Hey there! If you‘re looking to build an automated software system on AWS using a serverless architecture, you‘ve come to the right place. As a fellow tech geek and cloud data analyst, I‘m excited to walk you through 5 robust native AWS services that can help you create a full end-to-end serverless platform.
Trust me, I know first-hand how tedious and complex building these kinds of systems used to be. You‘d have to set up multiple servers, tweaking their CPU, memory, storage, and other configurations based on guesses of future needs. Then you‘d need a team of admins to keep it all running smoothly 24/7. And good luck trying to connect it all into one coherent system!
The cloud offers a better way. With the right serverless services, you can stitch together an automated end-to-end architecture without managing a single server yourself! The cost savings and flexibility can be tremendous for startups and MVP projects. I‘ll outline how it all works below.
First though, let‘s briefly compare the old way of building software systems vs. the serverless approach:
| Traditional Servers | Serverless | |
|---|---|---|
| Infrastructure | Purchase and configure servers and clusters | Leverage on-demand cloud services |
| Administration | IT team required for maintenance and management | No admins needed |
| Cost | Pay for idle resources and continuous uptime | Pay per actual usage only |
| Scaling | Manual intervention to scale up or down | Auto-scaling built-in |
As you can see, serverless solutions save time and money by automating the busywork of infrastructure and administration. Now let‘s dive into the 5 specific AWS services that comprise a robust serverless stack.
AWS S3 Buckets: Serverless Cloud Storage
If you need to store and retrieve files or images in the cloud, S3 buckets are your friend! Amazon Simple Storage Service (S3) offers cheap, flexible cloud storage that scales massively on demand.
As of 2022, there are over 100 trillion objects stored in S3 buckets worldwide! Yet prices remain low, starting at just $0.023 per GB of storage. And you only pay for what you use.
Some key facts about S3:
- Serverless – S3 requires no servers to manage or provision
- Scalable – Handles any volume of data and traffic automatically
- Durable – Stores data redundantly across multiple facilities
- Flexible – Configure for any access pattern from frequent to archival
- Programmable – SDKs for most languages to easily add storage
For our serverless stack, S3 provides inexpensive storage we can access from other services. The pay-per-use model keeps costs down as workloads fluctuate.
I recommend organizing your data thoughtfully in S3. Use folders and subfolders to group related content. Apply permission policies so only authorized users and services can access each bucket and object. Add bucket tags too for easier searching and access controls.
The bottom line is S3 solves the storage piece of your architecture simply and cheaply. Now let‘s look at querying all that data.
AWS Athena: Serverless SQL Queries on S3 Data
What good is storing data if you can‘t analyze it? Athena lets you query your S3 datasets directly using standard SQL. No servers to manage – it‘s entirely serverless!
Athena uses schema-on-read technology. This means your raw data files don‘t require any preprocessing. Just upload them to S3 buckets in a structured format like CSV, JSON, or Parquet. Athena will infer the schemas and let you start querying right away.
Some key advantages of Athena:
- Serverless SQL – Run ANSI SQL queries without any infrastructure
- Cost effective – Charged per query based on data scanned
- Scalable – Handles queries of any size automatically
- Fast – Leverages Presto distributed query engine for performance
- Secure – Integrates with IAM, VPC, encryption, etc.
In 2022, Athena processed over 23 billion queries! Its pay-per-query model and automatic scaling make it a cheap and easy way to analyze data in S3.
Now Athena does have some limitations to be aware of:
- No UPDATE, DELETE, or INSERT statements – Athena treats S3 data as immutable
- Less functionality than full-blown data warehouses
- Not ideal for small, repetitive queries due to startup costs
The key is using Athena for large, ad-hoc analytics queries. For more complex transactional workloads, we‘ll look at another service next. But for basic SQL access to S3, Athena is a serverless slam dunk.
AWS Aurora Serverless: Scalable Relational Database
If your workload requires a dynamic relational database, look no further than Aurora Serverless. This unique database offering combines the power of Aurora with auto-scaling, pay-per-use pricing of serverless.
Aurora is AWS‘s proprietary database engine compatible with both PostgreSQL and MySQL. It offers up to 5x the throughput of standard MySQL along with instant scalability and high availability.
