Two years ago, Amazon Lambda was announced in the Re: Invent conference. And this year, Amazon has the tech world bouncing in excitement with new launches like Snowball, Lex, Lightsail and enhancements in EC2 and Lambda. The new launches in 2016 conference include Lex, Lightsail and Greengrass. The tech giant is pushing its cloud services to more heights with enhanced features. More power to the developers!
With AWS Greengrass, developers can focus on the Internet of Things. The future is in IoT and Amazon is making sure it has its weapons ready to fight with other tech companies in the future. So how does AWS Greengrass pair up with Lambda? It runs the serverless computing model of Lambda and allows developers to use the same serverless model in the IoT.
In this year’s conference, new enhancements on Lambda have been announced, namely Step function and Lambda on the edge.
With [email protected], developers can directly attack the traffic coming on to Amazon’s CloudFront CDN nodes. In short, the apps will have better performance and efficiency as the traffic is not going back to AWS. The incoming traffic can be handled at the edge locations, which means a low network latency.
The server requests like HTTP are inspected by the functions and a suitable action is taken on them. The lambda functions can also be executed on external hardware (not using Amazon cloud or has connectivity to the Internet) using Greengrass. Lambda is also integrated with Snowball and can support tracing through X-Ray (which will enable developers to debug code easily).
Other functions of Edge include:
• Easier A/B testing through rewritten URLs and cookie inspection.
• Validate headers, tokens and modify the headers before forwarding the request to source.
• Send different content to users based on their device.
Note: You can learn lambda using hands-on labs using Ryans online courses. You can get this course on offer from here. AWS lambda 2016 course
A revision on Lambda
Lambda will run the code for you using a server-less model and the AWS infrastructure. Basically, developers just need to upload their code, create a Lambda function and select the event source like S3, Dynamo DB. Naturally, it can handle jobs like compute resources in response to any event like in-app activity.
AWS Lambda can also handle jobs like code monitoring, provisioning and server maintenance. So, developers don’t have to work on scaling, provisioning or managing servers! Developers can use Java, Node, Python or C#. And the best part, there’s support for all applications and backend services, no need to learn any framework and you can also work on native or third party libraries.
Pay as you go!
The price depends on the number of requests for functions and the execution time of the code. Developers can try it for free and the freebies include access to over 700 free software and AWS Cloud services for 12 months. Developers can query up to 1 million requests and 3.2 million seconds of compute time per month, free of cost.
Note: This free pricing model is available only for new customers!
In a nutshell, developers can deliver efficient apps and with the help of [email protected], Lightsail, CloudFront and Greengrass. Amazon is developing a complete suite for developers to work on IoT and cloud-based applications. This really helps Amazon in beating their competition and be one step ahead of the competition.
The king of e-Commerce and cloud computing services, Amazon announced Lightsail at the AWS re: Invent conference. Lightsail is a simple tool offering a breezy server management capability and massive data transfer capabilities. Developers can set up their virtual private servers, integrated with AWS.
Amazon Lightsail Features
The service is targeted to provide storage, computing and networking capabilities to developers and let them manage their work in the cloud. Lightsail is going to be a direct competitor to services like DigitalOcean with the basic variant starting from just $5 a month.
According to the AWS CEO, Andy Jassy, it has been designed keeping in mind the customers who don’t want to get into the nitty- gritty details of the underlying services. Developers are good to go with just a couple of steps – choose the operating system, storage, memory, etc and finalize a name to run your own VPS. Since Lightsail focuses on keeping it really simple by taking care of all simplifying complexities for end users, it is beneficial for the less technical users.
With this move, Amazon is concentrating on improving a vulnerable side of their business. It will cater to developers who are looking for low-cost offerings. Moreover, it is a fast and simple application which can launch a virtual private service with ease.
Lightsail AWS Integration
Since Lightsail is integrated with AWS, it will have all the features a VPS requires – power, reliability, and security. If the requirements increase, developers can also connect to the most advanced services like additional AWS database, messaging and others.
Lightsail includes all the essential components to get a head start on a project – DNS management, virtual machine, SSH connectivity SSD-based storage, data transfer and a static IP at affordable monthly prices. Amazon claims that developers can launch their own virtual private servers with just a few clicks.
Developers can choose their operating system – Ubuntu, Linux, etc, stacks or application like WordPress, Joomla or Drupal among many others.
Then, server size needs to be selected. Lightsail comes in 5 size variations – 20 GB, 30 GB, 40 GB, 60 GB and 80 GB SSD disk. Once this is done, Lightsail will automatically launch the VPS, attach the selected storage, manage IAM, and create a security group, virtual private cloud, setup the DNS and IP addresses.
Other features include:
SSH terminal access
SSH key management
A lot of new features have also been added to AWS to make it more appealing. Athena, an analytic service that allows customers to pay for queries that are run. Artificial intelligence services like Lex, Polly and Recognition to build conversational interfaces, convert text to speech and perform machine learning, especially deep learning based image analysis. AWS Snowmobile is another service, which can move enormous data to the cloud.
Users can try Lightsail free for a month and you can sign in to your AWS account to try Lightsail or create a new account. AWS accounts also include 12 months of free tier access and use of Amazon EC2, S3, and Dynamo DB.
