Kafka API is th Standard for Event Streaming

Actual-time beats gradual information in most use circumstances throughout industries. The rise of event-driven architectures and information in movement powered by Apache Kafka permits enterprises to construct real-time infrastructure and functions. This weblog put up explores why the Kafka API grew to become the de facto customary API for occasion streaming like Amazon S3 for object storage, and the tradeoffs of those requirements and corresponding frameworks, merchandise, and cloud providers.

De Facto Standard API - Amazon S3 for Object Storage and Apache Kafka for Event Streaming

Occasion-Pushed Structure: This Time It is Not A Fad

The Forrester article “Occasion-Pushed Structure: This Time It’s Not A Fad” from April 2021 defined why enterprises are not simply speaking about event-driven real-time functions, however lastly constructing them. Listed here are some arguments:

  • REST limitations can restrict what you are promoting technique.
  • Knowledge must be fluid and real-time.
  • Microservices and serverless want event-driven architectures.

Actual-time Knowledge in Movement Beats Sluggish Knowledge

Use circumstances for event-driven architectures exist throughout industries. Some examples:

  • Transportation: Actual-time sensor diagnostics, driver-rider match, ETA updates
  • Banking: Fraud detection, buying and selling, threat methods, cellular functions/buyer expertise
  • Retail: Actual-time stock, real-time POS reporting, personalization
  • Leisure: Actual-time suggestions, a personalised information feed, in-app purchases
  • The listing goes on throughout verticals…

Actual-time information in movement beats information at relaxation in databases or information lakes in most situations. There are a few exceptions that require batch processing:

  • Reporting (conventional enterprise intelligence).
  • Batch analytics (processing excessive volumes of information in a bundle, for example, Hadoop and Spark’s map-reduce, shuffling, and different information processing solely make sense in batch mode).
  • Mannequin coaching as a part of a machine studying infrastructure (whereas mannequin scoring and monitoring typically require real-time predictions, the mannequin coaching is batch in virtually all at present out there ML algorithms).

Past these exceptions, virtually all the pieces is healthier in real-time than batch.

Remember that real-time information processing is extra than simply sending information from A to B in real-time (aka messaging or pub/sub). Actual-time information processing requires integration and processing capabilities. If you happen to ship information right into a database or information lake in real-time however have to attend till it’s processed there in batch, it doesn’t remedy the issue.

With the concepts round real-time in thoughts, let’s discover what a de facto customary API is.

What’s a (De Facto) Customary API?

The reply is longer than you would possibly count on and must be separated into three sections:

  • API.
  • Customary API.
  • De facto customary API.

What’s an API?

An utility programming interface (API) is an interface that defines interactions between a number of software program functions or combined hardware-software intermediaries. It defines the sorts of calls or requests that may be made, easy methods to make them, the information codecs that must be used, the conventions to comply with, and so forth. It will possibly additionally present extension mechanisms in order that customers can lengthen present performance in numerous methods and to various levels.

An API may be completely customized, particular to a element, or designed based mostly on an {industry} customary to make sure interoperability. By means of data hiding, APIs allow modular programming, permitting customers to use the interface independently of the implementation.

What’s a Customary API?

Business consortiums or different industry-neutral (typically world) teams or organizations specify customary APIs. A number of traits present the trade-offs:

  • Vendor-agnostic interfaces
  • Sluggish evolution and lengthy specification course of
  • Most distributors add proprietary options as a result of a) too gradual strategy of the usual specification or extra typically b) to distinguish their business providing
  • Acceptance and success rely on the complexity and added worth (this sounds apparent however is usually the important thing blocker for achievement)

Examples for Customary APIs

Listed here are some examples of normal APIs. I additionally add my ideas if I feel they’re profitable or not (however I absolutely perceive that there are good arguments towards my opinion).

