! Glad you enjoyed the post.

      We did look at Stratos very early on, but it didn't make our longlist – it didn't seem that it would meet our selection criteria. In the very early stages of the investigation it was quite light-touch so I'm afraid we didn't document the exact reasons it didn't make the list. Is it something you've found useful?

  3. Comment by KubeFan posted on

    Interesting that Deis just re-platformed to kubernetes Worth giving the kubernetes based candidates a better look?

    • Replies to KubeFan>

      Comment by Anna Shipman posted on

      We spoke to Deis a little while ago and they mentioned they were planning this. It's good to see. Kubernetes has moved on a huge amount since we did our evaluation, and definitely is worth another look. Thanks!

  4. Comment by Carl posted on

    Just found this post and I have to say, Awesome work, kudos.

    There have been a lot of improvements to Cloud Foundry 1.6, it has some significant improvements, like the ability to run docker containers, .net as well as binary buildpacks.

    Check it all out here:

  5. Comment by Amit posted on

    Thanks for sharing this research! Couple questions. How did you determine production readiness? How did you determine whether data backup was possible? Couple suggestions. Cloud Foundry itself is mostly Go, with just one Ruby component and one Java component. The "Any associated cost?" column could be renamed so that the positive answer is "Yes", so that I can turn conditional highlighting on my Spreadsheet (No = Red) and quickly see the negative points of all the options. Maybe something like "Free of additional costs".

    • Replies to Amit>

      Comment by Anna Shipman posted on

      Hi Amit, thanks for your comment.

      We used various factors to determine production readiness; the main factors were our own experience in how production-ready technology works, coupled with the technology's own claims (e.g. whether it was at 1.0 at the point we were investigating it). For data backup, as I mentioned, each pair built a simple prototype using the technology and investigated it, so determining whether data backup was possible in each case would have been based on a combination of the documentation and testing it.

      You might be interested to know that we've now selected Cloud Foundry for our Beta; you can read about that in my latest blog post: