התחל במצב לא מקוון עם האפליקציה Player FM !
Monitoring Extreme-Scale Apache Kafka Using eBPF at New Relic
Manage episode 424666759 series 2510642
New Relic runs one of the larger Apache Kafka® installations in the world, ingesting circa 125 petabytes a month, or approximately three billion data points per minute. Anton Rodriguez is the architect of the system, responsible for hundreds of clusters and thousands of clients, some of them implemented in non-standard technologies. In addition to the large volume of servers, he works with many teams, which must all work together when issues arise.
Monitoring New Relic's large Kafka installation is critical and of course challenging, even for a company that itself specializes in monitoring. Specific obstacles include determining when rebalances are happening, identifying particularly old consumers, measuring consumer lag, and finding a way to observe all producing and consuming applications.
One way that New Relic has improved the monitoring of its architecture is by directly consuming metrics from the Linux kernel using its new eBPF technology, which lets programs run inside the kernel without changing source code or adding additional modules (the open-source tool Pixie enables access to eBPF in a Kafka context). eBPF is very low impact, so doesn’t affect services, and it allows New Relic to see what’s happening at the network level—and to take action as necessary.
EPISODE LINKS
- Monitoring Kafka Without Instrumentation Using eBPF
- What Is eBPF and Why Does It Matter for Observability?
- Kafka Monitoring
- Kafka Summit: Monitoring Kafka Without Instrumentation Using eBPF
- Watch the video version of this podcast
- Kris Jenkins’ Twitter
- Streaming Audio Playlist
- Join the Confluent Community
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Intro to Event-Driven Microservices with Confluent
- Use PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)
פרקים
1. Who watches the watchers? (00:00:00)
2. Intro (00:00:45)
3. Monitoring 125 petabytes of data (00:02:30)
4. Challenges (00:03:59)
5. Customer data in real time (00:08:29)
6. Monitoring data at scale (00:11:35)
7. eBPF and Kafka (00:13:32)
8. Pixie opens a new world of possibilities in Kafka monitoring (00:17:21)
9. eBPF and Pixie (00:24:12)
10. Use cases (00:25:59)
11. What is Pixie? (00:27:31)
12. Kafka Summit keynote (00:29:41)
13. Tips to get started with eBPF (00:34:32)
14. It's a wrap! (00:35:55)
265 פרקים
Manage episode 424666759 series 2510642
New Relic runs one of the larger Apache Kafka® installations in the world, ingesting circa 125 petabytes a month, or approximately three billion data points per minute. Anton Rodriguez is the architect of the system, responsible for hundreds of clusters and thousands of clients, some of them implemented in non-standard technologies. In addition to the large volume of servers, he works with many teams, which must all work together when issues arise.
Monitoring New Relic's large Kafka installation is critical and of course challenging, even for a company that itself specializes in monitoring. Specific obstacles include determining when rebalances are happening, identifying particularly old consumers, measuring consumer lag, and finding a way to observe all producing and consuming applications.
One way that New Relic has improved the monitoring of its architecture is by directly consuming metrics from the Linux kernel using its new eBPF technology, which lets programs run inside the kernel without changing source code or adding additional modules (the open-source tool Pixie enables access to eBPF in a Kafka context). eBPF is very low impact, so doesn’t affect services, and it allows New Relic to see what’s happening at the network level—and to take action as necessary.
EPISODE LINKS
- Monitoring Kafka Without Instrumentation Using eBPF
- What Is eBPF and Why Does It Matter for Observability?
- Kafka Monitoring
- Kafka Summit: Monitoring Kafka Without Instrumentation Using eBPF
- Watch the video version of this podcast
- Kris Jenkins’ Twitter
- Streaming Audio Playlist
- Join the Confluent Community
- Learn more with Kafka tutorials, resources, and guides at Confluent Developer
- Live demo: Intro to Event-Driven Microservices with Confluent
- Use PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)
פרקים
1. Who watches the watchers? (00:00:00)
2. Intro (00:00:45)
3. Monitoring 125 petabytes of data (00:02:30)
4. Challenges (00:03:59)
5. Customer data in real time (00:08:29)
6. Monitoring data at scale (00:11:35)
7. eBPF and Kafka (00:13:32)
8. Pixie opens a new world of possibilities in Kafka monitoring (00:17:21)
9. eBPF and Pixie (00:24:12)
10. Use cases (00:25:59)
11. What is Pixie? (00:27:31)
12. Kafka Summit keynote (00:29:41)
13. Tips to get started with eBPF (00:34:32)
14. It's a wrap! (00:35:55)
265 פרקים
كل الحلقات
×ברוכים הבאים אל Player FM!
Player FM סורק את האינטרנט עבור פודקאסטים באיכות גבוהה בשבילכם כדי שתהנו מהם כרגע. זה יישום הפודקאסט הטוב ביותר והוא עובד על אנדרואיד, iPhone ואינטרנט. הירשמו לסנכרון מנויים במכשירים שונים.