How to start with AWS and why you should use it anyway?
If someone considers Jeff Bezos as a business virtuoso because of the success of his online shop he/she is only a half right. His brilliance lies in the ability to sell almost everything. Like software development output turned into a cloud computing platform. This idea was a real bullseye as AWS now is a significant contributor to Amazon’s revenues.
With almost a hundred services in the portfolio for multiple purposes, it provides coverage of a range of needs and demands in app development. What all of them have in common is scalability, low-cost, and simplicity of usage, and also seamless integration with most of the meaningful programming languages, libraries and frameworks, and 3rd party services. Those values won over developers in Merixstudio and probably most of the devs in the best software houses around the world. We not only use AWS but also cooperate with Tenesys - a polish official Amazon Web Services partner. Despite Amazon services’ user-friendliness, effective utilization requires some mastering. So if you’re wondering how to start with Amazon Web Services there are a number of books, training and also events like a free online one coming on 26th of March - AWSome Day (run by Amazon and Intel).
Amazon S3 - simple cloud storage with a sea of possibilities
To a good start, we present an AWS dead cert - S3 as it is one of the most popular Amazon Web Service and leading cloud IaaS. Designed to store and backup any amount of data it maintains a high level of performance and scalability at the same time. Amazon’s S3 network infrastructure is quite large with 16 data centers around the world. What’s really impressing is level of durability reaching almost 100% which translates into a very low risk of object’s loss. Data are also protected by using checksums to detect corruption of data packets and versioning which enables to recover objects changed or deleted accidentally or in a result of application failures. Simple interface makes developing nice and pleasant but pricing which depends on particular storage classes might be a little confusing. Although Amazon S3 offers a plethora of different features and tools to manage and report on data combining it with other AWS like Lambda or Amazon Lake Formation can really lift up your operations on Big Data.
Amazon Redshift - advanced data warehouse at a reasonable price
If you would like to organize data in more clear data structures you should consider using Redshift. With Pinterest, Nasdaq, and Philips on the client list, it has to offer a lot more than just storing large volumes of data. Of course, we can point out cost-effectiveness as you get 1 TB for only 1000$ per year when subscribing 3-years plan (and some companies testimonials say about even 90% savings compared to previous competitive solutions they used). But money is not everything even considering rapidly growing amounts of data. Cost and capacity are once but the rapidity of processing is what seems to play a vital role in choosing data warehouse today. Amazon mentions 10 times better performance of Redshift in comparison with other DW services. Columnar Data Storage, Advanced Compression, Massively Parallel Processing (MPP) and optimization squeezing every drop of productivity from hardware significantly cut down delivering database queries. Those attributes are completed by automated provisioning and backup, effortless service and quick scaling (changing number of nodes in just a few clicks). Together with Python’s machine learning libraries like Pandas or NumPy, Redshift empowers you to take data analyzing to a completely new level.
Amazon Polly - text-to-speech fuelled by deep learning
Invaluable for text-to-speech purposes in software development. Polly offers not only a range (53 exactly) of different - both male and female - voices but also a quite wide selection of languages (26 for now) which is crucial while delivering an app with global outreach. Furthermore, an output is amazingly natural but if you’re not exactly satisfied with the effect you can customize it by adapting pronunciation, volume, and other variables using Speech Synthesis Markup Language (SSML). A high quality of the service is provided by a deep learning engine developed since 2016. Over those few years, Amazon enhanced its product with additional, awesome features for more advanced TTS applications, like real-time streaming. Developers will also appreciate the simplicity of implementation, user-friendly console, and easy setup. We found out about them deeply while working on one of the latest projects which required integration with Python and Django. With all of Polly’s advantages, Amazon offers profitable conditions of usage. Pay-as-you-go and unlimited replays of a generated file give a chance to implement text-to-speech technology even in educational or just smaller projects.
Amazon Lambda - an event-driven serverless platform in the cloud
Introducing Lambda in 2014 gained Amazon a status of pioneer and main patron of serverless computing. It took two years for competitors like Google, Microsoft, IBM or Oracle to follow Bezos’ company footsteps and released competitive services. With this relatively longest history and a bunch of values, Lambda became one of the leading serverless computing platforms. What exactly affect on its popularity among software developers? First of all - its versatility as it supports not only Node.js (like at the beginning) but a whole spectrum of programming languages - Python, Go, Java, C#, .NET Core, Ruby and Rust.
A great time-saver, apart from handing over responsibilities connected with server management, is auto-scaling - a code is being run in response to each trigger. Reducing the amount of work spent on those tasks enables a developer to aim more attention at e.g. creating business logic of an app. And time is not the only thing you can save. What really gives Lambda the upper hand is pay-per-execution pricing and a free trier including 1M requests and 400,000 GB-seconds of compute time per month.