Reduce Kafka cost and reinvest in your business
Harness the power of Kafka while shifting costs and focus on your core business needs.
Your challenge
In the early stages, building for Apache Kafka is easy and cheap: its scope is small, and things are moving fast.
As use-cases multiply — due to the simplicity of sharing streaming data across teams — your Kafka infrastructure expands, and challenges arise. Your engineers dedicate more time to build data pipelines, and the proliferation of technical components diverts their attention from your core business. You realize your Enterprise Data strategy has become more fragile.
My Kafka Infrastructure has grown too large
Kafka has become a cornerstone of your data-driven culture. Yet, as you scale, you're faced with several challenges.
- Growing Clusters:Your clusters multiply as your business expands. Each new cluster adds to your costs and administrative workload
- Storage Issues:Managing storage is critical and complex. As your Kafka usage grows, so does the need for efficient storage management
- Networking Costs and Latency:Networking costs increase and latency issues arise when your Kafka is not in the same VPC as your application
- Too many partitions:Controlling and limiting the number of partitions becomes significant as your infrastructure scales. Unchecked, it will impact your ability to grow sustainably
Building enterprise needs on top of Kafka are exorbitant
While you have succeeded in Kafka's mass adoption internally, you are also faced with implementing custom security, governance, and gitops solutions to account for business needs and integration. These are Enterprise must-haves, but the cost to develop and maintain them is significant.
- Homebrew Security implementations:Building and maintaining custom security solutions on top of Kafka demands expertise, time, resources, then ongoing updates to align with evolving data, business needs, and regulatory landscape.
- Workarounds cause Data Duplication:Because Kafka does not provide data masking or encryption solutions natively, the workaround often results in data duplication and increases your security landscape.
- Introducing Enterprise needs impacts all my clients:Implementing global custom behaviour such as end-to-end encryption or governance requirements necessitates costly and disruptive application changes.
- Support a breadth of languages and versions:Your Platform team needs to support libraries used by your Product teams to implement your Enterprise requirements. But it means they have to support Java, Rust, nodeJS, etc., without even mentioning all the different versions. Things can go south rather quickly.
Avoid Kafka issues leading to catastrophic cost implications
Kafka is a mission-critical component in your system architecture. Don't let your CTO lose faith in such a brilliant technology through avoidable production incidents.
- Loss of Business:When applications go down, the company loses revenue. Each second is money-burning.
- Breach of Service Level Agreements (SLAs):Businesses often have SLAs with their clients, guaranteeing a certain uptime level. Any breach of these SLAs can result in penalties or even loss of contracts.
- Support Cost:Application downtime often means an influx of support tickets, which can incur additional costs in staff time and resources to address.
- Losing Trust:Beyond the direct financial impact, application downtime can harm a company's reputation. Repeated or severe downtime can lead to a loss of trust and negative publicity.
My engineering and operational costs of Kafka are excessive
Excessive overengineering of basic data transformations in organizations leads to wasteful practices, resource-intensive solutions, and undesirable repercussions.
- Development Time and Cost Overhead:Writing a plethora of Spring Boot, Kafka Streams applications or deploying Kafka Connect to do simple transformations is a big time and cost sink.
- Deployment & Observability Complexities:Deploying each of these applications presents its own set of challenges and costs: provisioning infrastructure, CI/CD pipelines, version control complexities, and performance monitoring.
- Security Breaches:More applications mean a larger attack surface for potential costly security breaches.
- Maintenance and Upgrades:Every additional application adds to the overall maintenance costs. Each upgrade or modification requires additional testing and can introduce more potential points of failure in the system.
Pay less while doing more with Kafka.
- 1Improve Kafka resource efficiency
- Maximize usage of what you have (and pay for!) more efficiently
- Pay less for all your non-production environments, which are less critical
- Enforce resource limitations to prevent overprovisioning
- 2Engineers focus on the business, not the technicalities
- Avoid building tiny data applications adding complexity to your architecture and create maintenance costs
- Simpler mechanisms for deploying new data pipelines
- Avoid creating bespoke Kafka tooling to solve security or governance needs.
- Language agnostic solution for implementing Enterprise controls. There is no need to account for the breadth of languages clients use to enforce solutions such as encryption.
- 3Protection against production incidents
- Enforce technical constraints to ensure Kafka configurations from your least informed engineer do not cause production incidents.
- Help me to discover my application unknowns. Test the most common Kafka issues without the hassle of building complex test scenarios.
- 4Avoid duplicating data
- Duplicating your data costs real money (storage, networking)
- No need to deploy MirrorMaker or similar to make your data available cross-clusters
- Prevent data security loopholes due to having the same data in different places
Conduktor drastically simplifies your Kafka infrastructure, saving you time, resources, and money. With our innovative features, you can significantly reduce your Kafka costs:
Virtualization of resources
Virtualized resources are cheaper than physical: it's why there has been such a boom in cloud computing. We bring the same to Kafka at all levels: clusters, topics, and partitions.
- Multi-tenancy:Cluster "virtualization" to support a multi-tenant environment.
- Virtual SQL topics:Serverless data transformations avoid you from building, deploying, and maintaining custom applications.
- Topic Concentration:Represent many topics on a single, physical topic to limit partition explosion and maximize Kafka storage efficiency. It's particularly effective when using features like Change Data Capture (CDC) with Debezium.
A new way to share & reuse data
Maintain a single source of truth while having the flexibility to reuse and share that data across your business. This reduces costs associated with data replication and maintaining complex data pipelines.
- A way to avoid data duplication:Maintain a single source of truth while projecting different views for different business needs.
- Data caching:Conduktor reduces networking costs and latency penalties by caching Kafka data.
Strategies to avoid business disruption
Shielded Kafka clusters and a good night's sleep while your Kafka Disaster Recovery Plan executes.
- Technical Rule Enforcement:Mechanism to prevent rogue Kafka client configurations that will cost your business.
- Disaster Recovery Solution:Seamless failover solution to reduce the cost implications of people, applications, and customers due to downtime.
Autonomy without risking cost explosion
Give your developer teams freedom while controlling affordable costs for your business.
- Topic Creation Control:Enforce limits on the number of partitions, giving you control over potentially spiralling costs.
- Efficient Kafka Storage:Conduktor helps manage storage efficiently, reducing costs associated with scaling, disk failures, and performance implications.
Take the next step in yourData Streaming journey
Harness the power of Kafka while shifting costs and focus on your core business needs.