Limiting Cross-stack References in CDK
Several years ago I wrote CloudFormation Tips and Tricks, in which I gave the advice to “use outputs lavishly, exports sparingly.” The reason is that when you export a value…
Several years ago I wrote CloudFormation Tips and Tricks, in which I gave the advice to “use outputs lavishly, exports sparingly.” The reason is that when you export a value…
Serverless Stack (serverless-stack.com) is another rapid serverless application development platform for AWS. SST (as it is also known) promises to streamline development and allow local debug of AWS Lambdas. It…
Two months ago I didn’t give much thought to controlling a program’s access to the Internet. Then Log4Shell happened. This post looks at three ways that you can control what an in-VPC application is allowed to talk to.
Building a holiday light display for his own home spurred Al Iacovella’s interest in microcontrollers, data, and the internet of things.
It’s been a week since CVE-2021-44228, a remote code execution vulnerability in Log4J 2.x, hit the world. Hopefully by now everybody reading this has updated their Java deployments with the latest Log4J libraries. But no doubt there’s another vulnerability, in some popular framework or library, just waiting to make its presence known. This post is about Cloud features that act to minimize the blast radius of such vulnerabilities.
Amazon Redshift’s launch in 2012 was one of the “wow!” moments in my experience with AWS. Here was a massively parallel database system that could be rented for 25 cents per node-hour. Here we are in 2021, and AWS has just announced Redshift Serverless, in which you pay for the compute and storage that you use, rather than a fixed monthly cost for a fixed number of nodes with a fixed amount of storage. And for a lot of use cases, I think that’s a great idea. So I spent some time kicking the tires, and this is what I learned.
Amazon Athena is a service that lets you run SQL queries against structured data files stored in S3. It takes a “divide and conquer” approach, spinning up parallel query execution engines that each examine only a portion of your data. The performance of these queries, however, depends on how you consolidate and partition your data. In this post I compare query times for a moderately large dataset, looking for the “sweet spot” between number of files and individual file size.
Clickstream data – the behavior data collected from a user’s path through a website or app – is often used for business intelligence reports. It helps many companies answer questions…
In this 45 minute talk, Ken Rimple gives a quick overview of AWS CodeBuild, then dives into a few of the challenges he’s faced, from dealing with build errors properly, configuring CodeBuild to run inside of AWS, testing locally so you don’t go crazy waiting for 15 minutes each time you deploy a new build, how to properly access your build artifacts and reports, running tools like Cypress, to building and deploying Docker containers to ECS, and more.
Amazon Web Services (AWS) is a collection of nearly 200 services. They can be intimidating to the newcomer, and offer many opportunities for mistakes: some expensive, some just inconvenient. In this Lunch and Learn, our panel of AWS experts look at some of the mistakes they made, and how these could have been avoided.
Amazon uses a “pay as you go” pricing model: you pay for the resources that you use, and in most cases don’t need to pre-allocate resources. While this allows your business to scale, it means that each component of your data pipeline will incur a separate charge, which can obscure the overall cost of running the pipeline. This talk will examine those changes, along with strategies for partitioning those costs between your clients or organizational units.
Abstract So I have this production AngularJS on Java/Spring REST app. It’s getting a bit long in the tooth. I mean, how many Internet Dog Years ago was that? It…
Abstract AWS has made our life easier. And it has made scaling easier – but too often, when you go to scale, it’s a matter of reaching for the credit…
Abstract In 2009, Amazon Web Services was simple: EC2 for compute, S3 for storage. In 2019, it’s far more complex: well over 100 services, covering the entire software life-cycle. This…
Alexa’s so smart, she learns more every day. (That’s what Amazon tells me, anyway.) So I’m going to pick her brain a little, and see if she can tell me…
Alexa’s so smart, she learns more every day. (That’s what Amazon tells me, anyway.) So I’m going to pick her brain a little, and see if she can tell me…
One of the guiding principles of the Convox project is that you should always consume a service rather than running custom software. This talk will focus on how we use…
Apps no longer just run on smartphones and tablets – they process verbal commands we speak to devices like Amazon Echo, run as bots in Slack channels, and are rapidly evolving customer experiences that span a range of IoT devices in homes, cars, offices, and industrial settings. Crucial to the success of all these ecosystems is one central idea: Code has to not just run in the cloud, it has to be easy to get it there and scale it there. Serverless computing – calling AWS Lambda functions instead of managing heavyweight applications on infrastructure – is changing how developers think about backends, event-driving processing, and application design. Infrastructure, deployment, and software platform setup that used to take days or weeks of time vanishes, replaced by microservices that do one thing well, require zero effort to deploy, and scale automatically and implicitly just by using them. At the same time, AWS Lambda and other serverless systems have redefined cloud economics by eliminating the possibility of cold servers, creating a radical new price point for applications running in the cloud and freeing developers and COO’s alike from worrying about paying for unused capacity. In this talk we’ll define Serverless computing, examine the key trends and innovative ideas behind the technology, and look in detail at design patterns for big data, event processing, mobile backends, and more using AWS Lambda.
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