Confluent & Chakray
Chakray is an Systems Integrator partner with Confluent who provide platform, distribution and additional tooling around the popular Apache Kafka event streaming open source project. Our partnership with Confluent has enabled us to build a Kafka consulting practice of Confluent Certified Kafka Developers and Administrators covering UK, Spain, Canada, LATAM and APAC regions. We have experience in the deployment and management of Kafka solutions.
How we help with Confluent & Apache Kafka
As an event streaming platform there are various organisational initiatives where this technology may be suitable. Assessing whether event streaming technology is appropriate and comparing the approach with other options is an important first step. We help organisations perform informed value based assessments with respect to technologies and approaches. There are a number of key initiatives where we see event streaming platforms like Confluent Kafka in use:
- Event driven architecture & microservices
- Core integration strategy
- Digital transformation
- Real time streaming analytics
- Legacy modernisation
- Machine learning & artificial intelligence
Kafka is a key enabler in terms of achieving digital agility. In order to realise that organisations need to build or engage a well developed Kafka capability, there are skills and roles that need to be established. Chakray can help organisations assess and plan for this capability.
We provide the following Confluent services:
Design & Architecture
Managed Services / Support
Implementation / Development
Delivery / Project Management
Organisations engaging this technology tend to be very technical or development focussed. It is no small undertaking to deploy an event driven architecture in an organisation. You may already have existing investment in microservices and be looking to an event backbone to more effectively decouple them. We also see organisations transitioning to Confluent Kafka to underpin their overall integration strategy. A better approach to delivering en masse real-time data to systems and application.
Confluent Kafka deployment is every bit as much about the opportunities it presents as it is the problems it solves. Technology organisations, or those that are transitioning to becoming technology organisations, to become more competitive in their market, will likely be looking more at opportunity in their business cases than the cost of deployment. Likewise with respect to organisations that need to deliver customer centric solutions and more engaging customer experiences. Event streams related to customer represent behaviours and driving these streams into machine learning enables organisations to harness that behavioural data.
Why Confluent Kafka?
Event streaming has a very close affinity with microservices. In an event driven architecture, producers of events do not need to concern themselves with the consumers of those events. The technology therefore enables microservices to become truly decoupled. Early adoptions of microservices, whilst functionally decoupled, still generally expect something back from the other microservices they communicate with. Apache Kafka enables almost pure autonomy of microservices. This comes at a price in terms of complexity in deployment though and this is where organisations can reap the benefit of Confluent’s rich Kafka platform.
Confluent significantly simplifies the deployment of Kafka with the Confluent platform, providing tooling for monitoring, scaling and automatic load balancing of Kafka implementations. Confluent has solved the infrastructure deployment challenge on premise and across all the major cloud platforms so that organisations can just engage the technology and reap its benefits. More than 60% of Fortune 100 companies and 30% of Fortune 500 companies are already using Kafka. As an open source project within the Apache Foundation it can be considered to be battle tested/hardened and Confluent are one of the primary contributors to the project.
Kafka Connect provides a rich ecosystem of community and Confluent supported connectors for popular applications and technologies. Kafka REST Proxy provides simple connectivity where connectors don’t already exist allowing applications to connect, produce and consume through simple APIs. Whether organisations need to connect IoT devices through MQTT or legacy service bus applications through JMS, Confluent has it covered and administrators can monitor the entire estate through the Confluent Control Center.
Our team of experts will work closely with yours to ensure an appropriate reference architecture and standards are developed for Confluent Kafka in your organisations. We can help you to focus on the right use cases to demonstrate ROI and hone in on the proposition of highest value in your Kafka journey. Confluent has a maturity model and adoption curve within any given organisation. Chakray is here to help you at every step in that journey bringing pragmatic guidance and advice when you need it. Adoption needs to be planned, incremental and measured to ensure success and ROI is achieved in the organisation.
Integration is Chakray’s DNA and whatever else Kafka is an enabling technology, it is an integration technology. We engage it and treat it as we do other integration technologies. As something that is core to the success of digitally transforming organisations in a connected world. Organisations that do it well, build a capability, absorb into their integration strategy and own it within their integration competency. Microservices development teams within an organisation are customers of that competency not the owners.
We firmly believe that organisations seeking to unlock the benefits of event streaming with Apache Kafka should be using Confluent’s technology. Whilst we can deploy a fully open source Apache Kafka implementation, it is not the preferred route. It is a complex architecture to deploy and manage without Confluent’s wrap around technology. In our experience, the overall TCO differences between the two paths will be negligible and one of those paths is significantly easier.
It’s beneficial to have a holistic view and position this technology strategically within the organisation. It’s not just a development decision, it has the potential to enable significant opportunity within an organisation. With the right business engagement during adoption, organisations can realise even greater long term value and opportunity from this technology.
Event granularity is a key consideration when implementing Kafka, there is no specific rule to the granularity of events, though more benefit can be achieved by adopting a level that best suits the use case. A more fine-grained approach will lead to more events being captured, though with the right monitoring, management and administration capabilities in place, such as utilising Confluents’s Schema Registry, then this can easily be catered for. The same approach should be taken with the loose coupling of services, it is necessary to plan the management and governance in advance so that the services and their interactions can be clearly understood and observed at an organisational level.
Event streaming is a journey and we work with organisations to ensure they are measuring their success during that journey.
Chakray has been a niche integration consultancy since 2013. Our entire team lives and breathes the body of knowledge and disciple of Integration. Whether it is Enterprise Integration Patterns, IPaaS, Microservices or Event Streaming we bring a connected integration mindset to the table when we solve problems for our customers. We help our customers best leverage and realise the value of the technologies they are engaging. Helping them avoid or eliminate technical debt in implementations. Whether it is data expertise, integration, DevOps or something specific like GDPR or data protection, we bring the right SMEs and experience in implementation to assist. Our customers lean on our experience to avoid the common pitfalls and establish the right capabilities within their organisation.
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Kafka is one of the most popular publisher-subscriber models written in Java and Scala It was originally developed by LinkedIn and later