AWS credits are a way to save on your Amazon Web Services (AWS) bill. Credits are applied to AWS cloud bills to help cover costs that are associated with eligible services, and are applied until they are exhausted or they expire. Essentially, credits are a coupon-code like mechanism used by Amazon on your bill. If you want to see how to redeem your AWS promotional credits, look here. So how do you get these credits? There are a number of ways – here are 9 that we have either used ourselves or that have been successfully used by our customers.
With AWS Activate, companies can build or scale with up to $100,000 in AWS promotional credits. AWS Activate is ideal for startups because they get access to resources as quickly as possible, and AWS provides them with a low cost, easy-to-use infrastructure to help them grow.
This is a big help for startups, knowing they are getting their money’s worth with these credits lets them focus on one thing – growth. If you are looking to get started on AWS definitely check this out.
Publish an Alexa Skill
For all you developers, each Alexa skill that you publish, you can apply to receive a $100 AWS promotional credit. Take advantage of these credits to get all your skills potential!
AWS Cloud Credits for Research
AWS Cloud Credits for Research evaluates academic research from researchers at accredited institutions around the world. Researchers that apply for this program take an initiative to build a cloud-hosted service, software, or tools and/or want to migrate a research process or open data to the cloud. The credit amount awarded will vary depending on the cost model and usage requirements documented in the research proposal.
Attending AWS webinars, events, and conferences can get you AWS credits. In order to be awarded the credits, you’ll have to provide proof that you actually attended. Make sure to keep an eye on their events page, as new stuff is being added all the time.
In an effort to educate the next generation of cloud professionals, AWS has made AWS Educate available to institutions, educators, and students. It provides institutions with the resources educators and students need for training resources, cloud-related learning, and content for courses. Students have the opportunity to receive credits by getting hands-on experience with AWS tech, training, content and career pathways.
At member institutions, educators earn $200 in AWS credits compared to non-member institutions they earn $75. Students receive an AWS Educate starter account along with $50 in credits at a member institution and $35 at a non-member institution. To make this even more appealing, AWS will award students and staff with more credits if you sign up as a member institution.
AWS Credit Program for Nonprofits
Through TechSoup Global, eligible nonprofit organizations can request one grant of $2,000 AWS credits once per fiscal year.
AWS Free Tier
As always, AWS Free Tier is a great option to get access to AWS products for no cost. Customers can use the product for free up to specified limits for one year from the date the account was created.
This includes 750 hours of Amazon EC2 Linux t2.micro instance usage, 5 GB of Amazon S3 standard storage, 750 hours of Amazon RDS Single-AZ db.t2.micro Instances, one million AWS Lambda requests and you can build and host most Alexa skills for free.
AWS focuses on education technology startups long term success with their AWS EdStart program. AWS is looking to provide businesses with the resources they need to get started as quickly and easily on AWS to ensure they have every opportunity to prosper. After applying and getting approved, businesses will receive their credit validation. The credit amount awarded is based on the business’s needs.
You only have access to promotional credits for a limited time, so make sure you take advantage of all these opportunities if you can! Whether you are just getting started with AWS or have been using it for a while, there are plenty of credits and resources available to make AWS an affordable option for you.
On our first day as Turbonomic employees, our team had some great discussions with CTO Charles Crouchman about Turbonomic, ParkMyCloud, and the market for infrastructure automation tools. Charles explained his vision of the future of infrastructure automation, which parallels the automation trajectory that cars and other vehicles have been following for decades. It’s a comparison that’s useful in order to understand the goals of fully-automated cloud infrastructure – and the mindset of cloud users adopting this paradigm. (And of course, given our name, we’re all in on driving analogies!)
The Five Levels of Vehicle Autonomy
The idea of the five levels of vehicle autonomy – or six, if you include level 0 – is an idea that comes from the Society of Automotive Engineers.
The levels are as follows:
Level 0 – No Automation. The driver performs all driving tasks with no tools or assistance.
Level 1 – Driver Assistance.The vehicle is controlled by the driver, but the vehicle may have driver-assist features such as cruise control or an automated emergency brake.
Level 2 – Partial Automation or Occasional Self-Driving. The driver must remain in control and engaged in driving and monitoring, but the vehicle has combined automated functions such as acceleration and steering/lane position.
Level 3 – Conditional Automation or Limited Self-Driving. The driver is a necessity, but not required to monitor the environment. The vehicle monitors the road and traffic, and informs the driver when he or she must take control.
Level 4 – High Automation or Full Self-Driving Under Certain Conditions. The vehicle is capable of driving under certain conditions, such as urban ride-sharing, and the driver may have the option to control the vehicle. This is where airplanes are today – for the most part, they can fly themselves, but there’s always a human pilot present.
Level 5 – Full Automation or Full Self-Driving Under All Conditions. The vehicle can drive without a human driver or occupants under all conditions. This is an ideal, but right now, neither the technology nor the people are ready for this level of automation.
How These Levels Apply to Infrastructure Automation Tools
Now let’s take a look at how these levels apply to infrastructure automation tools and infrastructure:
Level 0 – No Automation. No tools in place.
Level 1 – Driver Assistance.Some level of script-based automation with limited applications, such as scripting the installation of an application so it’s just one user command, instead of hand-installing it.
Level 2 – Partial Automation or Occasional Self-Driving. In cloud infrastructure, this translates to having a monitoring system in place that can alert you to potential issues, but cannot take action to resolve those issues.