By running Aurora in serverless mode, you get all the benefits of the Aurora engine without any database servers to manage. Aurora Serverless key facts:
- Scalable – Handles up to hundreds of thousands of transactions per second
- High performance – Up to 2x the throughput of provisioned Aurora at lower cost
- Serverless – Completely managed database with auto-scaling
- Cost efficient – Pay per second based on actual database usage
- Reliable – Handles failures automatically. Backups included.
In 2022, over 85,000 customers migrated to Aurora Serverless. The automatic scaling delivers speed and cost savings compared to provisioned databases.
The key is only paying for the actual database workloads you need. For example, if you have a periodic batch job that hits the database hard a few times a day, Aurora Serverless will scale up and down to match. No idle capacity to pay for.
So if you need a relational database that can handle heavy, variable workloads, Aurora Serverless is an excellent fit for your serverless architecture.
AWS Amplify: Frontend Framework for Web Apps
So now we‘ve got a way to store data (S3), analyze it (Athena), and capture results (Aurora). But how do we deliver those insights to users via a web or mobile app?
That‘s where Amplify comes in! Amplify offers a framework for quickly building and deploying cloud-powered frontend web apps using JavaScript, React, and other common tools.
With Amplify, you can:
- Prototype rapidly – Includes UI components for common use cases
- Simplify coding – Libraries handle authentication, analytics, APIs, etc
- Go serverless – Deploy via Git or use Amplify Console
- Scale globally – CDN distributes UI for low latency
- Connect services – Call REST APIs, GraphQL, Lambda functions
By 2023, over 1 million apps will be built using Amplify and AWS AppSync according to IDC. The combination of speed, scalability, and tight integration with AWS makes Amplify ideal for our serverless stack.
While Amplify streamlines frontend development, performance still comes down to efficiently calling backend APIs and databases. So be sure to optimize and scale those components for snappy user experiences!
AWS Step Functions: Build Serverless Workflows
So we‘ve assembled all the pieces of a serverless architecture – but how do we automate and orchestrate workflows between them? Enter AWS Step Functions.
Step Functions allow you to build entire workflows by connecting serverless components. Each "step" consists of an AWS service like Lambda, Fargate, S3, etc. Step Functions handle executing and coordinating each step.
The key benefits of Step Functions:
- Serverless workflows – Chain services together without managing servers
- Visual logic – Design workflows using GUI instead of code
- Error handling – Catch and recover from failures automatically
- Tracking – Logs provide end-to-end monitoring and alerts
- Scalability – Scale executions up to handle any workload
As of late 2022, Step Functions drive hundreds of billions of executions per month! The service has become a mission-critical automation tool across industries.
For our architecture, Step Functions enable orchestrating all the other serverless components into cohesive workflows. Want to process new S3 uploads with Lambda, save outputs to Aurora, and update a dashboard? Step Functions connect those steps seamlessly.
The only catch is Lambda functions are limited to 15 minutes max. So for long workflows, you may need to split work across chained Lambdas. But overall, Step Functions are a game changer for automation and coordination in serverless environments.
Bringing It All Together
Phew, that was a whirlwind tour of 5 game-changing services for building serverless architectures on AWS! Let‘s quickly recap:
- S3 Buckets – Scalable and inexpensive cloud storage
- Athena – Serverless SQL queries on S3 data
- Aurora Serverless – Auto-scaling relational database
- Amplify – Framework for web app frontends
- Step Functions – Orchestrate components into workflows
Chaining these services together lets you go from ingesting data to crunching it to serving insights, all without provisioning a single server yourself. Pretty cool right?
Of course, serverless isn‘t a silver bullet. Applications with intensive CPU, GPU, or memory demands still require careful infrastructure planning. But for many modern workloads, a serverless approach on AWS unlocks speed, savings, and scalability not possible otherwise.
So next time you‘re architecting a new system, keep these services in mind. They provide powerful building blocks for creating automated end-to-end solutions quickly, cheaply, and without the server ops headache. Just don‘t forget to optimize APIs, databases, and application logic too!
Have questions or want help assessing if a serverless approach makes sense for your next project? Feel free to reach out! As a fellow technologist, I‘m always happy to chat cloud, code, and all things serverless.
