Most likely you have heard about Spectre and Meltdown by now. It’s all over the news. As an IT or DevOps engineer, it’s now your job to patch your EC2 instance operating systems.
This task can be “fun” if you need to SSH/RDP into every EC2 instance and apply patches. Or, it can be truly fun if you decide to use AWS Systems Manager to apply patches to your OS.
Modern cloud-based data services have revolutionized the way companies manage their data. Tools such as Amazon Athena and Amazon Redshift have changed data warehouse technology, catering for a move towards interactive, real-time, analytical solutions.
Both Amazon Athena and Redshift offer their own unique benefits and use cases. Athena provides a cheaper and more portable way to query data while Redshift offers unrivalled performance and scalability.
The following article provides a brief comparison of the Amazon Athena and Redshift data services. By understanding the main uses of each and comparing them under key headings, you can come to a more informed decision in choosing the right tools for your company’s data needs.
Amazon EBS snapshots are an AWS-native backup mechanism for your EBS volumes.
If you are coming from a traditional backup history, they can be considered a mix of full and incremental backups:
However, unlike traditional backups, if you delete the first EBS snapshot (the “full one”), the rest of the EBS snapshots are still fully recoverable. It is 100% safe to delete any EBS snapshot; all remaining EBS snapshots are fully recoverable.
EBS snapshots are an important tool in any disaster recovery strategy. For many, creating daily EBS snapshots, automatically, is an important event.
Since EBS snapshots are incremental, pre-calculating the cost of EBS snapshots is difficult. The reason is that there are many factors that can affect the actual cost of an EBS snapshot:
We have created an EBS Snapshot Pricing Calculator to help estimate the cost of creating daily EBS snapshots.
We’re happy to announce that we’ve added support for scheduling of creating and deleting DynamoDB backups. Today, we are adding two new actions:
During development, we came across some caveats about the new DynamoDB backup feature that we’d like to share. Here are our observations.
This week is AWS re:Invent 2017. For the 6th time, it’s bigger than ever, spanning 5 hotels: The Venetian, The Mirage, Encore, Aria, and MGM Grand. So plan your transitions well, make sure you have some good walking shoes, and take the AWS shuttles between hotels.
Like previous years, you’ll notice different coloured lanyards holding everyone’s badges. Here’s an updated list.
Amazon DynamoDB is a flexible NoSQL database solution. It provides a serverless database for non-relational data.
Unlike Amazon RDS, there is no built-in way to backup or export the data stored in a DynamoDB table. There are many reasons you may want to export your DynamoDB table items to S3:
Amazon has provided a solution using AWS Data Pipeline to export DynamoDB items to S3, but that requires using additional AWS services and cannot be applied to multiple tables across multiple regions easily.
Today, we’re happy to announce the addition of a new action to Skeddly: Export DynamoDB Tables.
Last November, AWS announced the ability to subscribe to SaaS products through the AWS Marketplace. Prior to that, all SaaS listings were simple redirects to the vendor’s website.
With that announcement, users are able to subscribe to SaaS products directly from the Marketplace. In addition, billing for the service is integrated with your AWS bill.
Today we are very happy to announce that Skeddly subscriptions are now available through the AWS Marketplace.
For the first 12 months of all new AWS accounts, Amazon EC2 includes 750 hours of running Linux EC2 instances and 750 hours of running Windows EC2 instances, as long as the EC2 instance type is
Doing the math, 750 hours is just enough time to run a single EC2 instance for an entire 31-day month.
During the early days of a startup, much of your AWS usage is going to be used for development. Many development resources don’t need to be running 24/7 like production resources do. The end result is that you’re wasting your precious EC2 free tier on unused resources.
By scheduling your EC2 instances to stop, you can expand your EC2 free tier from 1 EC2 instance up to 3 EC2 instances.
To help reduce your RDS costs, Amazon RDS allows you to stop and start your RDS instances. This is a very helpful cost-reduction technique that can be used in development, staging, or other environments where RDS instances do not need to be available 24/7.
Skeddly includes actions such as “Start RDS Instances” and “Stop RDS Instances” to help you automate this cost saving technique.
However, Aurora RDS clusters and instances cannot be stopped. They can only be terminated and recreated.
We have added a new action to Skeddly to help you lower your Aurora RDS costs by deleting and recreating your Aurora clusters. Our new action is called “Restore RDS Cluster”.