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Optimizing Kafka Streams Applications

Confluent

Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. In what follows, we provide some context around how a processor topology was generated inside Kafka Streams before 2.1, Along with it, we will demonstrate a few known issues that impact efficiency of the generated processor topology.

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Announcing Complete Azure Observability for Kentik Cloud

Kentik

Kentik customers move workloads to (and from) multiple clouds, integrate existing hybrid applications with new cloud services, migrate to Virtual WAN to secure private network traffic, and make on-premises data and applications redundant to multiple clouds – or cloud data and applications redundant to the data center.

Cloud 105
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Kafka Streams’ Take on Watermarks and Triggers

Confluent

Whether Streams emits every single update or groups updates is irrelevant to the semantics of a data processing application. High-volume applications may not be able to process and transmit every update within the constraints of CPU, memory, network and disk. You get to focus on the logic of your data processing pipeline.

Topology 106
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Kentik Bridges the Intelligence Gap for Hybrid Cloud Networks

Kentik

IT resources, including those managed by Kubernetes and other container scheduling platforms, can be provisioned or de-provisioned in seconds creating surprising shifts in application delivery traffic. Go inside your cloud infrastructure to see how applications are communicating inside the cloud, to the internet, and your on-prem network.

Cloud 105
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Journey to Event Driven – Part 4: Four Pillars of Event Streaming Microservices

Confluent

Storing events in a stream and connecting streams via stream processors provide a generic, data-centric, distributed application runtime that you can use to build ETL, event streaming applications, applications for recording metrics and anything else that has a real-time data requirement. Let’s explore what this really means.

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Securing Your Network Against Attacks: Prevent, Detect, and Mitigate Cyberthreats

Kentik

This is compounded by recent trends of remote work, where network operators need to wrestle with the fact that employees often access the network via work sites with far less governance. Distributed denial of service (DDoS) DDoS attacks are cyber attacks that most often have the purpose of causing application downtime.

Network 94
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Reliable, Fast Access to On-Chain Data Insights

Confluent

On the event streaming side, we offer reliable low-latency data streams for financial applications based on Kafka Streams. Another interesting way of exposing data we’re looking into is the queryable state of Kafka Streams applications to expose the current state of forks happening and more. On our API instances, we use Socket.IO