Generic Requirements
  • SQL: Area-specific language utilized in programming and designed for managing information held in a relational database administration system. Profitable as virtually each database someway helps SQL or tries to construct the same syntax. An excellent instance is ksqlDB, the Kafka-native streaming SQL engine. ksqlDB (like most different streaming SQL engines) is just not ANSI SQL however nonetheless understood simply by those that know SQL.
  • J2EE / Java EE / Jakarta EE: Profitable as most distributors adopted no less than elements of it for Java frameworks. Whereas early variations had been very heavyweight and sophisticated, the present APIs and implementations are rather more light-weight and user-friendly. JMS is a good instance the place distributors added proprietary add-ons so as to add options and differentiate. No vendor-lockin is simply true in concept!
  • HTTP: Profitable as utility layer protocol for distributed, collaborative, hypermedia data methods. Whereas not 100% right, folks sometimes interpret HTTP as REST Net Providers. HTTP is usually misused for issues it’s not constructed for.
  • SOAP / WSDL: Partly profitable in offering XML-based internet service customary specs. Some distributors constructed good tooling round it. Nevertheless, that is sometimes solely true for the fundamental requirements resembling SOAP and WSDL, not a lot for all the opposite complicated add-ons (typically known as WS-* hell).

Requirements for a Particular Downside or Business

  • OPC-UA for Industrial IoT (IIoT): Partly profitable machine-to-machine communication protocol for industrial automation developed. Adopted by virtually each vendor within the industrial house. The disadvantage (equally to HTTP) is that it’s typically misused. As an example, MQTT is a significantly better and extra light-weight selection in some situations. OPC-UA is a good instance the place the core is profitable, however the industry-specific add-ons will not be prevalent and never supported by instruments. Additionally, OPC-UA is just too heavyweight for most of the use circumstances it’s utilized in.
  • PMML for Machine Studying: Not profitable as an XML-based predictive mannequin interchange format. The thought is nice: Practice an analytic mannequin as soon as after which deploy it throughout platforms and programming languages. In apply, it didn’t work. Too many limitations and pointless complexity for a challenge. Most real-world machine studying deployments I’ve seen within the wild keep away from it and deploy fashions to manufacturing with a normal wrapper. ONNX and different successors will not be extra prevalent but both.

In abstract, some customary APIs are profitable and adopted effectively; many others will not be. Opposite to those requirements specified by consortiums, there may be one other class rising: De Facto Customary APIs.

What’s a De Facto Customary API?

De Facto customary APIs originate from an present profitable answer (that may be an open-source framework, a business product, or a cloud service). Two methods exist how these de facto customary APIs emerge:

  •  Pushed by a single vendor (typically proprietary), for instance, Amazon S3 for object storage.
  • Pushed by an enormous group round a profitable open-source challenge, for instance, Apache Kafka for occasion streaming.

Irrespective of how a de facto customary API originated, they sometimes have a couple of traits in frequent:

  • Creation of a brand new class of software program, one thing that didn’t exist earlier than.
  • Adoption by different frameworks, merchandise, or cloud providers because the API as a result of grew to become the de facto customary.
  • No complicated, formal, long-running customary processes; therefore innovation is feasible in a comparatively versatile and agile approach.
  • Sensible processes and guidelines are in place to make sure good high quality and consensus (both managed by the proprietor firm for a proprietary customary API or throughout the open-source group).

Let’s now discover two de facto customary APIs: Amazon S3 and Apache Kafka. Each are very profitable however very completely different relating to being a normal. Therefore, the trade-offs are very completely different.

Amazon S3: De Facto Customary API for Object Storage

Amazon S3 or Amazon Easy Storage Service is a service provided by Amazon Net Providers (AWS) that gives object storage via an internet service interface within the public AWS cloud. It makes use of the identical scalable storage infrastructure that Amazon.com makes use of to run its world e-commerce community. Amazon S3 may be employed to retailer any sort of object, which permits for makes use of like storage for web functions, backup and restoration, catastrophe restoration, information archives, information lakes for analytics, and hybrid cloud storage. Moreover, S3 on Outposts supplies on-premises object storage for on-premises functions that require high-throughput native processing.

Amazon CTO on Previous, Current, Way forward for S3” is a good learn in regards to the evolution of this fully-managed cloud service. Whereas the general public API was saved steady, the interior backend structure below the hood modified a number of occasions considerably. Plus, new options had been developed on prime of the API, for example, AWS Athena for analytics and interactive queries utilizing customary SQL. I actually like how Werner Vogels describes his understanding of an excellent cloud service:

Vogels doesn’t need S3 customers to even assume for a second about spindles or magnetic {hardware}. He doesn’t need them to care about understanding what’s occurring in these information facilities in any respect. It’s all in regards to the providers, the interfaces, and the flexibleness of entry, ideally with the strongest consistency and lowest latency when it actually issues.

So, we’re speaking a few very profitable proprietary cloud service by AWS. Therefore, what is the level?

