It’s that time of year again where we’re recovering from eating and drinking too much, and looking forward to the new year filled with exciting opportunities and a chance to do better. Who knew that an arbitrary point in the Earth’s orbit round the Sun had such power? I’ve definitely neglected the blog this past year or so (I’ve been a little more active on my dev blog, but only just) and I’m contemplating just migrating all the content from this site over to picnicerror.net and focusing my efforts on one site. Anyway, I digress. I think my last post on this site was looking back (very belatedly) at my favourite games from 2017, so it seems kind of fitting that my next post is this one.

One of the major pain points for me with Amazon Redshift has always been the coupling between storage and compute. Competitors like Snowflake and Google’s BigQuery offer independent compute and storage, which means easier (and quicker) scaling in times of increased load. Redshift’s main drawback in the scalability sense has been that it can take up to 24 hours to resize your cluster (during which it’s in read-only mode), meaning there’s a lot of pressure to get your cluster configuration spot on before you go into production. Redshift’s provision of elasticity is just not up to par with most of Amazon’s other services. While Redshift Spectrum helps with this, it’s not a solution to the issue of scalability for an existing cluster.

In the lead up to re:Invent, Amazon last night dropped a load of really neat announcements (server-side encryption for DynamoDB as standard, SSE support for SNS), among which was the reveal of Elastic resize for Redshift. As an aside, if this is the stuff they’re announcing now, there should be some really nice announcements at re:Invent.

What seems like an age ago, I spotted a setting on one of our Redshift clusters that suggested Enhanced VPC routing support for Redshift Spectrum might be on the way. After waiting a while, and waiting some more, and then waiting some more, it seems that Amazon have finally released this into the wild, and Redshift Spectrum now works with clusters that have Enhanced VPC routing available!

As of Build 1.0.4349 or Build 1.0.4515, this functionality will be available in Redshift. It hasn’t made it into the official announcements yet, but it has popped up on the Redshift forums here: https://forums.aws.amazon.com/ann.jspa?annID=6197

One of the things that I really like about Google BigQuery is the ability to write queries right there in the web browser without having to install a hefty IDE. Sure, there are times when having the full power of something like JetBrains DataGrip comes in handy (source control integration, customisation, formatting), but sometimes you just want to dive in and write a quick query without any messing around. Amazon did this for Athena, which was really handy, but strangely never did so for Redshift…until now!

I did it last year, so it’s time to do it again. Actually, it was time to do it again about six months ago but life got in the way. Here are my top games from 2017. Caveat: This list is only from games I’ve played myself in my limited available time. There are plenty of other great games that I just haven’t got round to yet.

While quietly perusing Twitter this evening, I happened to notice one from the official AWS account with a link to a blog post from Amazon tech hero Randall Hunt describing the newly available capability for AWS Lambda: SQS as an event source!

AWS Lambda functions are getting a lot of press right now, with “serverless” being the topic de jour. We’ve been using it extensively and it’s incredibly flexible and useful, although not suitable for every situation. It really does remove a lot of obstacles for the average developer. In saying that, there are a few tips that I’d like to share based on our experiences with Lambda. Many of these may be no-brainers, but it’s always worth sharing these things as you never know when they’ll be useful.

Serverless computing and event-driven functions are what it’s all about at the moment. But what happens when the event trigger fires, and your process then encounters an error? How do you recover from this given the event has since passed and may never happen again? This is a common question in AWS when working with their serverless, event-driven Lambda Functions.

Fortunately, AWS lets you define Dead Letter Queues for this very scenario. This option allows you to designate either an SQS queue or SNS topic as a DLQ, meaning that when your Lambda function fails it will push the incoming event message (and some additional context) onto the specified resource. If it’s SNS you can send out alerts or trigger other services (maybe even a retry of the same function - although watch out for infinite loops), or any combination of the above, given its fanout nature. If it’s SQS you can persist the message and process it with another service.

So let’s look at both options in a little more detail.