Why developers use Confluent to manage Apache Kafka

Imagine you are getting groceries delivered, or wanting for a recommendation on what to look at following on Tv, or making use of a credit history card without worrying as well considerably about fraud. The applications that power these interactions all rely on knowledge in motion, and there’s a decent […]

Imagine you are getting groceries delivered, or wanting for a recommendation on what to look at following on Tv, or making use of a credit history card without worrying as well considerably about fraud. The applications that power these interactions all rely on knowledge in motion, and there’s a decent possibility Apache Kafka powers the applications.

Extra than eighty% of the Fortune a hundred use Kafka as the celebration streaming substrate to power genuine-time, consumer-going through applications and application-pushed back again ends. Kafka has develop into the go-to for any firm wanting to combine ever more assorted portfolios of applications and microservices through immutable celebration logs rather than mutable knowledge merchants. The gains are manifold, but recall that Kafka is a dispersed method, and volunteering to function a dispersed method yourself is an ever more controversial selection.

This is why the cloud exists. Through fully managed cloud providers, suppliers bear the money fees and accumulate the operational knowledge needed to operate infrastructure properly. Confluent, the 1st fully managed Kafka support on the market place, allows you aim on constructing applications and including worth to the organization rather than turning dials on operationally intricate infrastructure layers. I’d like to wander you through how Confluent can deliver peace and simplicity to the lives of the folks who work with Kafka.

Cloud-native is the long term of infrastructure

There is often a higher demand for application performance than there is the ability to supply it. This indicates that application groups ought to aim on the activities that develop the most worth that they probably can. Generally, this suggests offering new functions that immediately give a aggressive edge to buyers and customers.

Of system, all applications have to have storage and compute infrastructure to purpose with ongoing progress and routine maintenance, distracting from worth-producing feature progress. This is specially real for Kafka, because dispersed knowledge infrastructure imposes a considerable option price on groups selecting to function it by themselves. Put simply just: Your position is ultimately to just take treatment of your buyers. Whilst managing Kafka might be a suggests to that stop, it is probably not the most practical way to get the position done. This obstacle is one particular of a lot of explanations that led to the rise of managed cloud providers.

Elastic scaling for reals this time

Elastic scalability has often been an inherent aspect of the cloud’s mythology but has been slow in coming to reality. Early on in the cloud’s background, databases innovators used new strategies to horizontal elastic scalability of huge datasets. Extra lately, microservices and container orchestration have assisted deliver application scalability to the masses. Nevertheless, knowledge infrastructure usually has remained notoriously resistant to effortless scalability.

Kafka has an excellent horizontal scale story: topics are partitioned, unique partition logs are assigned to distinctive brokers, then eaten by scalable clusters of shopper applications. There are some scriptable instruments to administer these scale-oriented abilities, but self-managed clusters continue to have to have considerable operational and technical knowledge. For case in point, partition logs really do not continue to be evenly dispersed on brokers as a cluster alterations over time. Even further, new topics are included, and partitions obtain most likely uneven go through and publish website traffic, as organization situations evolve. That is just one particular case in point of something cluster administrators ought to attend to over time.

Confluent has created-in elastic scalability. Clusters scale from to 100MBps throughput with no intervention and up to 11GBps (the recent report as of this producing) through a simple website UI—no going partitions about, no rebalancing brokers. As the earth slowly but surely catches up to the cloud’s authentic promises of elastic scale, Confluent brings scale to knowledge infrastructure in a truly cloud-native way.

confluent 01 Confluent

Connecting your knowledge just about everywhere

Your everyday living will be multicloud anyway, so knowledge infrastructure layers need to have to be multicloud-able to be serious contenders. Confluent is multicloud, natively supporting AWS, Microsoft Azure, and Google Cloud. This adaptability is critical when you need to have to operate on more than one particular cloud, or at the very least be capable to threaten to. Confluent tends to make this effortless by making use of a one administration website UI and a unified manage plane abstracted from the unique cloud infrastructure.

confluent 02 Confluent

But multicloud is not often adequate! Sometimes you really do not want to go almost everything to the cloud. Lots of organizations want to manage a blend of on-prem, non-public cloud, or general public cloud providers. This hybrid cloud encounter is top of brain for Confluent, earning it probable to manage backup providers, segregate products and solutions, and take care of a refined Plan B through the Confluent UI.

confluent 03 Confluent

Really do not get misplaced in the ecosystem, get the full package deal

As the Kafka community has found out in the 10 yrs considering that its delivery, you need to have more than dispersed logs to construct a thriving celebration-pushed method. You also need to have responsible and safe connections concerning all your techniques and streams, which is no suggest feat. Then you can start out to extract worth from the full method with genuine-time stream processing.

Several elements have emerged about core Kafka performance to aid supply on these requirements, the two from the open up supply ecosystem and from Confluent:

  • Kafka Join: The common knowledge integration framework that offers an ecosystem of connectors. It gets rid of the need to have to re-publish connectors for each new knowledge supply.
  • Kafka Streams: A stream processing framework that enriches the existing Kafka shopper framework with refined stream processing performance, rather than offloading stream processing to one more dispersed method.
  • Confluent Schema Registry: Allows manage compatibility concerning evolving applications as message formats adjust over time.
  • ksqlDB: The celebration streaming databases for Kafka making use of SQL to construct stream processing applications you may possibly normally have created with Kafka Streams.
  • Confluent Metrics API: Unifies a lot of of the unique metrics you could acquire through the JMX interface on several method elements into a one, queryable stream of JSON knowledge.

The simple fact of elements like these is that groups will eventually need to have them. They have emerged from the Kafka community and from Confluent for that very reason. It is practically impossible to be proficient adequate in each and every of these places to construct a solution that does not have to have continuous attention for smooth procedure.

With Confluent, you have all the instruments you need to have to be thriving with Kafka at your fingertips. You can use one particular system, and almost everything you need to have is there in a seamless, integrated way, such as hundreds of connectors to common knowledge resources.

Information security at scale is a ought to

Kafka has a least feasible security story: It delivers robust encryption of knowledge in flight and ACL-based mostly authentication and authorization as options. Confluent expands on these functions in the techniques enterprises assume.

confluent 04 Confluent

For case in point, all knowledge in Confluent is encrypted at rest as properly as in flight. On top of that, applications also have to have authentication with each simply call, removing the menace of unintentionally having “wide open” ports.

A wide variety of other Confluent functions aid maintain security simple, such as SAML-based mostly one signal-on and safe obtain to other cloud means in your VPCs.

As proof of these safe abilities, Confluent fulfills a lot of field expectations and certification achievements, assembly specifications for PCI, HIPAA, and GDPR as properly as SOC1, SOC2, SOC3, and ISO 27001 certifications.

It is a obstacle to reach all of these certifications even though also offering a lot of other safe and practical functions out of the box. Builders can construct with self confidence even though leaving the major security carry to the managed system.

But really do not just just take my phrase for it. You can attempt our fully managed Kafka support for free through Confluent or your cloud provider of selection.

Tim Berglund is senior director of developer advocacy at Confluent.

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