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Nastel Announces AutoPilot for Apache Kafka

Nastel Technologies announced AutoPilot for Apache Kafka, new technology for problems commonly experienced in today’s complex hybrid IBM middleware stacks (MQ / IIB / DataPower) and Apache Kafka environments.

AutoPilot provides operational and transactional monitoring for Apache Kafka, the open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java.

Kafka is a unified, high-throughput, low-latency platform for handling real-time data feeds. It utilizes a massively scalable pub/sub message queue architected as a distributed transaction log, as its storage layer. It is often used by our clients as a transport for streaming data interconnected with other messaging and processing systems.

AutoPilot for Kafka provides the forensics used to diagnose Kafka problems. Performance and availability monitoring of Kafka is accomplished via end-to-end stream monitoring and tracking of metrics from brokers, consumers, producers and Zookeeper, Kafka’s configuration service.

AutoPilot examines the metrics collected for Kafka topics, producers, consumers and brokers as well as offering deep-dive insight into the JVM, itself.

AutoPilot for Kafka provides:

- Auto discovery of end-to-end transactions spanning Kafka and other technologies such as IBM MQ

- Parsing of Kafka messages which are tokenized and utilized for analytics and transaction stitching

- SLA Monitoring, Analytics and Reporting

- Deep-dive monitoring of composite application components that include Kafka

- Proactive alerting and reduction in false alarms

AutoPilot also utilizes Kafka internally as an integration technology for data transport.

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Nastel Announces AutoPilot for Apache Kafka

Nastel Technologies announced AutoPilot for Apache Kafka, new technology for problems commonly experienced in today’s complex hybrid IBM middleware stacks (MQ / IIB / DataPower) and Apache Kafka environments.

AutoPilot provides operational and transactional monitoring for Apache Kafka, the open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java.

Kafka is a unified, high-throughput, low-latency platform for handling real-time data feeds. It utilizes a massively scalable pub/sub message queue architected as a distributed transaction log, as its storage layer. It is often used by our clients as a transport for streaming data interconnected with other messaging and processing systems.

AutoPilot for Kafka provides the forensics used to diagnose Kafka problems. Performance and availability monitoring of Kafka is accomplished via end-to-end stream monitoring and tracking of metrics from brokers, consumers, producers and Zookeeper, Kafka’s configuration service.

AutoPilot examines the metrics collected for Kafka topics, producers, consumers and brokers as well as offering deep-dive insight into the JVM, itself.

AutoPilot for Kafka provides:

- Auto discovery of end-to-end transactions spanning Kafka and other technologies such as IBM MQ

- Parsing of Kafka messages which are tokenized and utilized for analytics and transaction stitching

- SLA Monitoring, Analytics and Reporting

- Deep-dive monitoring of composite application components that include Kafka

- Proactive alerting and reduction in false alarms

AutoPilot also utilizes Kafka internally as an integration technology for data transport.

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...