Kafka Management and Monitoring with Nastel at the Kafka Summit
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These are the slides that I showed on our demo stand at the Kafka Summit London 2019. They show how Nastel provides management, monitoring, tracing and tracking for Kafka solutions as well as incorporating other technologies such as IBM MQ, Tibco EMS, MFT, IBM Event Streams.
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Kafka Management and Monitoring with Nastel at the Kafka Summit
- 1. Nastel Overview prepared for Kafka Summit London 2019 Park Plaza Westminster Bridge Hotel 13-14 May 2019 Sam Garforth sgarforth@nastel.com @samjgarforth
- 2. Nastel’s Solution – 360° Situational Awareness™ 2 ©2019 NASTEL TECHNOLOGIES, INC. MIDDLEWARE MANAGEMENT PROACTIVE MONITORING DIAGNOSTICS ANALYTICS TRACKING DECISION SUPPORT OS DBMS MIDDLE WARE APP STACK
- 3. Nastel Technologies Solution Offering 3 ©2016 NASTEL TECHNOLOGIES, INC. Nastel® Navigator – Automated discovery of middleware estate … Simplified configuration management … Full audit trail of changes (who, what, where) … Secure, granular delegation of specific authorities to Dev/Ops Nastel® AutoPilot – Easily managed, policy-based, real- time monitoring … Trend & pattern detection … notifications, proactive alerting … automated actions Nastel® XRay – Analytics, diagnostics, decision support and tracking … Tracking capabilities include full visibility of application message flows, in business context: resources, applications, events, timings, topologies
- 4. Middleware Management - Nastel Navigator 4 ©2019 NASTEL TECHNOLOGIES, INC.
- 5. Nastel AutoPilot for Kafka 5 ©2019 NASTEL TECHNOLOGIES, INC.
- 6. Nastel AutoPilot for Kafka 6 ©2019 NASTEL TECHNOLOGIES, INC.
- 7. Nastel XRay – Kafka Analytics 7 ©2019 NASTEL TECHNOLOGIES, INC.
- 8. Nastel XRay – Kafka Tracing 8 ©2019 NASTEL TECHNOLOGIES, INC. Show elapsed time of message workflows from start to end Drill down into details of messaging events & timings Show elapsed time of each message “hop” (event) Identify root cause : events & resources that may have contributed to increased time … CPU … contention Learn the topology of message flows Detect and alert upon exceptions based on historical data from prior messages flows Recognize changes in workflow timings such that a new baseline can be formed