Functions as a Service from IT Svit
Many businesses that want to utilize their Big Data analytics to the fullest extent need to use serverless computing or functions-as-a-service. This feature is provided by AWS, GCP, MS Azure and IBM, but naturally, AWS and GCP are the most popular platforms. You can run the code as a function on your own or hire professionals to minimize the risks. IT Svit is ready to help with enabling Functions-as-a-Service for your business projects.
Remote management for a managed service
The main reason for hiring a Managed Services Provider to run Functions-as-a-Service for you, is because AWS Lambda works excellently only with native Amazon web services. Embedding it into a third party system requires a decent cloud infrastructure management expertise and this is where IT Svit excels, as we have 5+ years of DevOps expertise and work with serverless computing since its public release.
FaaS consulting and implementation
If your business is about to embark on a Big Data analytics journey and you want to use the most robust and cost-efficient systems, planning ahead is crucial to ensure there is no roadblocks along the way. IT Svit has ample experience with providing Functions-as-a-Service design and implementation to help you reach your business goals.
IT Svit helps businesses get the most out of their Functions-as-a-Service
Every company aiming to utilize its cloud infrastructure to the fullest extent comes to the decision to implement Big Data analytics. This approach provides multiple and quite tangible business benefits but requires quite a significant level of system architecture expertise to ensure the resources allocated to this endeavor are used cost-efficiently.
Functions-as-a-Service is the response from cloud vendors like Amazon Web Services and Google Cloud to this kind of market demand. This kind of web service provides the capability to run your code — any code — without ever requiring to configure the server cluster and have all the scalability, security and maintenance challenges handled for you. How does it work?
FaaS is provided on a Pay-as-you-go billing model and provides a variety of interfaces to interact with other Amazon web services, Google Cloud Big Data tools or any third-party components. If acts as a kind of glue that holds different parts of your workflows together. The most important aspect of FaaS that it is dormant until it is not needed and shuts down immediately after it finished working — so you spend an absolute minimum of computing resources.
For example, your system operates some data and it has to be analyzed using stream processing or batch processing. This means that there must be several system components:
- some data storage,
- some ETL process (Extract-Transform-Load),
- some data visualization modules
- these modules must be connected to your customer-facing systems and mission-critical infrastructure environment,
- they must provide easy data integration capabilities to export the analytics results into a variety of endpoints in different formats, etc.
In other words, a Big Data analytics system is a complicated solution with a large number of interacting components, some of which must become active on a specific stage of data processing, and some must operate all the time. Thus said, FaaS is a feature that can be configured to serve as a medium between those moving parts, that is invoked only when needed, performs the required action and goes dormant afterward.
FaaS can be invoked through API calls, webhooks, scripts or by any other means of interaction used in your systems. Once a dormant system receives the request, a Docker invoker spins up the needed type of instance and a load balancer scales it to be able to process the volume of the data incoming. This takes some time — from several seconds to minutes — but is much better than keeping a single instance always running idly and scaling it up based on request.
FaaS has several distinctive features from a standard cloud infrastructure instance:
- it runs for quite a limited time
- it uses limited CPU power and RAM
- it handles limited volumes of data
The limitations are put in place to distinguish this kind of service from a standard Amazon EC2 or Google Kubernetes Engine instance that works 24/7. This way, you have access to a powerful feature that comes online only when needed and shuts down as soon as the job is done to conserve your money. The question here is how to configure this system the way it has to be configured.
There are three main approaches to enabling access to such expertise:
- Working with support engineers from the cloud service providers like AWS or Google Cloud
- Hiring experienced Big Data architects in-house
- Outsourcing this task to a Managed Services Provider like IT Svit.
The last approach is the most cost-efficient one, and below we explain why it is so.
Many companies prefer to hire specialists in-house for their projects. However, Big Data analytics projects are quite complicated and require deep expertise in cloud architecture management and optimization. If you want your Big Data analytics projects to be done correctly from the start, you would want them delivered by experts — and Big Data experts are not easy to come by on the job market.
This is why multiple businesses decide to go for fully-managed FaaS services from their cloud vendors. However, these specialists would recommend using many vendor-specific features, which can result in increased project costs — just because they are best used to working with these tools. Would you happen to have various third-party modules in your system — that would be a problem. Besides, your projects would be served as a part of a long ticket queue, and even under SLA coverage that would result in TTR of 4 hours much more frequently, than 15 minutes. Lastly, but not the least importantly — cloud-specific FaaS infrastructure will be obsolete should you ever decide to move to another cloud platform.
This is why working with a Managed Services Provider like IT Svit can be the best solution. We have lots of experience working with platform-specific and open-source Big Data tools and we can build cohesive Big Data analytics systems using a combination of both kinds of platforms. Thus said, you gain instant access to a team of experienced Big Data architects with a wide knowledge of best practices of building solutions for data analytics using Functions-as-a-Service.
If this sounds like something your business could benefit from — IT Svit is always glad to assist!