We enjoyed hosting the first Cambridge AWS User Group Meetup of the year in February (but were so busy we forgot to blog about it), so we’re excited to welcome everyone back to our town hall for the 3rd meet up of the year. The details of the next meetup are still being decided but there are always great opportunities to learn about AWS and contribute your own knowledge back to the group. Come along we’ll have snacks, soft and hard drinks, and most importantly questions asked and knowledge shared! While the details are getting settled here’s a little write up, finally, of February’s meet up.
Breaking the February Silence
Last year at the first of the main meetups, Tom Clark from Ocean Array Systems presented their idea for a data processing solution (the ‘Zero to Hero’ section of the meetup). They were looking to get some advice on how best to leverage AWS’ services given they had ‘zero’ current knowledge. Now seven months later he was back to present on their progress. The solution was very similar to what was sketched out back in July. He didn’t have any slides and rather than moving rooms to one with a white board he just sketched things out on the glass and a big sheet of paper 🙂
Tom had five points he’d taken away from the last seven months of development although I’ve merged two and added one from the list I originally captured when listening to him:
- It’s worth thinking about costs, particularly considering the prototyping to beta/first few clients stage. The different systems scale differently in price. For example, they ended up making heavy use of lambda whereas with hindsight t2.nano and t2.micro instances are very cheap, can handle reasonable scale for tasks suitable for lambda functions and have a large number of free hours associated with them. In the end lambda may scale to infinity more cheaply when you bring in the cost of engineers to maintain large numbers of EC2 nodes but in the early days it might be cheaper (your time included) to manage your own EC2 instance;
- Your choice of database is a sensitive aspect for you commercial model. They went with the room’s advice and used DynamoDB but a knowledgeable source highlighted that quickly gets expensive. They’d have saved some money scaling with a cheaper solution;
- What is the commercial value of your data? For them it was important to get a sane API in front of the data as soon as possible. One of their datasets is collected from 3rd parties and they realised 1) it’s tedious, and 2) no one else has done this. By providing a decent API to this data (which they need internally anyway) they have the opportunity to resell access (sounds like how AWS got started);
- Figure out how to create isolated software projects! This is learning from immutable infrastructure and fairly common advice these days which means there’s no harm in repeating it 😉 Clojure does this well with leiningen, and I’ve had limited but positive experience with Python’s virtualenv and limited painful experience the RVM;
- You need a dedicated person to pull together the AWS services. I believe their system has been developed by three people, two experts in Matlab and machine learning, and the other who could focus on AWS. This could be a good intern or junior as generally the learning curve for AWS services isn’t that steep.
The second talk was given by Jon Green who went through the AWS Re:Invert 2015 talk on the IOT service. I’m barely a beginner in the IOT field, but the solution does seem complete, and it looks like AWS have solved a lot of problems. How many of these were already solved I couldn’t say. Given the breadth of the solution it’s not easy to summarise but there are two interesting points that have stuck in my mind: –
Firstly; it’s currently hard for enthusiasts to have a play, even more so in the UK than in the US. Given the power of AWS’ free tier to have developers create toy projects for little cost and then take those solutions over to their companies where they start bringing in revenue this seems a missed opportunity. Having said that I’ve had a quick browse at https://aws.amazon.com/iot/getting-started/ and at least one of the partner hardware kits is available if you switch the link from amazon.com to amazon.co.uk. Stock availability was something Jon highlighted, so get it while stocks last 😉
The second point is a bit more abstract. IOT provides tools to provide secure identification, registration and state management of your devices. This is the most hardware centric part of the system, the rest is about event processing and a lot of that looks like a streaming service. Jon made a very thought provoking point that even the most hardware related parts need not necessarily refer to a physical device and your whole IOT solution could be virtual. The IOT system has a lot of components just waiting for someone with some knowledge and imagination 🙂
Hope to see you all on Thursday 9th June! The talk line up is still being finalised but we do know that Matt McDonnell from the Metail Data Science team will be starting things off with a presentation on ‘Deploying Data Science with Docker and AWS’.