Most Object Storage Distributors Help the Amazon S3 API

Many enterprises use the Amazon S3 API. Therefore, it grew to become the de facto customary. If different storage distributors wish to promote object storage, supporting the S3 interface is usually essential to get via the evaluations and RFPs. If you happen to do not assist the S3 API, it’s a lot tougher for firms to undertake the storage and implement the combination (as most firms already use Amazon S3 and have constructed instruments, scripts, testing round this API).

For that reason, many functions have been constructed to assist the Amazon S3 API natively. This consists of functions that write information to Amazon S3 and Amazon S3-compatible object shops.

S3 suitable options embrace shopper backup, file browser, server backup, cloud storage, cloud storage gateway, sync&share, hybrid storage, on-premises storage, and extra.

Many distributors promote S3-compatible merchandise: Oracle, EMC, Microsoft, NetApp, Western Digital, MinIO, Pure Storage, and lots of extra. Take a look at the Amazon S3 website from Wikipedia for a extra detailed and full listing.

So Why Has The S3 API Turn into so Ubiquitous?

The creation of a brand new software program class is a dream for each vendor! Let’s perceive how and why Amazon was profitable in establishing S3 for object storage. The next is a quote from Chris Evan’s nice article from 2016: “Has S3 develop into the de facto API customary?

So why has the S3 API develop into so ubiquitous?  I think there are a variety of causes.  These embrace:

  • First to market: When S3 was launched in 2006, most enterprises had been conversant in object storage as “content-addressable storage” via EMC’s Centera platform. Aside from that, functions had been area of interest and never extensively adopted aside from particular industries like Excessive-Efficiency Computing the place these customers had been used to coding to and for the {hardware}. S3 rapidly grew to become a platform everybody might use with little or no funding. That made it straightforward to devour and experiment with. By comparability, even immediately the leaders in object storage (as ranked by the most important analysts) nonetheless don’t make it straightforward (or attainable) to obtain and consider their merchandise, although most are software-only implementations.
  • Documentation: Following on from the earlier level, S3 has all the time been effectively documented, with examples on easy methods to run API instructions. There’s a doc historical past itemizing modifications over the previous 6-7 years that reveals precisely how the API has advanced.
  • A Single Agenda: The S3 API was designed to suit a single agenda — that of storing and retrieving objects from S3. As such, Amazon didn’t must design by committee and will implement the options they required and evolve from there. Distinction that with the CDMI (Cloud Knowledge Administration Interface) from SNIA. The SNIA web site is tough to navigate, the usual itself is simply on the 4th revealed iteration in six years, whereas the documentation runs to 264 pages! (Observe that the S3 API runs into extra pages, however is infinitely extra consumable, with easy examples from web page 11 onwards).

Cons of a Proprietary De Facto Customary Like Amazon S3

Many individuals would possibly say: “Higher a proprietary customary than no customary.” I partly agree with this. The chance to study one API and use it throughout multi-cloud and on-premise methods and distributors is nice. Nevertheless, Amazon S3 has a number of disadvantages as it’s NOT an open customary:

  • Different distributors (must) construct their implementation on a finest guess in regards to the habits of the API. There’s no official customary specification they’ll depend on.
  • Clients can’t be certain what they purchase. No less than, they need to not count on the identical habits of third get together S3 implementations that they get from their experiences utilizing Amazon S3 on AWS.
  • Amazon can change APIs and options because it likes. Different distributors must “reverse engineer the API” and regulate their merchandise.
  • Amazon might sue rivals for utilizing S3 API branding — although this isn’t more likely to occur as the advantages are most likely greater (I’m not a lawyer; therefore this assertion is perhaps unsuitable and is simply my private opinion)

Let’s now take a look at an open-source de facto customary: Kafka.

Kafka API: De Facto Customary API for Occasion Streaming

Apache Kafka is mainstream immediately! The Kafka API grew to become the de facto customary for event-driven architectures and occasion streaming. Two proof factors:

The Kafka API (aka Kafka Protocol)

Kafka grew to become the de facto occasion streaming API. Comparable just like the S3 API grew to become the de facto customary for object storage. Truly, the scenario is even higher for the Kafka API because the S3 API is a proprietary protocol from AWS. In distinction, the Kafka API and protocol are open supply below Apache 2.0 license.

The Kafka protocol covers the wire protocol carried out in Kafka. It defines the out there requests, their binary format, and the correct solution to make use of them to implement a shopper.

