What is our primary use case?
My primary use case is to set up an end-to-end application to deliver a business case involving data ingestion, processing, transformation, and checking, followed by outputs to other functions and processes in AWS and also to external systems.
We are using Step Functions as a core automation tool and it offers great power through its simplicity. It is quite easy to use, although there is a learning curve when using the Step Function scripts. Once mastered, after a week or so, the flows can be built quickly and effectively, allowing us to link a custom business process to multiple other AWS service automatically.
That done, most business cases can be delivered easily and quickly, all in a serverless and cost-effective way.
How has it helped my organization?
AWS has improved my organization by:
- saving us time, cost, and difficulty by allowing us to use serverless services
- enabling us to assemble complex applications with the minimum of boilerplate and plumbing
- allowing us to pay-as-we-go, so we can rapidly prototype, test, and then deploy to a production application setup
We can run advanced demos with our own data very quickly, showing potential clients the value of our services when we assemble apps for them.
We can show customers clear cost benefits and clearly effective solutions when assembling AWS services together.
What is most valuable?
The security has great IAM, roles, and carefully partitioned permissions that allow us to fine-tune control across our applications. External intrusion attempts will never get past application boundaries, which increases trust.
The composition of apps has everything wrapped according to function and applications. We can assemble services as we go. This speeds delivery times by orders of magnitude.
The price forecasting and billing dashboard by service, with billing budgets and alerts, have helped us shut down resources that were accruing costs that we no longer needed, saving us money.
What needs improvement?
The service's power lies in its simplicity. It is great in that respect.
The UI is constantly being improved and the billing dashboard has been improved.
Previously, we asked for more end-to-end workshops, examples, and tutorials and these have been added and improved.
Recently, AWS has been adding improvements across services, documentation, tutorials and we have now got workshops with real-world scenarios which are tremendously useful It makes me a very happy user.
AWS and the cloud is a space for constant learning and AWS has increased their output in that respect.
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For how long have I used the solution?
I have been using AWS since 2014.
What do I think about the stability of the solution?
The solution is very stable. The only errors I encountered were my own. Some services took a few minutes to refresh and propagate across my environments, and once these had propagated, the solutions were rock solid.
What do I think about the scalability of the solution?
The scalability is excellent. At no point have I hit scalability limits with AWS services and features.
How are customer service and support?
Customer service and tech support were excellent a few years ago when I needed them.
My general process is to explore and check options and run from a tutorial or AWS workshop. If this doesn't get me results, I then do a web search, and I generally find either further AWS docs or a specific example I can use to solve my issue. Within the last few years, my colleagues and I have been able to deliver as required.
Which solution did I use previously and why did I switch?
We did previously use a different solution when building AWS Lambda cloud functions. I could compare them directly with Azure Functions and Google Cloud and have found that the AWS Lambda solution is simpler, clearer, deploys quicker, and is generally much more simple and effective to use.
In terms of documentation, AWS is the clear leader. Their end-to-end examples and workshops are much more effective.
AWS services in many cases are deployed to AWS after being validated in Amazon.com's operations. This is evident in the ease-of-use and simplicity of many of the service features, and also in the excellent options offered for more complex services like AWS Forecast, where, for example, a checkbox and drop-down allows the user to add holidays for the country they work in when doing forecasts.
AWS has a stronger focus on business solutions than either GCP or Azure, and in many of the solutions, I have used. This is why in many cases I have switched from using other clouds, to AWS.
How was the initial setup?
The setup in AWS is a whole service in and of itself. To set up AWS applications, AWS offers a full service, CloudFormation, with some added features that allow us to automate the deployment of the full solution stack.
This makes setup complex, in that one must modify the CloudFormation template one requires and validate it. An external resource was required to check the templates.
Once this is done, the full solution stacks are automatically deployed.
What about the implementation team?
I handled the initial setup in-house and by myself.
What was our ROI?
A recently deployed Step Function automation fulfilled all the needs of a workflow automation engine while remaining below the free operation per month, so we were able to deliver a fully automated application approval process without paying for any workflow automation engine license fees or any server hardware or infrastructure costs.
What's my experience with pricing, setup cost, and licensing?
I would advise others to work from an architecture overview.
Be aware of the very powerful schema-less data services in the cloud. They can help remove the need for data warehouses - e.g. multi-TB datasets - can be read, joined, queried and made to output daily reports within minutes, on temporary clusters, and that cost less than USD1000 per month. This is compared to the hundreds of thousands of USD for data warehouse licensing costs, plus the schema design time and ongoing DevOps they require.
Moving to serverless operations in the cloud frees up your people to deliver business services rather than spend days and days on administering data centers and the associated concerns that come with them.
Which other solutions did I evaluate?
I also looked at Azure and it was deemed less reliable than AWS as AWS has not had as many outages and uptime concerns as Azure has had of late. Azure Function Apps, Data Factory, Managed SQL.
Besides Azure, I looked at GCP and VMs, Cloud Functions, Speech-to-Text transcription, BigTable, and BigQuery.
What other advice do I have?
Empower your in-house people to start building and running their workloads in AWS.
Let them learn as they go. There are multiple online courses for a few dollars that can assist with specific, individual AWS services, as well as running through the AWS workshops.
Incentivize AWS certifications. Involve your tech people with business solution prototyping.
Tag your resources, name them well, and set budget thresholds. Assign people to tune the resources being used. Incentivize communications and publish the AWS services and features being used to deliver your business capabilities.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.