Programming Languages… AH! There are so many!! And it is really confusing to figure out which language you should learn. Should you choose C, the Yoda of languages or choose something like Python, Luke Skywalker of the geek world. Or maybe it could be between Java and Ruby. Well, whatever you learn or give up, it is difficult to decide. It’s like all the languages are attracting them towards you and you have no clue what to forego and what to choose! Let’s get down to business, shall we.
Best Programming Languages to Learn
We have compiled a list of the best programming languages you can learn, potential salary and community support. Maybe after reading this article, you might be in a better place to decide.
If there was a language that had the best of both functional and object-oriented concepts, then it is Scala. It is a rockstar programming language – it brings in real-time processing and is an object of admiration. It has unhindered access to Java as it uses the JVM. It can handle huge data with its libraries, match patterns and focuses on interactive development.
Other great features include support for big data and REPL. The downside is its compiler which is quite comparable to a Pentium 5 processor. It could do with some improvement, but overall it is forgivable for its follies.
Average Scala Developer Salary: $112,000
Write anywhere, run anywhere – the mantra of Java is quite appealing for developers. It is an all-purpose friend, whether you are coding an application or planning to become a data scientist or a mobile app developer, Java can make your life easy! Since a large part of Android runs on Java, it is beneficial to learn to program in Java. Then you can probably start learning Android SDK and focus on app development in a full-fledged way.
Java has been in the business for a long time and has provided a foundation to many website and software structures. It can be used by data scientists as well, but it doesn’t provide the brilliance of R and Python.
If you want to learn a traditional language, then Java will be a safe bet. Many programming languages like Storm, Kafka, and Scala are running on JVM. So it looks like Java will be here for a long time to come! Java has nearly 9 million developers so you can expect exceptional community support
Average Java Developer Salary: $102,000
Python is quite simple to learn and follows the conventional object-oriented programming concepts. R is not well suited to fit in as a comprehensive tool for data scientists. Python fills in those gaps as it is a lucid and practical tool.
Naturally, it is one of the best languages if you are planning to move in the field of data analytics, data science or big data. Since Python puts a lot of emphasis on readability; it is quite easy to understand the code written by others. You can also run machine learning algorithms using Scikit-learn, the native machine learning algorithm.
Python is the guy that everyone likes in the party. The community support has grown over the years and now it is a huge name in the geek community. A data scientist should know deep learning, a rising subject in the machine learning domain. And, python has all the capabilities and vibrant community to help you achieve their learning goals.
Average Python Developer Salary: $102,000
If Python is Leonard Hofstadter, then R is the annoying and unforgettable friend, Sheldon Cooper. It has been in the business ever since 1997 and is a great alternative to heavy tools like Matlab and SAS. Statisticians love R and it has great utility in the corporate world.
R might be intimidating for beginners, but give it some time and let it grow on you. R makes data manipulation and handling complex data, a child’s play. It has vibrant community support and new features are added constantly. It is a highly popular language among data scientists.
Average R Developer Salary: $62,000
Swift is a programming language developed by Apple. Earlier, Apple ecosystem was revolving around Objective C. But in an attempt to make things easier for developers, Apple released Swift, it’s very own programming language.
Why should you learn it? That’s quite simple, if you see yourself as an iOS app developer, you must learn Swift. The flaws in Objective-C have been addressed by Swift, so you can see a relatively clean, fast and error-free. It can also reduce the length of your code, saving you time and energy.
Moreover, it is open source, so developers can also develop on Windows or Linux systems, design their compilers and be assured that their apps are compatible with Apple devices.
Average Swift Developer Salary: $112,000
Ruby on Rails
Ruby is a favorite among developers, startups, and established businesses. Although its fame was dwindling a few years back, RoR has started regaining its popularity. Ruby has largely improved the framework and has brought agility and modular approach for developing new applications. It has a thriving community support and you can expect constant improvements in code and huge support.
Average Ruby Developer Salary: $103,000
In the realm of big data analytics, NoSQL databases are something you cannot avoid. If you are looking for an opportunity in the Big Data domain, you should consider learning the following NoSQL databases.
1. MongoDB 2. Cassandra.
You can view the list of NoSQL databases from here.
Average NoSQL Developer Salary: $105,000
Languages might change, but database requirements will never see a shift. Enterprises are reliant on SQL and database technologies like MySQL, Microsoft SQL Server are widely in used. And since the demand is always high, there is no doubt that the salaries for database professionals are high.
Average SQL Developer Salary: $92,000
Languages worth considering
There are other upcoming languages which might not be that well known and have less community support. But these languages are slowly making their presence felt. Few of the languages worth checking out are:
Julia is a newbie here and has the potential to surpass R and Python. It will need some more time before it can compete with the established players. Data scientists must watch out for Julia which is a fast growing language and has the capability to revolutionize data crunching.
Go or Google Programming language, is based loosely on C. It has gotten a lot of popularity in 2016 and that might skyrocket in 2017. With an average salary of $117,000, Go can be a suitable option for developers.
Programming Language Trends as per TIOBE index
As in the smartphone world, there is no clear winner in the programming languages world as well. If there was ever a war among programming languages, it would be a damp squib. Although C and Python (PythoC or Cython) might win, each language has its benefits and shortcomings.
If you are looking for mobile development, maybe you could opt for Java or Python if your aim is to become a data scientist. However, becoming a ninja programmer takes time and effort. Make sure that you take the benefits of opportunities and have fun with coding!