One in all my favourite traits of the Kafka protocol is backward compatibility. Kafka has a “bidirectional” shopper compatibility coverage. In different phrases, new shoppers can discuss to outdated servers, and outdated shoppers can discuss to new servers. This enables customers to improve both shoppers or servers with out experiencing any downtime or information loss. This makes Kafka preferrred for microservice architectures and domain-driven design (DDD). Kafka actually decouples the functions from one another in opposite to internet service/REST-based architectures).

Execs of an Open Supply De Facto Customary just like the Kafka API

The large advantage of an open-source de-facto customary API is that it’s open and often follows a collaborative standardized course of to make modifications to the API. This brings numerous advantages to the group and software program distributors.

The next info in regards to the Kafka API make many builders and enterprises joyful:

  • Adjustments happen in a visual course of enforced by a committee. For Apache Kafka, the Apache Software program Basis (ASF) is the related group. Apache tasks are managed utilizing a collaborative, consensus-based course of with members from numerous international locations and enterprises. Take a look at the way it works if you do not know it but.
  • Frameworks and distributors can implement towards the open protocol and validate the implementation. That’s considerably completely different from proprietary de facto requirements like Amazon S3. Having stated this, not each product that claims it makes use of the Kafka API is 100% suitable and consequently is restricted within the characteristic set and supplies completely different habits.
  • Builders can check the underlying habits towards the identical API. Therefore, unit and efficiency checks for various implementations can use the identical code.
  • The Apache 2.0 license makes certain that the consumer doesn’t have to fret about infringing any patents by utilizing the software program.

Frameworks, Merchandise, and Cloud Providers utilizing the Kafka API

Many frameworks and distributors adopted the Kafka API. Let’s check out a couple of very completely different options out there immediately that use the Kafka API:

  • Open-source Apache Kafka from the Apache web site.
  • Self-managed Kafka-based vendor options for on-premises or cloud deployments from Confluent, Cloudera, Purple Hat.
  • Partially managed Kafka-based cloud choices from Amazon MSK, Purple Hat, Azure HD Perception’s Kafka, Aiven, cloudkarafka, Instaclustr.
  • Absolutely managed Kafka cloud choices resembling Confluent Cloud — really, there isn’t any different serverless, absolutely suitable Kafka SaaS providing in the marketplace immediately (although many advertising departments attempt to promote it like this).
  • Partly protocol-compatible, self-managed options resembling Apache Pulsar (with a easy, very restricted Kafka wrapper class) or RedPanda for embedded/ WebAssembly (WASM) use circumstances.
  • Partly protocol-compatible, absolutely managed choices like Azure EventHubs.

Simply remember that the satan is within the particulars. Many choices solely implement a fraction of the Kafka API. Moreover, many choices solely assist the core messaging idea however exclude key options resembling Kafka Join for information integration, Kafka Streams for stream processing, or exactly-once semantics (EOS) for constructing transactional methods.

The Kafka API Dominates the Occasion Streaming Panorama

If you happen to take a look at the present occasion streaming panorama, you see that increasingly frameworks and merchandise undertake the Kafka API. Though the next is just not an entire listing (and different non-Kafka choices exist), it’s imposing:

The Event Streaming Landscape

If you wish to study extra in regards to the completely different Kafka choices in the marketplace, take a look at my Kafka vendor comparability. It’s essential to grasp what Kafka providing is best for you. Do you wish to give attention to enterprise logic and devour the Kafka infrastructure as a service? Or do you wish to implement safety, integration, monitoring, and so forth., by your self?

The Kafka API is Right here to Keep…

The Kafka API grew to become the de facto customary API for occasion streaming. The utilization of an open protocol creates large advantages for corresponding frameworks, merchandise, and cloud providers leveraging the Kafka API.

Distributors can implement towards the open customary and validate their implementation. Finish customers can select the perfect answer for his or her enterprise downside. Migration between completely different Kafka providers can be attainable comparatively simply — so long as every vendor is compliant with the Kafka protocol and implements it fully and accurately.

Are you utilizing the Kafka API immediately? Open supply Kafka (“automotive engine”), a business self-managed providing (“full automotive”), or the serverless Confluent Cloud (“self-driving automotive) to give attention to enterprise issues? Let’s join on LinkedIn and focus on it! Keep knowledgeable about new weblog posts by subscribing to my publication.


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