“Serverless data pipelines” are a relatively new concept, but they have quickly become popular for providing a more efficient method of data delivery. For us at Xentity efficiency is the name of the game, so you’ll have to forgive us if we come right out and say we absolutely love this concept and the challenges it addresses.
A Past Rife With Inefficiency And Expenses
Historically, data was stored on local servers before going “serverless” became a possibility. “Going serverless” is a method of computing and storage such as utilizing the Cloud, and whether you use a local server or are serverless, data pipelines connect that storage with whomever uses that data. When data was using servers to be “pipelined” to clients, it was slow, inefficient and expensive. Think about what happens when you leave the lights on in a room when you don’t need to, or imagine using a lightbulb with a higher wattage than you need. You’re wasting money, you’re using more power than you need, and it becomes not worth the effort. Servers require memory to pipeline data, and all that memory is used even if you do not need all of it.
Here at Xentity, one of the concepts we introduced in past projects is “independent quality assurance”. For example, traditional Extract-Transform-Load (ETL) concepts state that you have a source of data such as a database that you are trying to pipe records to another target. Somewhere along the way, you do some augmentation or quality assurance. This was fine historically, but now data and information doesn’t always come in one format but many (Think tweets, posts, files, images, documents, and records). How do you test data quality when every piece of data is different? That’s where independent quality assurance comes in. It focuses on looking at the quality of a single record vs. the quality of the data.
The challenge of data access and utilization becomes not only in efficiently loading data, but also transforming it into what the individual receiving the data desires. In a world where data comes in multiple forms, we need a system that can either load data of all kinds, or transform that data into a format where it can be pipelined to the end user.
By analogy, think of natural gas piping. Natural gas is actually transformed into a liquid so that when it is transferred for use and can be handled more easily in the pipelines. Or, say there’s a glass of water and you pour it out. The reason it has to stay a liquid is so that when you’re piping it to wherever it is it’s supposed to go it only goes in that single direction. The transformation part of ETL acts in a similar manner in that it ensures that data remains the same while being moved through the pipelines.
Why Being Serverless Is Awesome
Going serverless basically is the exact opposite of “server data pipelines”. And it is the solution to all of the issues we mentioned earlier. By going serverless we introduce what is known as “Reusable Transform Components”. In past projects, Xentity wanted to build reusable transformations not for the whole record, but to a singular output. We were creating a new derivative of source data, and these reusable components can be mixed, matched, and scaled with different memory power. Therefore you don’t need a monolithic server with 128 mb of memory for something smaller, and by going serverless we can decouple categories of data into their own groups with their own amounts of memory.
This is the reason why more architects are implementing serverless data pipelines. Take a look at the cloud for a great example on a serverless storage that can pipeline data. It’s like a rubber band, it expands to accommodate more when needed, and when you want to take stuff off the cloud, it contracts. In other words, it only works as hard and stores as much when you want it to. You turn the lights on when you need to, and turn it off when you’re done. Or you have the light bulb with the appropriate wattage.
The Benefit Of Going Serverless
With all of that in mind, there are many benefits for organizations moving towards a serverless method of pipelining data. Serverless cloud data pipeline are faster, cheaper, configurable based on either the data itself or the client’s needs. Enterprises scale data pipeline for tight budgets to large enterprise budgets without the server compute costs and ETL Licenses. As mentioned before, servers are way too expensive for how inefficient they are and now need to account the 4 V’s (volume, variety, veracity and velocity). And the data can be loaded into any kind of data storage, whether it’s a database, warehouse, lake, pond, whatever.
Serverless data pipelines also provide reproducibility and replication. Through this new method, clients can test single records of data and more easily reproduce and replicate. It simply provides records that allow easy replication in the future, like a ledger. Going serverless makes traceable data regularly available and accessible in service architecture.
Golden Opportunity For Efficiency
Te recap, serverless data pipelines are a far more efficient and less expensive method of piping data to their destination. At Xentity, we cover a lot of services regarding data, one of which being to pipe it to new destinations. Also, the idea of serverless pipelines fall in line with a lot of our company’s major philosophies: efficiency, better uses of information in the “IT” field, etc. And Xentity’s approach helps make data more traceable and allows for validation, which becomes extremely important in a world where data is far more accessible, and therefore validation becomes something of a necessity.