Level 3 – Conditional Automation or Limited Self-Driving. Think of this as traditional incident resolution or traditional orchestration. You can build specific automations to handle specific use cases, such as opening a ticket in a service desk, but you have to know what the event trigger is in order to automate a response.
Level 4 – High Automation or Full Self-Driving Under Certain Conditions.This is the step where analytics are integrated. A level-4 automated infrastructure system uses analytics to decide what to do. A human can monitor this, but is not needed to take action.
Level 5 – Full Automation or Full Self-Driving Under All Conditions. Full automation. Like in the case of vehicles, both the technology and the people are a long way from this nirvana.
So where are most cloud users in the process right now? There are cloud users and organizations all over this spectrum, which makes sense when you think about vehicle automation: there are early adopters who are perfectly willing to buy a Tesla, turn on auto-pilot, and let the car drive them to their destination. But, there are also plenty of laggards who are not ready to take their hands off the wheel, or even turn on cruise control.
Most public cloud users have at least elements of levels 1 and 2 via scripts and monitoring solutions. Many are at level 3, and with the most advanced platforms, organizations reach level 4. However, there is a barrier between levels 4 and 5: you will need an integrated hardware/software solution. The companies that are closest to full automation are the hyperscale cloud companies like Netflix, Facebook, and Google who have basically built their own proprietary stack including the hardware. This is where Kubernetes comes from and things like Netflix Scryer.
In our conversation, Charles said: “The thing getting in the way is heterogeneity, which is to say, most customers buy their hardware from one vendor, application software from another company, storage from another, cloud capacity from another, layer third-party software applications in there, use different development tools –– and none of these things were effectively built to be automated. So right now, automation needs to happen from outside the system, with adaptors into the systems. To get to level 5, the automation needs to be baked in from the system software through the application all the way up the stack.”
What Defines Early Adopters of Infrastructure Automation Tools
While there’s a wide scale of adoption in the market right now, there are a few indicators that can predict whether an organization or an individual will be open to infrastructure automation tools.
The first is a DevOps approach. If an organization using DevOps, they have already agreed to let software automate deployments, which means they’re accepting of automation in general – and likely to be open to more.
Another is whether resource management is centralized within the organization or not. If it is centralized, the team or department doing the management tends to be more open to automation and software solutions. If ownership is distributed throughout the organization, it’s naturally more difficult to make unified change.
Ultimately, the goal we should all be striving for is to use infrastructure automation tools to step up the levels of automated resource configuration and cost control. Through automation, we can reduce management time and room for human error to achieve optimized environments.
It’s that time of year again at ParkMyCloud’s cloud optimization headquarters. Summer is in full swing, the 4th of July is on Thursday, and the USWNT is in World Cup semi-finals – let’s GO USA. And, of course, ParkMyCloud is four years old.
Anniversaries in Review
We always like to take a moment of reflection on these anniversaries –– here are our previous ones, if you’re curious:
This past year has been a big one for ParkMyCloud. As you may be aware we were acquired in May by Turbonomic, the leader in application resource management. In the short time since that acquisition, things have been nothing but positive for ParkMyCloud and our customers. ParkMyCloud remains a separate brand and we continue to invest in the product and add new features to the platform to help our customers automate cost control for AWS, Azure and Google clouds. We now have more than 1,100 organizations in more than 50 countries using ParkMyCloud, achieving an average ROI of 815%. Yes, you read that correctly – 815%!
A few interesting trends found in the cloud usage tracked in our platform over the last 12 months:
There are now more Google Cloud projects being managed in the ParkMyCloud platform than Azure subscriptions, but conversely are more Azure resources than Google resources.
We now see ParkMyCloud customers using both Azure and Google Cloud together. This is new – in the past we have seen combinations of AWS and Azure as well as AWS and Google Cloud.
Every large enterprise that was using AWS exclusively 2-3 years ago now also has some Azure resources in the platform. Combined with the last data point, you can see how multi-cloud is truly the current reality.
The resource count in the platform is up over 600% over the last year. Obviously organic growth and the acquisition of new customers drives this, but we have seen a big uptick in the use of scale groups and analytics workloads, an effect of greater needs for elasticity.
Looking Ahead: Bigger and Better Cloud Optimization and Automation Coming Soon
The big news for our customers this year has been the addition of rightsizing to the platform. We currently support automated rightsizing for AWS and Google Cloud, and will have Azure complete in a few weeks. Soon, we’ll also be offering scheduled resizing which will give you flexibility to align resizing with your internal maintenance windows and other specific times to minimize downtime. During the second half of this year, we plan to add support for containers, snapshot management and the ability to identify AWS Reserved Instances. This last addition will help users see how they are utilizing their Reserved Instances and whether their utilization needs to match their reservations. Users will also be able to plan Reserved Instance purchases based on their uptime needs, better matching reservations vs. on-demand resources with schedules.
How do we develop this roadmap and stay on a path of constant improvement? We have a lot of customer conversations and get great input from our customers on our Slack channel. We hear about containers, serverless and other more advanced PaaS offerings that users would like to manage in addition to the main culprit of cloud waste, oversized and idle resources.
As always, we are open to feedback on what’s most important to you. What would help you optimize your cloud environment? Let us know in the comments below (or if you prefer, Slack or email.)
If we don’t hear from you, we will make these ground-breaking decisions on a warm Tuesday evening at Crooked Run Brewery in Sterling, VA (that’s where some of our best ideas come from). If you are in the vicinity, swing by for a beer!
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